essay on artificial intelligence a threat to employment

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• Published: 18 January 2024

The impact of artificial intelligence on employment: the role of virtual agglomeration

• Yang Shen   ORCID: orcid.org/0000-0002-6781-6915 1 &
• Xiuwu Zhang 1  

Humanities and Social Sciences Communications volume  11 , Article number:  122 ( 2024 ) Cite this article

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• Development studies

Sustainable Development Goal 8 proposes the promotion of full and productive employment for all. Intelligent production factors, such as robots, the Internet of Things, and extensive data analysis, are reshaping the dynamics of labour supply and demand. In China, which is a developing country with a large population and labour force, analysing the impact of artificial intelligence technology on the labour market is of particular importance. Based on panel data from 30 provinces in China from 2006 to 2020, a two-way fixed-effect model and the two-stage least squares method are used to analyse the impact of AI on employment and to assess its heterogeneity. The introduction and installation of artificial intelligence technology as represented by industrial robots in Chinese enterprises has increased the number of jobs. The results of some mechanism studies show that the increase of labour productivity, the deepening of capital and the refinement of the division of labour that has been introduced into industrial enterprises through the introduction of robotics have successfully mitigated the damaging impact of the adoption of robot technology on employment. Rather than the traditional perceptions of robotics crowding out labour jobs, the overall impact on the labour market has exerted a promotional effect. The positive effect of artificial intelligence on employment exhibits an inevitable heterogeneity, and it serves to relatively improves the job share of women and workers in labour-intensive industries. Mechanism research has shown that virtual agglomeration, which evolved from traditional industrial agglomeration in the era of the digital economy, is an important channel for increasing employment. The findings of this study contribute to the understanding of the impact of modern digital technologies on the well-being of people in developing countries. To give full play to the positive role of artificial intelligence technology in employment, we should improve the social security system, accelerate the process of developing high-end domestic robots and deepen the reform of the education and training system.

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Introduction.

Ensuring people’s livelihood requires diligence, but diligence is not scarce. Diversification, technological upgrading, and innovation all contribute to achieving the Sustainable Development Goal of full and productive employment for all (SDGs 8). Since the outbreak of the industrial revolution, human society has undergone four rounds of technological revolution, and each technological change can be regarded as the deepening of automation technology. The conflict and subsequent rebalancing of efficiency and employment are constantly being repeated in the process of replacing people with machines (Liu 2018 ; Morgan 2019 ). When people realize the new wave of human economic and social development that is created by advanced technological innovation, they must also accept the “creative destruction” brought by the iterative renewal of new technologies (Michau 2013 ; Josifidis and Supic 2018 ; Forsythe et al. 2022 ). The questions of where technology will eventually lead humanity, to what extent artificial intelligence will change the relationship between humans and work, and whether advanced productivity will lead to large-scale structural unemployment have been hotly debated. China has entered a new stage of deep integration and development of the “new technology cluster” that is represented by the internet and the real economy. Physical space, cyberspace, and biological space have become fully integrated, and new industries, new models, and new forms of business continue to emerge. In the process of the vigorous development of digital technology, its characteristics in terms of employment, such as strong absorption capacity, flexible form, and diversified job demands are more prominent, and many new occupations have emerged. The new practice of digital survival that is represented by the platform economy, sharing economy, full-time economy, and gig economy, while adapting to, leading to, and innovating the transformation and development of the economy, has also led to significant changes in employment carriers, employment forms, and occupational skill requirements (Dunn 2020 ; Wong et al. 2020 ; Li et al. 2022 ).

Artificial intelligence (AI) is one of the core areas of the fourth industrial revolution, along with the transformation of the mechanical technology, electric power technology, and information technology, and it serves to promote the transformation and upgrading of the digital economy industry. Indeed, the rapid iteration and cross-border integration of general information technology in the era of the digital economy has made a significant contribution to the stabilization of employment and the promotion of growth, but this is due only to the “employment effect” caused by the ongoing development of the times and technological progress in the field of social production. Digital technology will inevitably replace some of the tasks that were once performed by human labour. In recent years, due to the influence of China’s labour market and employment structure, some enterprises have needed help in recruiting workers. Driven by the rapid development of artificial intelligence technology, some enterprises have accelerated the pace of “machine replacement,” resulting in repetitive and standardized jobs being performed by robots. Deep learning and AI enable machines and operating systems to perform more complex tasks, and the employment prospects of enterprise employees face new challenges in the digital age. According to the Future of Jobs 2020 report released by the World Economic Forum, the recession caused by the COVID-19 pandemic and the rapid development of automation technology are changing the job market much faster than expected, and automation and the new division of labour between humans and machines will disrupt 85 million jobs in 15 industries worldwide over the next five years. The demand for skilled jobs, such as data entry, accounting, and administrative services, has been hard hit. Thanks to the wave of industrial upgrading and the vigorous development of digitalization, the recruitment demand for AI, big data, and manufacturing industries in China has maintained high growth year-on-year under the premise of macroenvironmental uncertainty during the period ranging from 2019 to 2022, and the average annual growth rate of new jobs was close to 30%. However, this growth has also aggravated the sense of occupational crisis among white-collar workers. The research shows that the agriculture, forestry, animal husbandry, fishery, mining, manufacturing, and construction industries, which are expected to adopt a high level of intelligence, face a high risk of occupational substitution, and older and less educated workers are faced with a very high risk of substitution (Wang et al. 2022 ). Whether AI, big data, and intelligent manufacturing technology, as brand-new forms of digital productivity, will lead to significant changes in the organic composition of capital and effectively decrease labour employment has yet to reach consensus. As the “pearl at the top of the manufacturing crown,” a robot is an essential carrier of intelligent manufacturing and AI technology as materialized in machinery and equipment, and it is also an important indicator for measuring a country’s high-end manufacturing industry. Due to the large number of manufacturing employees in China, the challenge of “machine substitution” to the labour market is more severe than that in other countries, and the use of AI through robots is poised to exert a substantial impact on the job market (Xie et al. 2022 ). In essence, the primary purpose of the digital transformation of industrial enterprises is to improve quality and efficiency, but the relationship between machines and workers has been distorted in the actual application of digital technology. Industrial companies use robots as an entry point, and the study delves into the impact of AI on the labour market to provide experience and policy suggestions on the best ways of coordinating the relationship between enterprise intelligent transformation and labour participation and to help realize Chinese-style modernization.

As a new general technology, AI technology represents remarkable progress in productivity. Objectively analysing the dual effects of substitution and employment creation in the era of artificial intelligence to actively integrate change and adapt to development is essential to enhancing comprehensive competitiveness and better qualifying workers for current and future work. This research is organized according to a research framework from the published literature (Luo et al. 2023 ). In this study, we used data published by the International Federation of Robotics (IFR) and take the installed density of industrial robots in China as the main indicator of AI. Based on panel data from 30 provinces in China covering the period from 2006–2020, the impact of AI technology on employment in a developing country with a large population size is empirically examined. The issues that need to be solved in this study include the following: The first goal is to examine the impact of AI on China’s labour market from the perspective of the economic behaviour of those enterprises that have adopted the use of industrial robots in production. The realistic question we expect to answer is whether the automated processing of daily tasks has led to unemployment in China during the past fifteen years. The second goal is to answer the question of how AI will continue to affect the employment market by increasing labour productivity, changing the technical composition of capital, and deepening the division of labour. The third goal is to examine how the transformation of industrial organization types in the digital economy era affects employment through digital industrial clusters or virtual clusters. The fourth goal is to test the role of AI in eliminating gender discrimination, especially in regard to whether it can improve the employment opportunities of female employees. Then, whether workers face different employment difficulties in different industry attributes is considered. The final goal is to provide some policy insights into how a developing country can achieve full employment in the face a new technological revolution in the context of a large population and many low-skilled workers.

The remainder of the paper is organized as follows. In Section Literature Review, we summarize the literature on the impact of AI on the labour market and employment and classify it from three perspectives: pessimistic, negative, and neutral. Based on a literature review, we then summarize the marginal contribution of this study. In Section Theoretical mechanism and research hypothesis, we provide a theoretical analysis of AI’s promotion of employment and present the research hypotheses to be tested. In Section Study design and data sources, we describe the data source, variable setting and econometric model. In Section Empirical analysis, we test Hypothesis 1 and conduct a robustness test and the causal identification of the conclusion. In Section Extensibility analysis, we test Hypothesis 2 and Hypothesis 3, as well as testing the heterogeneity of the baseline regression results. The heterogeneity test employee gender and industry attributes increase the relevance of the conclusions. Finally, Section Conclusions and policy implications concludes.

Literature review

The social effect of technological progress has the unique characteristics of the times and progresses through various stages, and there is variation in our understanding of its development and internal mechanism. A classic argument of labour sociology and labour economics is that technological upgrading objectively causes workers to lose their jobs, but the actual historical experience since the industrial revolution tells us that it does not cause large-scale structural unemployment (Zhang 2023a ). While neoclassical liberals such as Adam Smith claimed that technological progress would not lead to unemployment, other scholars such as Sismondi were adamant that it would. David Ricardo endorsed the “Luddite fear” in his book On Machinery, and Marx argued that technological progress can increase labour productivity while also excluding labour participation, thus leaving workers in poverty. The worker being turned ‘into a crippled monstrosity’ by modern machinery. Technology is not used to reduce working hours and improve the quality of work, rather, it is used to extend working hours and speed up work (Spencer 2023 ). According to Schumpeter’s innovation theory, within a unified complex system, the essence of technological innovation forms from the unity of positive and negative feedback and the oneness of opposites such as “revolutionary” and “destructive.” Even a tiny technological impact can cause drastic consequences. The impact of AI on employment is different from the that of previous industrial revolutions, and it is exceptional in that “machines” are no longer straightforward mechanical tools but have assumed more of a “worker” role, just as people who can learn and think tend to do (Boyd and Holton 2018 ). AI-related technologies continue to advance, the industrialization and commercialization process continues to accelerate, and the industry continues to explore the application of AI across multiple fields. Since AI was first proposed at the Dartmouth Conference in 1956, discussions about “AI replacing human labor” and “AI defeating humans” have endlessly emerged. This dynamic has increased in intensity since the emergence of ChatGPT, which has aroused people’s concerns about technology replacing the workforce. Summarizing the literature, we can find three main arguments concerning the relationship between AI and employment:

First, AI has the effect of creating and filling jobs. The intelligent manufacturing industry paradigm characterized by AI technology will assist in forming a high-quality “human‒machine cooperation” employment mode. In an enlightened society, the social state of shared prosperity benefits the lowest class of people precisely because of the advanced productive forces and higher labour efficiency created through the refinement of the division of labour. By improving production efficiency, reducing the sales price of final products, and stimulating social consumption, technological progress exerts both price effects and income effects, which in turn drive related enterprises to expand their production scale, which, in turn, increases the demand for labour (Li et al. 2021 ; Ndubuisi et al. 2021 ; Yang 2022 ; Sharma and Mishra 2023 ; Li et al. 2022 ). People habitually regard robots as competitors for human beings, but this view only represents the materialistic view of traditional machinery. The coexistence of man and machine is not a zero-sum game. When the task evolves from “cooperation for all” to “cooperation between man and machine,” it results in fewer production constraints and maximizes total factor productivity, thus creating more jobs and generating novel collaborative tasks (Balsmeier and Woerter 2019 ; Duan et al. 2023 ). At the same time, materialized AI technology can improve the total factor production efficiency in ways that are suitable for its factor endowment structure and improve the production efficiency between upstream and downstream enterprises in the industrial chain and the value chain. This increase in the efficiency of the entire market will subsequently drive the expansion of the production scale of enterprises and promote reproduction, and its synergy will promote the synchronous growth of the labour demand involving various skills, thus resulting in a creative effect (Liu et al. 2022 ). As an essential force in the fourth industrial revolution, AI inevitably affects the social status of humans and changes the structure of the labour force (Chen 2023 ). AI and machines increase labour productivity by automating routine tasks while expanding employee skills and increasing the value of work. As a result, in a machine-for-machine employment model, low-skilled jobs will disappear, while new and currently unrealized job roles will emerge (Polak 2021 ). We can even argue that digital technology, artificial intelligence, and robot encounters are helping to train skilled robots and raise their relative wages (Yoon 2023 ).

Second, AI has both a destructive effect and a substitution effect on employment. As soon as machines emerged as the means of labour, they immediately began to compete with the workers themselves. As a modern new technology, artificial intelligence is essentially humanly intelligent labour that condenses complex labour. Like the disruptive general-purpose technologies of early industrialization, automation technologies such as AI offer both promise and fear in regard to “machine replacement.” Technological progress leads to an increase in the organic composition of capital and the relative surplus population. The additional capital formed in capital accumulation comes to absorb fewer and fewer workers compared to its quantity. At the same time, old capital, which is periodically reproduced according to the new composition, will begin to increasingly exclude the workers it previously employed, resulting in severe “technological unemployment.” The development of productivity creates more free time, especially in industries such as health care, transportation, and production environment control, which have seen significant benefits from AI. In recent years, however, some industrialized countries have faced the dilemma of declining income from labour and the slow growth of total labour productivity while applying AI on a large scale (Autor 2019 ). Low-skilled and incapacitated workers enjoy a high probability of being replaced by automation (Ramos et al. 2022 ; Jetha et al. 2023 ). It is worth noting that with the in-depth development of digital technologies, such as deep learning and big data analysis, some complex, cognitive, and creative jobs that are currently considered irreplaceable in the traditional view will also be replaced by AI, which indicates that automation technology is not only a substitute for low-skilled labour (Zhao and Zhao 2017 ; Dixon et al. 2021 ; Novella et al. 2023 ; Nikitas et al. 2021 ). Among factors, AI and robotics exert a particularly significant impact on the manufacturing job market, and industry-related jobs will face a severe unemployment problem due to the disruptive effect of AI and robotics (Zhou and Chen 2022 ; Sun and Liu 2023 ). At this stage, most of the world’s economies are facing the deep integration of the digital wave in their national economy, and any work, including high-level tasks, is being affected by digitalization and AI (Gardberg et al. 2020 ). The power of AI models is growing exponentially rather than linearly, and the rapid development and rapid diffusion of technology will undoubtedly have a devastating effect on knowledge workers, as did the industrial revolution (Liu and Peng 2023 ). In particular, the development and improvement of AI-generated content in recent years poses a more significant threat to higher-level workers, such as researchers, data analysts, and product managers, than to physical labourers. White collar workers are facing unprecedented anxiety and unease (Nam 2019 ; Fossen and Sorgner 2022 ; Wang et al. 2023 ). A classic study suggests that AI could replace 47% of the 702 job types in the United States within 20 years (Frey and Osborne 2017 ). Since the 2020 epidemic, digitization has accelerated, and online and digital resources have become a must for enterprises. Many occupations are gradually moving away from humans (Wu and Yang 2022 ; Männasoo et al. 2023 ). It is obvious that the intelligent robot arm on the factory assembly line is poised to allow factory assembly line workers to exit the stage and move into history. Career guides are being replaced by mobile phone navigation software.

Third, the effect of AI on employment is uncertain, and its impact on human work does not fall into a simple “utopian” or “dystopian” scene, but rather leads to a combination of “utopia” and “dystopia” (Kolade and Owoseni 2022 ). The job-creation effects of robotics and the emergence of new jobs that result from technological change coexist at the enterprise level (Ni and Obashi 2021 ). Adopting a suitable AI operation mode can adjust for the misallocation of resources by the market, enterprises, and individuals to labour-intensive tasks, reverse the nondirectional allocation of robots in the labour sector, and promote their reallocation in the manufacturing and service industries. The size of the impact on employment through the whole society is uncertain (Fabo et al. 2017 ; Huang and Rust 2018 ; Berkers et al. 2020 ; Tschang and Almirall 2021 ; Reljic et al. 2021 ). For example, Oschinski and Wyonch ( 2017 ) claimed that those jobs that are easily replaced by AI technology in Canada account for only 1.7% of the total labour market, and they have yet to find evidence that automation technology will cause mass unemployment in the short term. Wang et al. ( 2022 ) posited that the impact of industrial robots on labour demand in the short term is mainly negative, but in the long run, its impact on employment is mainly that of job creation. Kirov and Malamin ( 2022 ) claimed that the pessimism underlying the idea that AI will destroy the jobs and quality of language workers on a large scale is unjustified. Although some jobs will be eliminated as such technology evolves, many more will be created in the long run.

In the view that modern information technology and digital technology increase employment, the literature holds that foreign direct investment (Fokam et al. 2023 ), economic systems (Bouattour et al. 2023 ), labour skills and structure (Yang 2022 ), industrial technological intensity (Graf and Mohamed 2024 ), and the easing of information friction (Jin et al. 2023 ) are important mechanisms. The research on whether AI technology crowds out jobs is voluminous, but the conclusions are inconsistent (Filippi et al. 2023 ). This paper is focused on the influence of AI on the employment scale of the manufacturing industry, examines the job creation effect of technological progress from the perspectives of capital deepening, labour refinement, and labour productivity, and systematically examines the heterogeneous impact of the adoption of industrial robots on employment demand, structure, and different industries. The marginal contributions of this paper are as follows: first, the installation density of industrial robots is used as an indicator to measure AI, and the question of whether AI has had negative effects on employment in the manufacturing sector from the perspective of machine replacement is examined. The second contribution is the analysis of the heterogeneity of AI’s employment creation effect from the perspective of gender and industry attributes and the claim that women and the employees of labour-intensive enterprises are more able to obtain additional work benefits in the digital era. Most importantly, in contrast to the literature, this paper innovatively introduces virtual agglomeration into the path mechanism of the effect of robots on employment and holds that information technologies such as the internet, big data, and the industrial Internet of Things, which rely upon AI, have reshaped the management mode and organizational structure of enterprises. Online and offline integration work together, and information, knowledge, and technology are interconnected. In the past, the job matching mode of one person, one post, and specific individuals has changed into a multiple faceted set of tasks involving one person, many posts, and many types of people. The internet platform spawned by digital technology frees the employment mode of enterprises from being limited to single enterprises and specific gathering areas. Traditional industrial geographical agglomeration has gradually evolved into virtual agglomeration, which geometrically enlarges the agglomeration effect and mechanism and enhances the spillover effect. In the online world, individual practitioners and entrepreneurs can obtain orders, receive training, connect resources and employment needs more widely and efficiently, and they can achieve higher-quality self-employment. Virtual agglomeration has become a new path by which AI affects employment. Another literature contribution is that this study used the linear regression model of the machine learning model in the robustness test part, which verified the employment creation effect of AI from the perspective of positive contribution proportion. In causal identification, this study innovatively uses the industrial feed-in price as a tool variable to analyse the causal path of AI promoting employment.

Theoretical mechanism and research hypothesis

The direct influence of ai on employment.

With advances in machine learning, big data, artificial intelligence, and other technologies, a new generation of intelligent robots that can perform routine, repetitive, and regular production tasks requiring human judgement, problem-solving, and analytical skills has emerged. Robotic process automation technology can learn and imitate the way that workers perform repeated new tasks regarding the collecting of data, running of reports, copying of data, checking of data integrity, reading, processing, and the sending of emails, and it can play an essential role in processing large amounts of data (Alan 2023 ). In the context of an informatics- and technology-oriented economy, companies are asking employees to transition into creative jobs. According to the theory of the combined task framework, the most significant advantage of the productivity effect produced by intelligent technology is creation of new demands, that is, the creation of new tasks (Acemoglu and Restrepo 2018 ). These new task packages update the existing tasks and create new task combinations with more complex technical difficulties. Although intelligent technology is widely used in various industries, it may have a substitution effect on workers and lead to technical unemployment. However, with the rise of a new round of technological innovation and revolution, high efficiency leads to the development and growth of a series of emerging industries and exerts job creation effects. Technological progress has the effect of creating new jobs. That is, such progress creates new jobs that are more in line with the needs of social development and thus increases the demand for labour (Borland and Coelli 2017 ). Therefore, the intelligent development of enterprises will come to replace their initial programmed tasks and produce more complex new tasks, and human workers in nonprogrammed positions, such as technology and knowledge, will have more comparative advantages.

Generally, the “new technology-economy” paradigm that is derived from automation machine and AI technology is affecting the breadth and depth of employment, which is manifested as follows:

It reduces the demand for coded jobs in enterprises while increasing the demand for nonprogrammed complex labour.

The development of digital technology has deepened and refined the division of labour, accelerated the service trend of the manufacturing industry, increased the employment share of the modern service industry and created many emerging jobs.

Advanced productive forces give workers higher autonomy and increased efficiency in their work, improving their job satisfaction and employment quality. As described in Das Kapital, “Although machines actually crowd out and potentially replace a large number of workers, with the development of machines themselves (which is manifested by the increase in the number of the same kind of factories or the expansion of the scale of existing factories), the number of factory workers may eventually be more than the number of handicraft workers in the workshops or handicrafts that they crowd out… It can be seen that the relative reduction and absolute increase of employed workers go hand in hand” (Li and Zhang 2022 ).

Internet information technology reduces the distance between countries in both time and space, promotes the transnational flow of production factors, and deepens the international division of labour. The emergence of AI technology leads to the decline of a country’s traditional industries and departments. Under the new changes to the division of labour, these industries and departments may develop in late-developing countries and serve to increase their employment through international labour export.

From a long-term perspective, AI will create more jobs through the continuous expansion of the social production scale, the continuous improvement of production efficiency, and the more detailed industrial categories that it engenders. With the accumulation of human capital under the internet era, practitioners are gradually becoming liberated from heavy and dangerous work, and workers’ skills and job adaptability will undergo continuous improvement. The employment creation and compensation effects caused by technological and industrial changes are more significant than the substitution effects (Han et al. 2022 ). Accordingly, the article proposes the following two research hypotheses:

Hypothesis 1 (H1): AI increases employment .

Hypothesis 2 (H2): AI promotes employment by improving labour productivity, deepening capital, and refining the division of labour .

Role of virtual agglomeration

The research on economic geography and “new” economic geography agglomeration theory focuses on industrial agglomeration in the traditional sense. This model is a geographical agglomeration model that depends on spatial proximity from a geographical perspective. Assessing the role of externalities requires a particular geographical scope, as it has both physical and scope limitations. Virtual agglomeration transcends Marshall’s theory of economies of scale, which is not limited to geographical agglomeration from the perspective of natural territory but rather takes on more complex and multidimensional forms (such as virtual clusters, high-tech industrial clusters, and virtual business circles). Under the influence of a new generation of digital technology that is characterized by big data, the Internet of Things, and the industrial internet, the digital, intelligent, and platform transformation trend is prominent in some industries and enterprises, and industrial digitalization and digital industrialization jointly promote industrial upgrading. The innovation of information technology leads to “distance death” (Schultz 1998 ). With the further materialization of digital and networked services of enterprises, the trading mode of digital knowledge and services, such as professional knowledge, information combination, cultural products, and consulting services, has transitioned from offline to digital trade, and the original geographical space gathering mode between enterprises has gradually evolved into a virtual network gathering that places the real-time exchange of data and information as its core (Wang et al. 2018 ). Tan and Xia ( 2022 ) stated that virtual agglomeration geometrically magnifies the social impact of industrial agglomeration mechanisms and agglomeration effects, and enterprises in the same industry and their upstream and downstream affiliated enterprises can realize low-cost long-distance transactions, services, and collaborative production through digital trade, resulting in large-scale zero-distance agglomeration along with neighbourhood-style production, service, circulation, and consumption. First, the knowledge and information underlying the production, design, research and development, organization, and trading of all kinds of enterprises are increasingly being completed by digital technology. The tacit knowledge that used to require face-to-face communication has become codable, transmissible, and reproducible under digital technology. Tacit knowledge has gradually become explicit, and knowledge spillover and technology diffusion have become more pronounced, which further leads to an increase in the demand for unconventional task labour (Zhang and Li 2022 ). Second, the cloud platform causes the labour pool effect of traditional geographical agglomeration to evolve into the labour “conservation land” of virtual agglomeration, and employment is no longer limited to the internal organization or constrained within a particular regional scope. Digital technology allows enterprises to hire “ghost workers” for lower wages to compensate for the possibility of AI’s “last mile.” Information technology and network platforms seek connections with all social nodes, promoting the time and space for work in a way that transcends standardized fixed frameworks. At the same time, joining or quitting work tasks, indirectly increasing the temporary and transitional nature of work and forming a decentralized management organization model of supplementary cooperation, social networks, industry experts, and skilled labour all become more convenient for workers (Wen and Liu 2021 ). With a mobile phone and a computer, labourers worldwide can create value for enterprises or customers, and the forms of labour are becoming more flexible and diverse. Workers can provide digital real-time services to employers far away from their residence, and they can also obtain flexible employment information and improve their digital skills through the leveraging of digital resources, resulting in the odd-job economy, crowdsourcing economy, sharing economy, and other economic forms. Finally, the network virtual space can accommodate almost unlimited enterprises simultaneously. In the commercial background of digital trade, while any enterprise can obtain any intermediate supply in the online market, its final product output can instantly become the intermediate input of other enterprises. Therefore, enterprises’ raw material supply and product sales rely on the whole market. At this time, the market scale effect of intermediate inputs can be infinitely amplified, as it is no longer confined to the limited space of geographical agglomeration (Duan and Zhang 2023 ). Accordingly, the following research hypothesis is proposed:

Hypothesis 3 (H3): AI promotes employment by improving the VA of enterprises .

Study design and data sources

Variable setting, explained variable.

Employment scale (ES). Compared with the agriculture and service industry, the industrial sector accommodates more labour, and robot technology is mainly applied in the industrial sector, which has the greatest demand shock effect on manufacturing jobs. In this paper, we select the number of employees in manufacturing cities and towns as the proxy variable for employment scale.

Core explanatory variable

Artificial intelligence (AI). Emerging technologies endow industrial robots with more complete technical attributes, which increases their ability to act as human beings in many work projects, enabling them to either independently complete production tasks or to assist humans in completing such tasks. This represents an important form of AI technology embedded into machinery and equipment. In this paper, the installation density of industrial robots is selected as the proxy variable for AI. Robot data mainly come from the number of robots installed in various industries at various national levels as published by the International Federation of Robotics (IFR). Because the dataset published by the IFR provides the dataset at the national-industry level and its industry classification standards are significantly different from those in China, the first lessons for this paper are drawn from the practices of Yan et al. ( 2020 ), who matches the 14 manufacturing categories published by the IFR with the subsectors in China’s manufacturing sector, and then uses the mobile share method to merge and sort out the employment numbers of various industries in various provinces. First, the national subsector data provided by the IFR are matched with the second National Economic Census data. Next, the share of employment in different industries to the total employment in the province is used to develop weights and decompose the industry-level robot data into the local “provincial-level industry” level. Finally, the application of robots in various industries at the provincial level is summarized. The Bartik shift-share instrumental variable is now widely used to measure robot installation density at the city (province) level (Wu 2023 ; Yang and Shen, 2023 ; Shen and Yang 2023 ). The calculation process is as follows:

In Eq. ( 1 ), N is a collection of manufacturing industries, Robot it is the robot installation density of province i in year t, \({{{\mathrm{employ}}}}_{{{{\mathrm{ij}}}},{{{\mathrm{t}}}} = 2006}\) is the number of employees in industry j of province i in 2006, \({{{\mathrm{employ}}}}_{{{{\mathrm{i}}}},{{{\mathrm{t}}}} = 2006}\) is the total number of employees in province i in 2006, and \({{{\mathrm{Robot}}}}_{{{{\mathrm{jt}}}}}{{{\mathrm{/employ}}}}_{{{{\mathrm{i}}}},{{{\mathrm{t}}}} = 2006}\) represents the robot installation density of each year and industry level.

Mediating variables

Labour productivity (LP). According to the definition and measurement method proposed by Marx’s labour theory of value, labour productivity is measured by the balance of the total social product minus the intermediate goods and the amount of labour consumed by the pure production sector. The specific calculation process is \(AL = Y - k/l\) , where Y represents GDP, l represents employment, k represents capital depreciation, and AL represents labour productivity. Capital deepening (CD). The per capita fixed capital stock of industrial enterprises above a designated size is used in this study as a proxy variable for capital deepening. The division of labour refinement (DLR) is refined and measured by the number of employees in producer services. Virtual agglomeration (VA) is mainly a continuation of the location entropy method in the traditional industrial agglomeration measurement idea, and weights are assigned according to the proportion of the number of internet access ports in the country. Because of the dependence of virtual agglomeration on digital technology and network information platforms, the industrial agglomeration degree of each region is first calculated in this paper by using the number of information transmissions, computer services, and software practitioners and then multiplying that number by the internet port weight. The specific expression is \(Agg_{it} = \left( {M_{it}/M_t} \right)/\left( {E_{it}/E_t} \right) \times \left( {Net_{it}/Net_t} \right)\) , where \(M_{it}\) represents the number of information transmissions, computer services and software practitioners in region i in year t, \(M_t\) represents the total number of national employees in this industry, \(E_{it}\) represents the total number of employees in region i, \(E_t\) represents the total number of national employees, \(Net_{it}\) represents the number of internet broadband access ports in region i, and \(Net_t\) represents the total number of internet broadband access ports in the country. VA represents the degree of virtual agglomeration.

Control variables

To avoid endogeneity problems caused by unobserved variables and to obtain more accurate estimation results, seven control variables were also selected. Road accessibility (RA) is measured by the actual road area at the end of the year. Industrial structure (IS) is measured by the proportion of the tertiary industry’s added value and the secondary industry’s added value. The full-time equivalent of R&D personnel is used to measure R&D investment (RD). Wage cost (WC) is calculated using city average salary as a proxy variable; Marketization (MK) is determined using Fan Gang marketization index as a proxy variable; Urbanization (UR) is measured by the proportion of the urban population to the total population at the end of the year; and the proportion of general budget expenditure to GDP is used to measure Macrocontrol (MC).

Econometric model

To investigate the impact of AI on employment, based on the selection and definition of the variables detailed above and by mapping the research ideas to an empirical model, the following linear regression model is constructed:

In Eq. ( 2 ), ES represents the scale of manufacturing employment, AI represents artificial intelligence, and subscripts t, i and m represent time t, individual i and the m th control variable, respectively. \(\mu _i\) , \(\nu _t\) and \(\varepsilon _{it}\) represent the individual effect, time effect and random disturbance terms, respectively. \(\delta _0\) is the constant term, a is the parameter to be fitted, and Control represents a series of control variables. To further test whether there is a mediating effect of mechanism variables in the process of AI affecting employment, only the influence of AI on mechanism variables is tested in the empirical part according to the modelling process and operational suggestions of the intermediary effects as proposed by Jiang ( 2022 ) to overcome the inherent defects of the intermediary effects. On the basis of Eq. ( 2 ), the following econometric model is constructed:

In Eq. ( 3 ), Media represents the mechanism variable. β 1 represents the degree of influence of AI on mechanism variables, and its significance and symbolic direction still need to be emphasized. The meanings of the remaining symbols are consistent with those of Eq. ( 2 ).

Data sources

Following the principle of data availability, the panel data of 30 provinces (municipalities and autonomous regions) in China from 2006 to 2020 (samples from Tibet and Hong Kong, Macao, and Taiwan were excluded due to data availability) were used as statistical investigation samples. The raw data on the installed density of industrial robots and the number of workers in the manufacturing industry come from the International Federation of Robotics and the China Labour Statistics Yearbook. The original data for the remaining indicators came from the China Statistical Yearbook, China Population and Employment Statistical Yearbook, China’s Marketization Index Report by Province (2021), the provincial and municipal Bureau of Statistics, and the global statistical data analysis platform of the Economy Prediction System (EPS). The few missing values are supplemented through linear interpolation. It should be noted that although the IFR has yet to release the number of robots installed at the country-industry level in 2020, it has published the overall growth rate of new robot installations, which is used to calculate the robot stock in 2020 for this study. The descriptive statistical analysis of relevant variables is shown in Table 1 .

Empirical analysis

To reduce the volatility of the data and address the possible heteroscedasticity problem, all the variables are located. The results of the Hausmann test and F test both reject the null hypothesis at the 1% level, indicating that the fixed effect model is the best-fitting model. Table 2 reports the fitting results of the baseline regression.

As shown in Table 2 , the results of the two-way fixed-effect (TWFE) model displayed in Column (5) show that the fitting coefficient of AI on employment is 0.989 and is significant at the 1% level. At the same time, the fitting results of other models show that the impact of AI on employment is significantly positive. The results confirm that the effect of AI on employment is positive and the effect of job creation is greater than the effect of destruction, and these conclusions are robust, thus verifying the employment creation mechanism of technological progress. Research Hypothesis 1 (H1) is supported. The new round of scientific and technological revolution represented by artificial intelligence involves the upgrading of traditional industries, the promotion of major changes in the economy and society, the driving of rapid development of the “unmanned economy,” the spawning a large number of new products, new technologies, new formats, and new models, and the provision of more possibilities for promoting greater and higher quality employment. Classical and neoclassical economics view the market mechanism as a process of automatic correction that can offset the job losses caused by labour-saving technological innovation. Under the premise of the “employment compensation” theory, the new products, new models, and new industrial sectors created by the progress of AI technology can directly promote employment. At the same time, the scale effect caused by advanced productivity results in lower product prices and higher worker incomes, which drives increased demand and economic growth, increasing output growth and employment (Ge and Zhao 2023 ). In conjunction with the empirical results of this paper, we have reason to believe that enterprises adopt the strategy of “machine replacement” to replace procedural and repetitive labour positions in the pursuit of high efficiency and high profits. However, AI improves not only enterprises’ production efficiency but also their production capacity and scale economy. To occupy a favourable share of market competition, enterprises expand the scale of reproduction. At this point, new and more complex tasks continue to emerge, eventually leading companies to hire more labour. At this stage, robot technology and application in developing countries are still in their infancy. Whether regarding the application scenario or the application scope of robots, the automation technology represented by industrial robots has not yet been widely promoted, which increases the time required for the automation technology to completely replace manual tasks, so the destruction effect of automation technology on jobs is not apparent. The fundamental market situation of the low cost of China’s labour market drives enterprises to pay more attention to technology upgrading and efficiency improvement when introducing industrial robots. The implementation of the machine replacement strategy is mainly caused by the labour shortage driven by high work intensity, high risk, simple process repetition, and poor working conditions. The intelligent transformation of enterprises points to more than the simple saving of labour costs (Dixon et al. 2021 ).

Robustness test

The above results show that the effect of AI on job creation is greater than the effect of substitution and the overall promotion of enterprises for the enhancement of employment demand. To verify the robustness of the benchmark results, the following three means of verifying the results are adopted in this study. First, we replace the explained variables. In addition to industrial manufacturing, robots are widely used in service industries, such as medical care, finance, catering, and education. To reflect the dynamic change relationship between the employment share of the manufacturing sector and the employment number of all sectors, the absolute number of manufacturing employees is replaced by the ratio of the manufacturing industry to all employment numbers. The second means is increasing the missing variables. Since many factors affect employment, this paper considers the living cots, human capital, population density, and union power in the basic regression model. The impact of these variables on employment is noticeable; for example, the existence of trade unions improves employee welfare and the working environment but raises the entry barrier for workers in the external market. The new missing variables are the average selling price of commercial and residential buildings, urban population density (person/square kilometre), nominal human capital stock, and the number of grassroots trade union organizations in the China Human Capital Report 2021 issued by Central University of Finance and Economics, which are used as proxy variables. The third means involves the use of linear regression (the gradient descent method) in machine learning regression to calculate the importance of AI to the increase in employment size. The machine learning model has a higher goodness of fit and fitting effect on the predicted data, and its mean square error and mean absolute error are more minor (Wang Y et al. 2022 ).

As seen from the robustness part of Table 3 , the results of Method 1 show that AI exerts a positive impact on the employment share in the manufacturing industry; that is, AI can increase the proportion of employment in the manufacturing industry, the use of AI creates more derivative jobs for the manufacturing industry, and the demand for the labour force of enterprises further increases. The results of method 2 show that after increasing the number of control variables, the influence of robots on employment remains significantly positive, indicating no social phenomenon of “machine replacement.” The results of method 3 show that the weight of AI is 84.3%, indicating that AI can explain most of the increase in the manufacturing employment scale and has a positive promoting effect. The above three methods confirm the robustness of the baseline regression results.

Endogenous problem

Although further control variables are used to alleviate the endogeneity problem caused by missing variables to the greatest extent possible, the bidirectional causal relationship between labour demand and robot installation (for example, enterprises tend to passively adopt the machine replacement strategy in the case of labour shortages and recruitment difficulties) still threatens the accuracy of the statistical inference results in this paper. To eliminate the potential endogeneity problem of the model, the two-stage least squares method (2SLS) was applied. In general, the cost factor that enterprises need to consider when introducing industrial robots is not only the comparative advantage between the efficiency cost of machinery and the costs of equipment and labour wages but also the cost of electricity to maintain the efficient operation of machinery and equipment. Changes in industrial electricity prices indicate that the dynamic conditions between installing robots and hiring workers have changed, and decision-makers need to reweigh the costs and profits of intelligent transformation. Changes in industrial electricity prices can impact the demand for labour by enterprises; this path does not directly affect the labour market but is rather based on the power consumption, work efficiency, and equipment prices of robots. Therefore, industrial electricity prices are exogenous relative to employment, and the demand for robots is correlated.

Electricity production and operation can be divided into power generation, transmission, distribution, and sales. China has realized the integration of exports and distribution, so there are two critical prices in practice: on-grid and sales tariffs (Yu and Liu 2017 ). The government determines the on-grid tariff according to different cost-plus models, and its regulatory policy has roughly proceeded from that of principal and interest repayment, through operating period pricing, to benchmark pricing. The sales price (also known as the catalogue price) is the price of electric energy sold by power grid operators to end users, and its price structure is formed based on the “electric heating price” that was implemented in 1976. There is differentiated pricing between industrial and agricultural electricity. Generally, government departments formulate on-grid tariffs, integrating the interests of power plants, grid enterprises, and end users. As China’s thermal power installed capacity accounts for more than 70% of the installed capacity of generators, the price of coal becomes an essential factor affecting the price of industrial internet access. The pricing strategy for electricity sales is not determined by market-oriented transmission and distribution electricity price, on-grid electricity price, or tax but rather by the goal of “stable growth and ensuring people’s livelihood” (Tang and Yang 2014 ). The externality of the feed-in price is more robust, so the paper chooses the feed-in price as an instrumental variable.

It can be seen from Table 3 that the instrumental variables in the first stage positively affect the robot installation density at the level of 1%. Meanwhile, the results of the validity test of the instrumental variables show that there are no weak instrumental variables or unidentifiable problems with this variable, thus satisfying the principle of correlation and exclusivity. The second-stage results show that robots still positively affect the demand for labour at the 1% level, but the fitting coefficient is smaller than that of the benchmark regression model. In summary, the results of fitting the calculation with the causal inference paradigm still support the conclusion that robots create more jobs and increase the labour demand of enterprises.

Extensibility analysis

Robot adoption and gender bias.

The quantity and quality of labour needed by various industries in the manufacturing sector vary greatly, and labour-intensive and capital-intensive industries have different labour needs. Over the past few decades, the demand for female employees has grown. Female employees obtain more job opportunities and better salaries today (Zhang et al. 2023 ). Female employees may benefit from reducing the content of manual labour jobs, meaning that further study of AI heterogeneity from the perspective of gender bias may be needed. As seen from Table 4 , AI has a significant positive impact on the employment of both male and female practitioners, indicating that AI technology does not have a heterogeneous effect on the dynamic gender structure. By comparing the coefficients of the two (the estimated results for men and those for women), it can be found that robots have a more significant promotion effect on female employees. AI has significantly improved the working environment of front-line workers, reduced the level of labour intensity, enabled people to free themselves of dirty and heavy work tasks, and indirectly improved the job adaptability of female workers. Intellectualization increases the flexibility of the time, place, and manner of work for workers, correspondingly improves the working freedom of female workers, and alleviates the imbalance in the choice between family and career for women to a certain extent (Lu et al. 2023 ). At the same time, women are born with the comparative advantage of cognitive skills that allow them to pay more nuanced attention to work details. By introducing automated technology, companies are increasing the demand for cognitive skills such as mental labour and sentiment analysis, thus increasing the benefits for female workers (Wang and Zhang 2022 ). Flexible employment forms, such as online car hailing, community e-commerce, and online live broadcasting, provide a broader stage for women’s entrepreneurship and employment. According to the “Didi Digital Platform and Female Ecology Research Report”, the number of newly registered female online taxi drivers in China has exceeded 265,000 since 2020, and approximately 60 percent of the heads of the e-commerce platform, Orange Heart, are women.

Industry heterogeneity

Given the significant differences in the combination of factors across the different industries in China’s manufacturing sector, there is also a significant gap in the installation density of robots; even compared to AI density, in industries with different production characteristics, indicating that there may be an opposite employment phenomenon at play. According to the number of employees and their salary level, capital stock, R&D investment, and patent technology, the manufacturing industry is divided into labour-intensive (LI), capital-intensive (CI), and technology-intensive (TI) industries.

As seen from the industry-specific test results displayed in Table 4 , the impact of AI on employment in the three attribute industries is significantly positive, which is consistent with the results of Beier et al. ( 2022 ). In contrast, labour-intensive industries can absorb more workers, and industry practitioners are better able to share digital dividends from these new workers, which is generally in line with expectations (in the labour-intensive case, the regression coefficient of AI on employment is 0.054, which is significantly larger than the regression coefficient of the other two industries). This conclusion shows that enterprises use AI to replace the labour force of procedural and process-based positions in pursuit of cost-effective performance. However, the scale effect generated by improving enterprise production efficiency leads to increased labour demand, namely, productivity and compensation effects. For example, AGV-handling robots are used to replace porters in monotonous and repetitive high-intensity work, thus realizing the uncrewed operation of storage links and the automatic handling of goods, semifinished products, and raw materials in the production process. This reduces the cost of goods storage while improving the efficiency of logistics handling, increasing the capital investment of enterprises in the expansion of market share and extension of the industrial chain.

Mechanism test

To reveal the path mechanism through which AI affects employment, in combination with H2 and H3 and the intermediary effect model constructed with Eq. ( 3 ), the TWFE model was used to fit the results shown in Table 5 .

It can be seen from Table 5 that the fitting coefficients of AI for capital deepening, labour productivity, and division of labour are 0.052, 0.071, and 0.302, respectively, and are all significant at the 1% level, indicating that AI can promote employment through the above three mechanisms, and thus research Hypothesis 2 (H2) is supported. Compared with the workshop and handicraft industry, machine production has driven incomparably broad development in the social division of labour. Intelligent transformation helps to open up the internal and external data chain, improve the combination of production factors, reduce costs and increase efficiency to enable the high-quality development of enterprises. At the macro level, the impact of robotics on social productivity, industrial structure, and product prices affects the labour demand of enterprises. At the micro level, robot technology changes the employment carrier, skill requirements, and employment form of labour and impacts the matching of labour supply and demand. The combination of the price and income effects can drive the impact of technological progress on employment creation. While improving labour productivity, AI technology reduces product production costs. In the case of constant nominal income, the market increases the demand for the product, which in turn drives the expansion of the industrial scale and increases output, resulting in an increase in the demand for labour. At the same time, the emergence of robotics has refined the division of labour. Most importantly, the development of AI technology results in productivity improvements that cannot be matched by pure labour input, which not only enables 24 h automation but also reduces error rates, improves precision, and accelerates production speeds.

Table 5 also shows that the fitting coefficient of AI to virtual agglomeration is 0.141 and significant at the 5% level, indicating that AI and digital technology can promote employment by promoting the agglomeration degree of enterprises in the cloud and network. Research Hypothesis 3 is thus supported. Industrial internet, AI, collaborative robots, and optical fidelity information transmission technology are necessary for the future of the manufacturing industry, and smart factories will become the ultimate direction of manufacturing. Under the intelligent manufacturing model, by leveraging cloud links, industrial robots, and the technological depth needed to achieve autonomous management, the proximity advantage of geographic spatial agglomeration gradually begins to fade. The panconnective features of digital technology break through the situational constraints of work, reshaping the static, linear, and demarcated organizational structure and management modes of the industrial era and increasingly facilitates dynamic, network-based, borderless organizational forms, despite the fact that traditional work tasks can be carried out on a broader network platform employing online office platforms and online meetings. While promoting cost reduction and efficiency increase, such connectivity also creates new occupations that rely on this network to achieve efficient virtual agglomeration. On the other hand, robot technology has also broken the fixed connection between people and jobs, and the previous post matching mode of one person and one specific individual has gradually evolved into an organizational structure involving multiple posts and multiple people, thus providing more diverse and inclusive jobs for different groups.

Conclusions and policy implications

Research conclusion.

The decisive impact of digitization and automation on the functioning of all society’s social subsystems is indisputable. Technological progress alone does not impart any purpose to technology, and its value (consciousness) can only be defined by its application in the social context in which it emerges (Rakowski et al. 2021 ). The recent launch of the intelligent chatbot ChatGPT by the US artificial intelligence company OpenAI, with its powerful word processing capabilities and human-computer interaction, has once again sparked global concerns about its potential impact on employment in related industries. Automation technology represented by intelligent manufacturing profoundly affects the labour supply and demand map and significantly impacts economic and social development. The application of industrial robots is a concrete reflection of the integration of AI technology and industry, and its widespread promotion and popularization in the manufacturing field have resulted in changes in production methods and exerted impacts on the labour market. In this paper, the internal mechanism of AI’s impact on employment is first delineated and then empirical tests based on panel data from 30 provinces (municipalities and autonomous regions, excluding Hong Kong, Macao, Taiwan, and Xizang) in China from 2006 to 2020 are subsequently conducted. As mentioned in relation to the theory of “employment compensation,” the research described in this paper shows that the overall impact of AI on employment is positive, revealing a pronounced job creation effect, and the impact of automation technology on the labour market is mainly positively manifested as “icing on the cake.” Our conclusion is consistent with the literature (Sharma and Mishra 2023 ; Feng et al. 2024 ). This conclusion remains after replacing variables, adding missing variables, and controlling for endogeneity problems. The positive role of AI in promoting employment does not have exert opposite effects resulting from gender and industry differences. However, it brings greater digital welfare to female practitioners and workers in labour-intensive industries while relatively reducing the overall proportion of male practitioners in the manufacturing industry. Mechanism analysis shows that AI drives employment through mechanisms that promote capital deepening, the division of labour, and increased labour productivity. The digital trade derived from digital technology and internet platforms has promoted the transformation of traditional industrial agglomeration into virtual agglomeration, the constructed network flow space system is more prone to the free spillover of knowledge, technology, and creativity, and the agglomeration effect and agglomeration mechanism are amplified by geometric multiples. Industrial virtual agglomeration has become a new mechanism and an essential channel through which AI promotes employment, which helps to enhance labour autonomy, improve job suitability and encourage enterprises to share the welfare of labour among “cultivation areas.”

Policy implications

Technology is neutral, and its key lies in its use. Artificial intelligence technology, as an open new general technology, represents significant progress in productivity and is an essential driving force with the potential to boost economic development. However, it also inevitably poses many potential risks and social problems. This study helps to clarify the argument that technology replaces jobs by revealing the impact of automation technology on China’s labour market at the present stage, and its findings alleviate the social anxiety caused by the fear of machine replacement. According to the above research conclusions, the following valuable implications can be obtained.

Investment in AI research and development should be increased, and the high-end development of domestic robots should be accelerated. The development of AI has not only resulted in the improvement of production efficiency but has also triggered a change in industrial structure and labour structure, and it has also generated new jobs as it has replaced human labour. Currently, the impact of AI on employment in China is positive and helps to stabilize employment. Speeding up the development of the information infrastructure, accelerating the intelligent upgrade of the traditional physical infrastructure, and realizing the inclusive promotion of intelligent infrastructure are necessary to ensure efficient development. 5G technology and the development dividend of the digital economy can be used to increase the level of investment in new infrastructure such as cloud computing, the Internet of Things, blockchain, and the industrial internet and to improve the level of intelligent application across the industry. We need to implement the intelligent transformation of old infrastructure, upgrade traditional old infrastructure to smart new infrastructure, and digitally transform traditional forms of infrastructure such as power, reservoirs, rivers, and urban sewer pipes through the employment of sensors and access algorithms to solve infrastructure problems more intelligently. Second, the diversification and agglomeration of industrial lines are facilitated through the transformation of industrial intelligence and automation. At the same time, it is necessary to speed up the process of industrial intelligence and cultivate the prospects of emerging industries and employment carriers, particularly in regard to the development and growth of emerging producer services. The development of domestic robots should be task-oriented and application-oriented, should adhere to the effective transformation of scientific and technological achievements under the guidance of the development of the service economy. A “1 + 2 + N” collaborative innovation ecosystem should be constructed with a focus on cultivating, incubating, and supporting critical technological innovation in each subindustry of the manufacturing industry, optimizing the layout, and forming a matrix multilevel achievement transformation service. We need to improve the mechanisms used for complementing research and production, such as technology investment and authorization. To move beyond standard robot system development technology, the research and development of bionic perception and knowledge, as well as other cutting-edge technologies need to be developed to overcome the core technology “bottleneck” problem.

It is suggested that government departments improve the social security system and stabilize employment through multiple channels. The first channel is the evaluation and monitoring of the potential destruction of the low-end labour force by AI, enabled through the cooperation of the government and enterprises, to build relevant information platforms, improve the transparency of the labour market information, and reasonably anticipate structural unemployment. Big data should be fully leveraged, a sound national employment information monitoring platform should be built, real-time monitoring of the dynamic changes in employment in critical regions, fundamental groups, and key positions should be implemented, employment status information should be released, and employment early warning, forecasting, and prediction should be provided. Second, the backstop role of public service, including human resources departments and social security departments at all levels, should improve the relevant social security system in a timely manner. A mixed-guarantee model can be adopted for the potential unemployed and laws and regulations to protect the legitimate rights and interests of entrepreneurs and temporary employees should be improved. We can gradually expand the coverage of unemployment insurance and basic living allowances. For the extremely poor, unemployed or extreme labour shortage groups, public welfare jobs or special subsidies can be used to stabilize their basic lifestyles. The second is to understand the working conditions of the bottom workers at the grassroots level in greater depth, strengthen the statistical investigation and professional evaluation of AI technology and related jobs, provide skills training, employment assistance, and unemployment subsidies for workers who are unemployed due to the use of AI, and encourage unemployed groups to participate in vocational skills training to improve their applicable skillsets. Workers should be encouraged to use their fragmented time to participate in the gig and sharing economies and achieve flexible employment according to dominant conditions. Finally, a focus should be established on the impact of AI on the changing demand for jobs in specific industries, especially transportation equipment manufacturing and communications equipment, computers, and other electronic equipment manufacturing.

It is suggested that education departments promote the reform of the education and training system and deepen the coordinated development of industry-university research. Big data, the Internet of Things, and AI, as new digital production factors, have penetrated daily economic activities, driving industrial changes and changes in the supply and demand dynamics of the job market. Heterogeneity analysis results confirmed that AI imparts a high level of digital welfare for women and workers in labour-intensive industrial enterprises, but to stimulate the spillover of technology dividends in the whole society, it is necessary to dynamically optimize human capital and improve the adaptability of man-machine collaborative work; otherwise, the disruptive effect of intelligent technology on low-end, routine and programmable work will be obscured. AI has a creativity promoting effect on irregular, creative, and stylized technical positions. Hence, the contradiction between supply and demand in the labour market and the slow transformation of the labour skill structure requires attention. The relevant administrative departments of the state should take the lead in increasing investment in basic research and forming a scientific research division system in which enterprises increase their levels of investment in experimental development and multiple subjects participate in R&D. Relevant departments should clarify the urgent need for talent in the digital economy era, deepen the reform of the education system as a guide, encourage all kinds of colleges and universities to add related majors around AI and big data analysis, accelerate the research on the skill needs of new careers and jobs, and establish a lifelong learning and employment training system that meets the needs of the innovative economy and intelligent society. We need to strengthen the training of innovative, technical, and professional technical personnel, focus on cultivating interdisciplinary talent and AI-related professionals to improve worker adaptability to new industries and technologies, deepen the adjustment of the educational structure, increase the skills and knowledge of perceptual, creative, and social abilities of the workforce, and cultivate the skills needed to perform complex jobs in the future that are difficult to replace by AI. The lifelong education and training system should be improved, and enterprise employees should be encouraged to participate in vocational skills training and cultural knowledge learning through activities such as vocational and technical schools, enterprise universities, and personnel exchanges.

Research limitations

The study used panel data from 30 provinces in China from 2006 to 2020 to examine the impact of AI on employment using econometric models. Therefore, the conclusions obtained in this study are only applicable to the economic reality in China during the sample period. There are three shortcomings in this study. First, only the effect and mechanism of AI in promoting employment from a macro level are investigated in this study, which is limited by the large data particles and small sample data that are factors that reduce the reliability and validity of statistical inference. The digital economy has grown rapidly in the wake of the COVID-19 pandemic, and the related industrial structures and job types have been affected by sudden public events. An examination of the impact of AI on employment based on nearly three years of micro-data (particularly the data obtained from field research) is urgent. When conducting empirical analysis, combining case studies of enterprises that are undergoing digital transformation is very helpful. Second, although the two-way fixed effect model and instrumental variable method can reveal conclusions regarding causality to a certain extent, these conclusions are not causal inference in the strict sense. Due to the lack of good policy pilots regarding industrial robots and digital parks, the topic cannot be thoroughly evaluated for determining policy and calculating resident welfare. In future research, researchers can look for policies and systems such as big data pilot zones, intelligent industrial parks, and digital economy demonstration zones to perform policy evaluations through quasinatural experiments. The use of difference in differences (DID), regression discontinuity (RD), and synthetic control method (SCM) to perform regression is beneficial. In addition, the diffusion effect caused by introducing and installing industrial robots leads to the flow of labour between regions, resulting in a potential spatial spillover effect. Although the spatial econometric model is used above, it is mainly used as a robustness test, and the direct effect is considered. This paper has yet to discuss the spatial effect from the perspective of the spatial spillover effect. Last, it is important to note that the digital infrastructure, workforce, and industrial structure differ from country to country. The study focused on a sample of data from China, making the findings only partially applicable to other countries. Therefore, the sample size of countries should be expanded in future studies, and the possible heterogeneity of AI should be explored and compared by classifying different countries according to their stage of development.

Data availability

The data generated during and/or analyzed during the current study are provided in Supplementary File “database”.

Acemoglu D, Restrepo P (2018) Low-Skill and High-Skill Automation. J Hum Cap 12(2):204–232. https://doi.org/10.1086/697242

Article   Google Scholar  

Alan H (2023) A systematic bibliometric analysis on the current digital human resources management studies and directions for future research. J Chin Hum Resour Manag 14(1):38–59. https://doi.org/10.47297/wspchrmWSP2040-800502.20231401

Autor D (2019) Work of the past, work of the future. AEA Pap Proc 109(4):1–32. https://doi.org/10.1257/pandp.20191110

Balsmeier B, Woerter M (2019) Is this time different? How digitalization influences job creation and destruction. Res Policy 48(8):103765. https://doi.org/10.1016/j.respol.2019.03.010

Beier G, Matthess M, Shuttleworth L, Guan T, Grudzien DIDP, Xue B et al. (2022) Implications of Industry 4.0 on industrial employment: A comparative survey from Brazilian, Chinese, and German practitioners. Technol Soc 70:102028. https://doi.org/10.1016/j.techsoc.2022.102028

Berkers H, Smids J, Nyholm SR, Le Blanc PM (2020) Robotization and meaningful work in logistic warehouses: threats and opportunities. Gedrag Organisatie 33(4):324–347

Google Scholar  

Borland J, Coelli M (2017) Are robots taking our jobs? Aust Economic Rev 50(4):377–397. https://doi.org/10.1111/1467-8462.12245

Bouattour A, Kalai M, Helali K (2023) The nonlinear impact of technologies import on industrial employment: A panel threshold regression approach. Heliyon 9(10):e20266. https://doi.org/10.1016/j.heliyon.2023.e20266

Article   PubMed   PubMed Central   Google Scholar  

Boyd R, Holton RJ (2018) Technology, innovation, employment and power: Does robotics and artificial intelligence really mean social transformation? J Sociol 54(3):331–345. https://doi.org/10.1177/1440783317726591

Chen Z (2023) Ethics and discrimination in artificial intelligence-enabled recruitment practices. Humanities Soc Sci Commun 10:567. https://doi.org/10.1057/s41599-023-02079-x

Dixon J, Hong B, Wu L (2021) The robot revolution: Managerial and employment consequences for firms. Manag Sci 67(9):5586–5605. https://doi.org/10.1287/mnsc.2020.3812

Duan SX, Deng H, Wibowo S (2023) Exploring the impact of digital work on work-life balance and job performance: a technology affordance perspective. Inf Technol People 36(5):2009–2029. https://doi.org/10.1108/ITP-01-2021-0013

Duan X, Zhang Q (2023) Industrial digitization, virtual agglomeration and total factor productivity. J Northwest Norm Univ(Soc Sci) 60(1):135–144. https://doi.org/10.16783/j.cnki.nwnus.2023.01.016

Dunn M (2020) Making gigs work: digital platforms, job quality and worker motivations. N. Technol Work Employ 35(2):232–249. https://doi.org/10.1111/ntwe.12167

Fabo B, Karanovic J, Dukova K (2017) In search of an adequate European policy response to the platform economy. Transf: Eur Rev Labour Res 23(2):163–175. https://doi.org/10.1177/1024258916688861

Feng R, Shen C, Guo Y (2024) Digital finance and labor demand of manufacturing enterprises: Theoretical mechanism and heterogeneity analysis. Int Rev Econ Financ 89(Part A):17–32. https://doi.org/10.1016/j.iref.2023.07.065

Filippi E, Bannò M, Trento S (2023) Automation technologies and their impact on employment: A review, synthesis and future research agenda. Technol Forecast Soc Change 191:122448. https://doi.org/10.1016/j.techfore.2023.122448

Fokam DNDT, Kamga BF, Nchofoung TN (2023) Information and communication technologies and employment in developing countries: Effects and transmission channels. Telecommun Policy 47(8):102597. https://doi.org/10.1016/j.telpol.2023.102597

Forsythe E, Kahn LB, Lange F, Wiczer D (2022) Where have all the workers gone? Recalls, retirements, and reallocation in the COVID recovery. Labour Econ 78:102251. https://doi.org/10.1016/j.labeco.2022.102251

Fossen FM, Sorgner A (2022) New digital technologies and heterogeneous wage and employment dynamics in the United States: Evidence from individual-level data. Technol Forecast Soc Change 175:121381. https://doi.org/10.1016/j.techfore.2021.121381

Frey CB, Osborne MA (2017) The future of employment: How susceptible are jobs to computerisation? Technol Forecast Soc Change 114:254–280. https://doi.org/10.1016/j.techfore.2016.08.019

Gardberg M, Heyman F, Norbäck P, Persson L (2020) Digitization-based automation and occupational dynamics. Econ Lett 189:109032. https://doi.org/10.1016/j.econlet.2020.109032

Ge P, Zhao Z (2023) The rise of robots and employment change: 2009–2017. J Renmin Univ China 37(1):102–115

Graf H, Mohamed H (2024) Robotization and employment dynamics in German manufacturing value chains. Struct Change Economic Dyn 68:133–147. https://doi.org/10.1016/j.strueco.2023.10.014

Han J, Yan X, Wei N (2022) Study on regional differences of the impact of artificial intelligence on China’s employment skill structure. Northwest Popul J 43(3):45–57. https://doi.org/10.15884/j.cnki.issn.1007-0672.2022.03.004

Article   CAS   Google Scholar  

Huang M, Rust RT (2018) Artificial intelligence in service. J Serv Res 21(2):155–172. https://doi.org/10.1177/1094670517752459

Jiang T (2022) Mediating effects and moderating effects in causal inference. China Ind Econ 410(5):100–120. https://doi.org/10.19581/j.cnki.ciejournal.2022.05.005

Article   MathSciNet   Google Scholar  

Jin X, Ma B, Zhang H (2023) Impact of fast internet access on employment: Evidence from a broadband expansion in China. China Econ Rev 81:102038. https://doi.org/10.1016/j.chieco.2023.102038

Jetha A, Bonaccio S, Shamaee A, Banks CG, Bültmann U, Smith PM et al. (2023) Divided in a digital economy: Understanding disability employment inequities stemming from the application of advanced workplace technologies. SSM - Qual Res Health 3:100293. https://doi.org/10.1016/j.ssmqr.2023.100293

Josifidis K, Supic N (2018) Income polarization of the US working class: An institutionalist view. J Econ Issues 52(2):498–508. https://doi.org/10.1080/00213624.2018.1469929

Kirov V, Malamin B (2022) Are translators afraid of artificial intelligence? Societies 12(2):70. https://doi.org/10.3390/soc12020070

Kolade O, Owoseni A (2022) Employment 5.0: The work of the future and the future of work. Technol Soc 71:102086. https://doi.org/10.1016/j.techsoc.2022.102086

Li L, Mo Y, Zhou G (2022) Platform economy and China’ s labor market: structural transformation and policy challenges. China Econ J 15(2):139–152. https://doi.org/10.1080/17538963.2022.2067685

Li Q, Zhang R (2022) Study on the challenges and countermeasures of coordinated development of quantity and quality of employment under the new technology-economy paradigm. J Xiangtan Univ(Philos Soc Sci) 46(5):42–45+58. https://doi.org/10.13715/j.cnki.jxupss.2022.05.019

Li Z, Hong Y, Zhang Z (2021) The empowering and competition effects of the platform-based sharing economy on the supply and demand sides of the labor market. J Manag Inf Syst 38(1):140–165. https://doi.org/10.1080/07421222.2021.1870387

Liu L (2018) Occupational therapy in the fourth industrial revolution. Can J Occup Ther 85(4):272–283. https://doi.org/10.1177/0008417418815179

Article   ADS   Google Scholar  

Liu N, Gu X, Lei CK (2022) The equilibrium effects of digital technology on banking, production, and employment. Financ Res Lett 49:103196. https://doi.org/10.1016/j.frl.2022.103196

Liu Y, Peng J (2023) The impact of “AI unemployment” on contemporary youth and its countermeasures. Youth Exploration 241(1):43–51. https://doi.org/10.13583/j.cnki.issn1004-3780.2023.01.004

Lu J, Xiao Q, Wang T (2023) Does the digital economy generate a gender dividend for female employment? Evidence from China. Telecommun Policy 47(6):102545. https://doi.org/10.1016/j.telpol.2023.102545

Luo J, Zhuo W, Xu B (2023). The bigger, the better? Optimal NGO size of human resources and governance quality of entrepreneurship in circular economy. Management Decision ahead-of-print. https://doi.org/10.1108/MD-03-2023-0325

Männasoo K, Pareliussen JK, Saia A (2023) Digital capacity and employment outcomes: Microdata evidence from pre- and post-COVID-19 Europe. Telemat Inform 83:102024. https://doi.org/10.1016/j.tele.2023.102024

Michau JB (2013) Creative destruction with on-the-job search. Rev Econ Dyn 16(4):691–707. https://doi.org/10.1016/j.red.2012.10.011

Morgan J (2019) Will we work in twenty-first century capitalism? A critique of the fourth industrial revolution literature. Econ Soc 48(3):371–398. https://doi.org/10.1080/03085147.2019.1620027

Nam T (2019) Technology usage, expected job sustainability, and perceived job insecurity. Technol Forecast Soc Change 138:155–165. https://doi.org/10.1016/j.techfore.2018.08.017

Ndubuisi G, Otioma C, Tetteh GK (2021) Digital infrastructure and employment in services: Evidence from Sub-Saharan African countries. Telecommun Policy 45(8):102153. https://doi.org/10.1016/j.telpol.2021.102153

Ni B, Obashi A (2021) Robotics technology and firm-level employment adjustment in Japan. Jpn World Econ 57:101054. https://doi.org/10.1016/j.japwor.2021.101054

Nikitas A, Vitel AE, Cotet C (2021) Autonomous vehicles and employment: An urban futures revolution or catastrophe? Cities 114:103203. https://doi.org/10.1016/j.cities.2021.103203

Novella R, Rosas-Shady D, Alvarado A (2023) Are we nearly there yet? New technology adoption and labor demand in Peru. Sci Public Policy 50(4):565–578. https://doi.org/10.1093/scipol/scad007

Oschinski A, Wyonch R (2017). Future shock?: the impact of automation on Canada’s labour market.C.D. Howe Institute Commentary working paper

Polak P (2021) Welcome to the digital era—the impact of AI on business and society. Society 58:177–178. https://doi.org/10.1007/s12115-021-00588-6

Rakowski R, Polak P, Kowalikova P (2021) Ethical aspects of the impact of AI: the status of humans in the era of artificial intelligence. Society 58:196–203. https://doi.org/10.1007/s12115-021-00586-8

Ramos ME, Garza-Rodríguez J, Gibaja-Romero DE (2022) Automation of employment in the presence of industry 4.0: The case of Mexico. Technol Soc 68:101837. https://doi.org/10.1016/j.techsoc.2021.101837

Reljic J, Evangelista R, Pianta M (2021). Digital technologies, employment, and skills. Industrial and Corporate Change dtab059. https://doi.org/10.1093/icc/dtab059

Schultz DE (1998) The death of distance—How the communications revolution will change our lives. Int Mark Rev 15(4):309–311. https://doi.org/10.1108/imr.1998.15.4.309.1

Sharma C, Mishra RK (2023) Imports, technology, and employment: Job creation or creative destruction. Manag Decis Econ 44(1):152–170. https://doi.org/10.1002/mde.3671

Shen Y, Yang Z (2023) Chasing green: The synergistic effect of industrial intelligence on pollution control and carbon reduction and its mechanisms. Sustainability 15(8):6401. https://doi.org/10.3390/su15086401

Spencer DA (2023) Technology and work: Past lessons and future directions. Technol Soc 74:102294. https://doi.org/10.1016/j.techsoc.2023.102294

Sun W, Liu Y (2023) Research on the influence mechanism of artificial intelligence on labor market. East China Econ Manag 37(3):1–9. https://doi.org/10.19629/j.cnki.34-1014/f.220706008

Tan H, Xia C (2022) Digital trade reshapes the theory and model of industrial agglomeration — From geographic agglomeration to online agglomeration. Res Financial Econ Issues 443(6):43–52. https://doi.org/10.19654/j.cnki.cjwtyj.2022.06.004

Tang J, Yang J (2014) Research on the economic impact of the hidden subsidy of sales price and reform. China Ind Econ 321(12):5–17. https://doi.org/10.19581/j.cnki.ciejournal.2014.12.001

Tschang FT, Almirall E (2021) Artificial intelligence as augmenting automation: Implications for employment. Acad Manag Perspect 35(4):642–659. https://doi.org/10.5465/amp.2019.0062

Wang PX, Kim S, Kim M (2023) Robot anthropomorphism and job insecurity: The role of social comparison. J Bus Res 164:114003. https://doi.org/10.1016/j.jbusres.2023.114003

Wang L, Hu S, Dong Z (2022) Artificial intelligence technology, Task attribute and occupational substitutable risk: Empirical evidence from the micro-level. J Manag World 38(7):60–79. https://doi.org/10.19744/j.cnki.11-1235/f.2022.0094

Wang R, Liang Q, Li G (2018) Virtual agglomeration: a new form of spatial organization with the deep integration of new generation information technology and real economy. J Manag World 34(2):13–21. https://doi.org/10.19744/j.cnki.11-1235/f.2018.02.002

Wang X, Zhu X, Wang Y (2022) TheImpactofRobotApplicationonManufacturingEmployment. J Quant Technol Econ 39(4):88–106. https://doi.org/10.13653/j.cnki.jqte.2022.04.002

Wang Y, Zhang Y (2022) Dual employment effect of digital economy and higher quality employment development. Expanding Horiz 231(3):43–50

Wang Y, Zhang Y, Liu J (2022) Digital finance and carbon emissions: an empirical test based on micro data and machine learning model. China Popul,Resour Environ 32(6):1–11

Wen J, Liu Y (2021) Uncertainty of new employment form: Digital labor in platform capital space and the reflection on it. J Zhejiang Gongshang Univ 171(6):92–106. https://doi.org/10.14134/j.cnki.cn33-1337/c.2021.06.009

Wong SI, Fieseler C, Kost D (2020) Digital labourers’ proactivity and the venture for meaningful work: Fruitful or fruitless? J-of-Occup-and-Organ-Psychol 93(4):887–911. https://doi.org/10.1111/joop.12317

Wu B, Yang W (2022) Empirical test of the impact of the digital economy on China’s employment structure. Financ Res Lett 49:103047. https://doi.org/10.1016/j.frl.2022.103047

Wu Q (2023) Sustainable growth through industrial robot diffusion: Quasi-experimental evidence from a Bartik shift-share design. Economics of Transition and Institutional Change Early Access https://doi.org/10.1111/ecot.12367

Xie M, Dong L, Xia Y, Guo J, Pan J, Wang H (2022) Does artificial intelligence affect the pattern of skill demand? Evidence from Chinese manufacturing firms. Econ Model 96:295–309. https://doi.org/10.1016/j.econmod.2021.01.009

Yan X, Zhu K, Ma C (2020) Employment under robot Impact: Evidence from China manufacturing. Stat Res 37(1):74–87. https://doi.org/10.19343/j.cnki.11-1302/c.2020.01.006

Yang CH (2022) How artificial intelligence technology affects productivity and employment: Firm-level evidence from Taiwan. Res Policy 51(6):104536. https://doi.org/10.1016/j.respol.2022.104536

Yang Z, Shen Y (2023) The impact of intelligent manufacturing on industrial green total factor productivity and its multiple mechanisms. Front Environ Sci 10:1058664. https://doi.org/10.3389/fenvs.2022.1058664

Yoon C (2023) Technology adoption and jobs: The effects of self-service kiosks in restaurants on labor outcomes. Technol Soc 74:102336. https://doi.org/10.1016/j.techsoc.2023.102336

Yu L, Liu Y (2017) Consumers’ welfare in China’s electric power industry competition. Res Econ Manag 38(8):55–64. https://doi.org/10.13502/j.cnki.issn1000-7636.2017.08.006

Zhang Q, Zhang F, Mai Q (2023) Robot adoption and labor demand: A new interpretation from external competition. Technol Soc 74:102310. https://doi.org/10.1016/j.techsoc.2023.102310

Zhang Y, Li X (2022) The new digital infrastructure, gig employment and spatial spillover effect. China Bus Mark 36(11):103–117. https://doi.org/10.14089/j.cnki.cn11-3664/f.2022.11.010

Article   MathSciNet   CAS   Google Scholar  

Zhang Z (2023a) The impact of the artificial intelligence industry on the number and structure of employments in the digital economy environment. Technol Forecast Soc Change 197:122881. https://doi.org/10.1016/j.techfore.2023.122881

Zhao L, Zhao X (2017) Is AI endangering human job opportunities?—From a perspective of marxism. J Hebei Univ Econ Bus 38(6):17–22. https://doi.org/10.14178/j.cnki.issn1007-2101.2017.06.004

Zhou S, Chen B (2022) Robots and industrial employment: Based on the perspective of subtask model. Stat Decis 38(23):85–89. https://doi.org/10.13546/j.cnki.tjyjc.2022.23.016

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This work was financially supported by the Natural Science Foundation of Fujian Province (Grant No. 2022J01320).

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Shen, Y., Zhang, X. The impact of artificial intelligence on employment: the role of virtual agglomeration. Humanit Soc Sci Commun 11 , 122 (2024). https://doi.org/10.1057/s41599-024-02647-9

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How Will Artificial Intelligence Affect Jobs 2024-2030

You would have been living under a rock if you did not know how artificial intelligence is set to affect jobs in 2024-2030. AI like ChatGPT seems to be stealing all of the headlines at the moment, Google unveiled new AI software to build presentations, analyze and enter data, and write content, and there are so many more AI tools like Gamma and Numerous AI.

Those that are resisting, rather than riding the crest of the wave will not be making hey whilst the sun shines when it comes to landing in-demand jobs in the next 6 years and enjoying job growth. AI will be taking some jobs, but it will be creating new ones!  

Here are the most likely jobs that artificial intelligence will affect from 2024-2030:

How artificial intelligence will change the world

Will ai help the world or hurt it.

Like any controversial subject, there will always be people who are for it, and those that are against it. Artificial Intelligence is no different. In fact, as new ai tools are introduced, and the news around them grows, so the division between the two camps will grow with it. Many market research analysts say that AI has the potential to bring about numerous positive changes in society, including enhanced productivity, improved healthcare, and increased access to education. But we need to adapt right now.

Others will say, mostly those working in human work types of jobs that are manually repetitive, that ai and robotics is a disruptive force and when it comes to the future of jobs it merely serves to steal jobs. But robots and ai technologies can and will create a great many new vocations and help solve complex problems and make our daily lives easier and more convenient. The jury is not yet out on this, but the leaning is more toward ai being a positive force rather than a negative one.

How will AI affect jobs and the economy?

McKinsey global institute says that at the global average level of adoption and absorption and advances in ai implied by their simulation, AI has the profound impact to deliver additional global economic activity of around $13 trillion in the foreseeable future and by 2030, or about 16% higher cumulative GDP compared with today. This amounts to 1.2% additional GDP growth per year. If delivered, this impact would compare well with that of other general-purpose technologies through history. This will mainly come from substitution of labor by automation and increased innovation in products and services.

The same report went on to say that By 2030, the average simulation shows that some 70% of companies will have embraced the ai revolution and adopted at  least one type of AI technology but that less than half will have fully absorbed the five categories. Forbes say ai has the potential to be among the most disruptive technologies across global economies that we will ever develop.

How will artificial intelligence affect society and future?

Forbes says that the future of AI brings endless possibilities and applications that will help simplify our lives to a great extent. It will help shape the future and destiny of humanity positively, whilst Bernard Marr & Co says that the transformative impact of artificial intelligence on our society will have far-reaching economic, legal, political and regulatory implications on all types of jobs and industries that we need to be discussing and preparing for. Others in the know say that AI has the potential to bring about numerous positive changes in society both now and in the future, including enhanced productivity, improved healthcare, and increased access to education. AI-powered technologies can also help solve complex problems and make our daily lives easier and more convenient.

How Will AI Affect Jobs - How many jobs will AI replace by 2030

Artificial intelligence (AI) could replace the equivalent of 300 million full-time jobs, a report by investment bank Goldman Sachs says. It could replace a quarter of work tasks in the US and Europe but may also mean new jobs and a productivity boom. And it could eventually increase the total annual value of goods and services produced globally by 7%. The report also predicts two-thirds of jobs in the U.S. and Europe “are exposed to some degree of AI automation,” and around a quarter of all jobs could be performed by AI entirely.

Researchers from the University of Pennsylvania and OpenAI found some educated white-collar workers earning up to $80,000 a year are the most likely to be affected by workforce automation.

Forbes also says that According to an MIT and Boston University report, AI will replace as many as two million manufacturing workers by 2025.

A study by the  McKinsey Global Institute reports that by 2030, at least 14% of employees globally could need to change their careers due to digitization, robotics, and AI advancements

What jobs are most likely to be automated?

1. customer service representative.

Most human customer service interactions are no longer done by phone with human employees manning the lines. Most of the time, the queries and problems of customers are repetitive. Answering these queries does not require high emotional or social intelligence. Therefore, AI can be used to provide automated responses to frequently asked questions.

2. Receptionists

The majority of companies across the world are now using robots at their reception. Even the calls are being managed by AI now. For example, AimeReception can see, listen, understand, and talk with guests and customers.

3. Accountants/Bookkeepers 

Many companies are now using automation and ai for their bookkeeping practices. AI-powered bookkeeping services provide an efficient accounting system and flexibility and security, considering that they are available as cloud-based services. Using ai algorithms, AI will ensure the data is collected, stored, and analyzed correctly. Using an AI accounting service is significantly less costly than paying an employee’s salary to do the same job.

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4. Salespeople 

Gone are the days when corporations required salespeople for advertising and retail activities. Advertising has shifted towards web and social media landscapes. The built-in target marketing capabilities in social media allow advertisers to create custom content for different types of audiences.

5. Research and analysis

The fields of data analysis and research are areas that already implement the use of artificial intelligence as a method of streamlining the process and identifying new data without human assistance. The processing power of modern computers allows for the efficient sorting, extrapolation and analysis of data. As artificial intelligence continues to improve, there may not be a need for humans to play a role in data analysis and research.

6. Warehouse work

Online sales is a steadily growing industry and comes with an increasing need for processes and automated systems that efficiently get orders onto trucks for delivery. One area of focus for streamlining the process has been the use of automation. Basic automation and artificial implementation in a warehouse allow for easy access to computerized systems to locate packages and direct staff, and future AI may even perform mechanized retrieval and loading to increase shipping capacities.

7. Insurance underwriting

When making assessments on the viability of insurance applicants, the most important work is often in analyzing the data available and applying it within a set of formulas or structures. Automation can easily complete these tasks and is continually adapting to perform more complicated duties, which may reduce how many underwriters a company requires.

Self-checkout stations at stores are an example of automation in the retail sphere and have gained prominence in grocery stores and big-box outlets. When a company makes use of self-checkout areas, it results from a cost-benefit analysis. Although allowing customers to scan their own items can increase the instances of theft, the company saves more money by reducing the need for employees working registers.

How to quickly change career

Experts say that ai and machine learning will help workers by creating more occupations than it replaces. That said, in order to ride the wave and build a new career, you have to have procured the skills necessary to get the job done. If you're exposed to ai and looking to pivot into an AI-focused role, demonstrating your knowledge and experience with AI development can give you an edge.

Why not take a read of our top 10 highest paying AI jobs article here.

To acquire the skills to stand out from other would be candidates you should: ramp up your technical skills, complete online courses, understand the industry, gain work experience, and develop your soft skills. AI will require extensive research and collaboration as it is still an emerging area. Soft skills will help set you apart from other developers who only have technical skills.

Which jobs will not be replaced by ai?

It is widely touted that ai will create more jobs than it replaces. Further to that, many in certain industries will breath a sigh of relief that ai will not threaten their vocation and livelihood. These are some of the jobs that will not involve repetitive tasks and be prone to disruption. This means that ai will not replace those that perform them in the open labor market.

1. Teachers

Teachers often represent a reference point for many of us. Often, our academic decisions are partly based on how inspiring a particular teacher has been with us in the years prior. For all these reasons, it is almost impossible that we will have a fully digital teaching experience in the Future. 

2. Lawyers and judges

These positions have a strong component of negotiation, strategy and case analysis. A lot is based on the personal experience and knowledge of each specialist. It requires a certain set of skills to be able to navigate complex legal systems and argue in defense of a client in court. There is a human factor involved when it comes down to consider all the various aspects of a trial and take a final decision that could turn into years in prison, in the case of a Judge.

3. Directors, Managers and CEOs

Managing teams inside an organization is a matter of Leadership and this is not a stack of behaviors that can be written down in a code and processed in a linear way. A CEO is also the person responsible for sharing the company’s mission and value down to the team. It is very unlikely that investors will ever feel comfortable investing in a company managed by robots or algorithms.

4. HR Managers 

Although ai does assist in the hiring process to make sifting through CVs so much easier and quicker, Human Resource Managers still cover a variety of very important tasks inside an organization. Hiring new professionals is just part of their prerogatives. They also are a key position inside the organization for maintaining the staff motivated, detecting early-on signs of discontent, and manage them if possible. 

5. Psychologists and Psychiatrists 

Although a lot of face recognition technology is currently being used to develop initial AI counseling care and support, given the growing demand, mental health is a very delicate topic. Human touch is essential when it comes down to supporting people to succeed in their lives in all of the aspects that it can entail.

6. Surgeons

For sure, technology has seriously increased the accuracy with whom we are today able to diagnose and detect diseases in any medical report. Micro robotics also enhance the precision of the surgeons when it comes down to operation, enabling less invasive procedures. But being a surgeon requires the ability to connect with the patient on so many other different levels while taking a vast number of the factor under consideration at the same time. Experience, knowledge, and skills acquired throughout the years are all factors that need to be condensed in a matter of minutes during an operation.

7. Computer System Analysts

No matter how automated we become, there will always be the need of a human presence that can run maintenance work, update, improve, correct, and set-up complex software and hardware systems that often require coordination among more than one specialist in order to properly work. Reviewing the system capabilities, controlling the workflow and schedule improvements and increase automation is only part of a Computer System Analyst, a profession that is a great demand in the last years.

8. Artists and writers

Writing especially is such an imaginative fine art, and being able to place a specific selection of words in the right order is definitely a challenging endeavor. So even if AI technically would have the capacity of absorbing the content of most books in the world, in probably any language and come up with a somewhat personal style of communication, the magic and thrill of creating art with words is something that is pretty much going to rest in our domain of competition in the years to come. 

How many jobs will be lost to ai by 2025?

The World Economic Forum has estimated that artificial intelligence will replace some 85 million jobs by 2025. Freethink says that 65% of retail jobs could be automated by that year , saying that this is largely due to technological advancements, rising costs and wages, tight labor markets, and reduced consumer spending. 

How many jobs will be lost to ai by 2030?

PwC estimates that by the mid-2030s, up to 30% of jobs could be automatable, with slightly more men being affected in the long run as autonomous vehicles and other machines replace many manual tasks where their share of employment is higher. During the first and second waves, they estimate that women could be at greater risk of automation due to their higher representation in clerical and other administrative functions​.

How to embrace AI and learn skills to take advantage of this new technology

You may be wondering how you can start familiarizing yourself with AI in your work to help advance your career. LinkedIn says that the good news is that you probably already have experience with AI whether you know it or not. Asking voice assistants like Alexa and Siri questions uses AI, for example. Plenty of the apps on your phone also use AI, too. Generative AI, which is taking up all the headlines lately, is really the next step for this technology.

The company went on to say that to stay ahead in the era of artificial intelligence, it is essential to develop new skills and adapt to the changing job market. Here are some strategies for staying ahead in the era of artificial intelligence:

1. Embrace lifelong learning

In the era of AI, it is important to be constantly learning and adapting to new technologies and ways of working. This means taking courses, attending workshops and conferences, and keeping up-to-date with the latest trends in your industry.

2. Develop soft skills

While AI is great at performing routine tasks, it is still far from replicating human emotional intelligence and creativity. Developing soft skills such as communication, problem-solving, and collaboration will be crucial in the era of AI.

3. Be agile

In the era of AI, the ability to adapt quickly to changing circumstances will be key. This means being willing to learn new skills, take on new responsibilities, and pivot to new career paths.

4. Specialize

As AI becomes more ubiquitous, there will be increasing demand for workers with specialized skills and knowledge. By developing expertise in a particular area, you can increase your value to employers and differentiate yourself in the job market.

Learn from a next-gen university which embraces change

If there is one word that you need to take out of the way to transition from the current job market to the new world order of the job market affected by ai, is the word, 'agility'. The other is 'skills' and skills development at that. 

Besides learning on the job, which can take a long time and effort for all concerned, many of those looking to switch careers or start a new one, are looking to online next-gen universities that can pivot on a penny and offer the programs at a specific period in time to take advantage of the drive to greater numbers of ai related jobs. 

Here at Nexford University, we offer a BBA degree with a specialization in AI .

Doing the degree will mean that learners will learn and develop skills based on the latest employer needs and market trends – this is what the 100% online learning university calls their Workplace Alignment Model which is designed to equip those learners with the skills needed and what employers are looking for.

We also offer a MBA degree with specialization in advanced AI , for those looking for postgraduate education.

Conclusion 

The neigh sayers have seemingly concluded that ai will take millions of jobs and put people out into the street, whilst those that are excited for it and ready to embrace the change are saying that ai has the ability to create more new types of jobs than it replaces. 

That said, it would appear that resistance is futile, and that people must accept that artificial intelligence is becoming a part of our everyday lives. Every job role should embrace it, considering the efficient and cost-effective solutions it brings. It lets people focus on more creative goals by automating the decision-making processes and tedious tasks.

Artificial intelligence offers great promise to drive businesses forward, automate manufacturing processes, and deliver valuable insights. AI is increasingly being used across various industries, including logistics, manufacturing, and cybersecurity. Small businesses have also made rapid progress in creating speech recognition software for mobile devices.

To stay ahead in the era of artificial intelligence, it is essential to embrace lifelong learning, develop soft skills, be agile, and specialize in a particular area. By developing these skills and adapting to the changing job market, workers can thrive in the era of AI and take advantage of the opportunities it presents. Enrolling to do a BBA in Artificial Intelligence or an MBA in artificial intelligence can help people to get ahead and stay ahead in an ever evolving job market. Nexford offers an online BBA program and online MBA program that equip learners with the necessary skills to succeed in the ever competitive ai job market and avoid job loss.

For a more in-depth analysis download our free report .

Mark is a college graduate with Honours in Copywriting. He is the Content Marketing Manager at Nexford, creating engaging, thought-provoking, and action-oriented content.

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Is Artificial Intelligence Helping or Hurting Human Employment?

Possibly one of the most contentious aspects of our projected use of artificial intelligence is how it will affect the jobs and careers of humans. Which, of course, directly relates to how it will affect our livelihoods. There are typically two camps under the artificial intelligence umbrella – those who see AI as a form of assistance for professionals and manufacturers and those who view the use of artificial intelligence as a means to an end for their careers. Those who the use of artificial intelligence are worried, understandably so, that they could lose their jobs to a robot that comes with a much cheaper price tag.

There is no doubt that artificial intelligence has moved from sci-fi movies and fiction to a very real concept used in our world, today. Those who suggest that artificial intelligence is a threat to workforces all over the world predict that as much as 30 percent of the world’s human workforce could be replaced with intelligence agents and robots. To put that number in perspective, that is 400-800 million jobs within ten years, which means that as many as 375 million people could possibly have to switch industries entirely.

Others argue that artificial intelligence will help create a brighter future for the workforce by creating more jobs. This camp argues that robots are being to replace jobs that aren’t good or high-paying, to begin with, and the use of robots or AI agents for these kinds of jobs will empower and influence human employees to work towards higher-paying and higher-quality positions. There is, however, the fear that the transition will become generational and somewhat bumpy.

How do we really prepare an entire international workforce for a seismic shift? Certain industries are already experiencing the application of artificial intelligence systems, devices, and agents to assist professionals. One of the most notable industries is health care systems throughout the globe. These developments come in many different including systems that help doctors reach diagnostic decisions, triage assistance, and even digital applications that help trace and contain disease and virus outbreaks. For now, these technologies are helping the health care industry, but it is natural for health care professionals to fear the possibility of being replaced.

Of course, it is no secret that digital technologies greatly improve productivity, but it has not yet been confirmed that productivity growth will also lead to a growth in employment. Also, if developers, creators, officials, and corporation heads are suggesting that automation and digital technologies allow the workforce to seek better jobs, how even is the playing field? Sure, many people may be able to seek out higher education or career development resources, but what about the individuals who do not have the access or funding to support going to college or a trade school?

Before making claims regarding how artificial intelligence is going to affect the global employment situation, it is the responsibility of global leaders to invest time and resources to determine how AI affects the global workforce.

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Choosing AI’s Impact on the Future of Work

Rapid advances in AI threaten to eliminate many jobs, but there are still two distinct paths this AI revolution could take.

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By Daron Acemoglu & Simon Johnson Oct. 25, 2023

In November 2022, OpenAI grabbed headlines by releasing ChatGPT, and “generative AI” became a term used in households around the world. According to Open AI CEO Sam Altman , “A lot of people working on AI pretend that it’s only going to be good; it’s only going to be a supplement; no one is ever going to be replaced.” But, he adds, “jobs are definitely going to go away, full stop.” Two major labor strikes this year, by the Writers Guild of America and the actors union (SAG-AFTRA), have helped focus attention on the threat AI poses to well-paid jobs.

Artificial Intelligence is poised to upend work around the world over the coming decades. Whether this lessens or increases inequality remains to be seen. AI technology is relatively new, but the impacts of previous high-impact innovations like the power loom, steam engines, electricity, and digital computers shed ample light on what could happen next. The consequences of any technology depend on who gets to make pivotal decisions about how the technology develops. This is doubly true for AI, because these new tools can be developed for many different types of activities, with the potential to spread rapidly in every sector of the economy and in every aspect of our lives.

Too many commentators see the path of technology as inevitable. But the historical record is clear: technologies develop according to the vision and choices of those in positions of power. As we document in Power and Progress: Our 1,000-Year Struggle over Technology and Prosperity , when these choices are left entirely in the hands of a small elite, you should expect that group to receive most of the benefits, while everyone else bears the costs—potentially for a long time.

Rapid advances in AI threaten to eliminate many jobs, and not just those of writers and actors. Jobs with routine elements, such as in regulatory compliance or clerical work, and those that involve simple data collection, data summary, and writing tasks are likely to disappear.

But there are still two distinct paths that this AI revolution could take. One is the path of automation, based on the idea that AI’s role is to perform tasks as well as or better than people. Currently, this vision dominates in the US tech sector, where Microsoft and Google (and their ecosystems) are cranking hard to create new AI applications that can take over as many human tasks as possible.

The negative impact on people along the “just automate” path is easy to predict from prior waves of digital technologies and robotics. It was these earlier forms of automation that contributed to the decline of American manufacturing employment and the huge increase in inequality over the last four decades. If AI intensifies automation, we are very likely to get more of the same—a gap between capital and labor, more inequality between the professional class and the rest of the workers, and fewer good jobs in the economy.

There is a second, very different path available to us, however. This path would focus on creating new tasks and capabilities for humans, rather than sidelining them. This too is not new in history. The augmentation of human capabilities, by creating new tasks and providing better tools and information for workers, was the bedrock of wage growth and shared prosperity during the decades that followed World War II.

In principle, AI could magnify the possibilities for human-complementary technological change. It could enable the development of a wide array of tools that provide better information to human decision-makers. Critically, this need not be limited to office workers and professionals. Much of the workforce today, from blue-collar workers in factories to electricians, plumbers, educators, and health care providers, depends on problem-solving and real-time decision-making. With better context-specific information, these workers could become more productive in the tasks they are performing and venture into new, more complex tasks.

Alas, this more hopeful path is not where we are heading. Three big social changes would be necessary for such a path, and each one of them is a tall order.

First, management needs to see and understand workers as a key resource whose productivity should be augmented, whose information should be improved, and whose training should be a priority. But the dominant perspective in most C-suites views labor as a cost to be cut, either to withstand competition or to better remunerate shareholders. What gets lost in the rush to reengineer the corporation with fewer workers is the long-term health of the companies, which never achieve the promised productivity gains from so-so automation and offshoring. Companies must recognize that, in reality, labor is a critical resource for productivity growth.

Second, the tech sector needs to prioritize helping workers, rather than focusing on tools of automation and surveillance. The industry’s vision has too long been shaped by an ill-advised quest for artificial general intelligence and autonomous machine intelligence, and many technologists are still preoccupied by showing how their algorithms can reach “human parity.” In practice, that means automating as many tasks as possible.

Third, labor needs to have a voice in how technologies are used. This voice is critical not only for resisting excessive emphasis on labor cost-cutting and automation. It is also essential because workers typically know which parts of their jobs would benefit from automation and which would not. They recognize which tasks could be made more efficient, freeing them to spend time on more productive activities, or even creating new opportunities for increased productivity. Increased worker buy-in reduces businesses’ incentives for further intensification of worker monitoring and surveillance. It also ensures that any productivity gains are shared more fairly between capital and labor.

These three social changes are possible, even if very unlikely to happen without a coordinated effort.

There is much greater pushback against the “shareholder values revolution”—which elevated cost-cutting and the interests of shareholders at the expense of workers—than at any other time over the last four decades. A new philosophy prioritizing long-term productivity growth may yet emerge, which management and workers can work together to achieve.

The tech sector can change, too. It was always an aberration that arguably the most powerful industry in the US (and the world) would ignore all social responsibility and elevate the virtues of “disruption” with an almost religious zeal. In its next, more mature phase, the industry could focus on providing better tools for workers and augmenting human capabilities, rather than replacing them wholesale.

And labor can become better organized and better focused on charting a new course for involvement in the production process during the age of AI, which will also enhance productivity. In fact, pro-union sentiment is higher than we’ve seen in decades, and the WGA strike has set an example of how focusing on technology—who controls it and how it will be used—could become central to contract negotiations in other industries.

It is crucial, however, that the renewed energy of organized labor is channeled in the right way. Labor cannot hope to ask for and obtain high wages unless technology moves in a more pro-worker direction. Nor can one reasonably expect that opposing new technologies, including AI, will be a viable option for the union movement. Rather, leaders and rank-and-file workers alike must understand the potential of new tools, including artificial intelligence, and articulate a vision for how these technologies can be used in a way that helps both labor and corporations. Making workers more productive in their decision-making and problem-solving tasks is the bedrock of such an approach.

None of this will happen automatically. Any meaningful change must start with a recognition of the problem—technology is heading in an anti-labor direction. People promoting change must also recognize the feasibility and desirability of a pro-worker direction for technological change.

Neither the tech industry nor other large corporations will undertake a huge course correction without strong pressure from others in society. In addition to robust labor voices, government regulation and civil society organizations have previously played a critical role in pushing companies in the right direction. This role is even more important today when we need a fundamental redirection of AI technology.

The government should adopt a set of complementary policies encouraging a better path for technology use and development, as we detail in a recent policy memo (jointly written with our MIT colleague David Autor, through the new MIT Shaping the Future of Work Initiative that we collectively co-direct) entitled “ Can We Have Pro-Worker AI? ”

Lawmakers should revise the federal tax code to equalize the tax burden across labor and machines, so companies are encouraged to hire, train, and retain human workers. Regulatory agencies should also find ways to include and amplify worker voice on how AI and other technology is used in the workplace—including regulating AI-assisted personnel management and placing safeguards around workplace surveillance.

The public sector should invest in research that prioritizes human-complementary AI technology and create a federal government consultative AI center of expertise to support lawmakers and officials who need to understand this technology. We should use this federal expertise to assess whether specific AI technologies live up to their promise to augment human work before they are rolled out in any publicly funded programs such as education or health care.

There is much to be alarmed about when it comes to AI. But if AI brings a dystopian future, it will not be because this was the only path available to us. It will be because we failed to grasp how this technology could be developed and used, and how it could help workers, rather than just replacing them. Understanding this is a first step toward the right type of AI revolution.

How can data-driven technology be harnessed to give power back to workers? Listen to a case study from SSIR’s 2023 Data on Purpose conference :

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Global challenges- Global solutions podcast

20 November 2023

Are we smart enough to manage the impact of Artificial Intelligence on the world of work? It seems that Artificial Intelligence (AI) is raising concerns in some quarters, especially in the world of work these days. But in fact, these concerns about whether the growth of AI is “a threat or a promise” have been growing for years. Is this concern warranted? In this episode Uma Rani, a Senior Economist at the ILO’s Research Department and Enrique Fernandez Macias, a researcher at the European Commission’s Joint Research Centre explore what kind of research and policies should be considered to better assess the impact of AI on such issues as gender balance, achieving social justice, and other ethical and moral questions arising from its use in the workplace in both developed and developing economies. This podcast is also available on Spotify and Apple Podcasts.

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Threat or Opportunity – Analysis of the Impact of Artificial Intelligence on Future Employment

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• Fenglian Wang 9 ,
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As the main force of the future development of science and technology, artificial intelligence technology has become the direction of many countries, enterprises and researchers. However, the technological progress represented by artificial intelligence has brought tremendous changes to the labor market, and also has a significant impact on the employment and income distribution of workers. In this paper, we use the methods of text survey, questionnaire survey and in-depth interview to explore the impact of AI on future employment. Specifically, this paper takes the most representative second and third tier cities as the research objects, and uses multiple linear regression analysis technology to study the understanding of the practitioners on the artificial intelligence technology; the acceptance of the practitioners on the artificial intelligence; the reasons why the artificial intelligence technology may cause the difficulty of the employment situation; the new employment opportunities that the artificial intelligence may produce; the strategies to deal with the impact of the artificial intelligence Some suggestions. This paper studies the impact of AI on future employment, and puts forward corresponding suggestions and countermeasures from the government, enterprises, universities and individuals.

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Li, Z.: Application of artificial intelligence in computer network technology. Electron. Technol. Softw. Eng. (10), 8 (2018)

Google Scholar  

Zhao, B., Du, Y.: How does artificial intelligence affect your career choice?. Study Abroad (14), 12–14 (2018)

Wang, T.: Impact of artificial intelligence on employment. J. Jiamusi Vocational College (07), 287–288+290 (2019)

Li, Z., Bao, Z.: “Cloud management”: a new model of social governance in the era of big data. Tianjin Soc. Sci. (03), 62–67 (2015)

National Science and Technology Council: Preparing for the future of artificial intelligence [OL]

Zhao, C.: Research on the two-way impact of artificial intelligence development on labor employment. Coop. Econ. Technol. (15), 120–121 (2019)

Huang, X.: Philosophical reflection on the upsurge of artificial intelligence. J. Shanghai Normal Univ. (Philos. Soc. Sci. Ed.) 47 (04), 34–42 (2008)

Tao, X., Chen, S.: “Out of control” and “doing nothing”: towards a partner type of man-machine relationship. J. Beijing Univ. Sci. Technol. (Soc. Sci. Ed.), (5), 70–77 (2019). [2019-10-21]

Jia, K., Jiang, Y.: Three basic problems of AI governance: technical logic, risk challenge and public policy choice. China Adm. (10), 40–45 (2017)

Guo, H., Qu, F., Zhan, P.: Research on information sharing service model and its application in smart city. J. Intell. 36 (04), 118–124 (2017)

He, Z.: Government adaptation and transformation in the era of artificial intelligence. Adm. Manage. Reform (08), 53–59 (2016)

Deng, J., Zhang, M., Zhu, L., Wang, M., Zhang, J.: Social network analysis of collaborative innovation system of social governance. China Sci. Technol. Forum (04), 18–24 (2016)

Frank, M.R., et al.: Toward understanding the impact of artificial intelligence on labor. Proc. Nat. Acad. Sci. U.S.A. 116 (14), 6531–6539 (2019)

Article   Google Scholar  

Agrawal, A., Gans, J.S., Goldfarb, A.: Artificial intelligence: the ambiguous labor market impact of automating prediction. J. Econ. Perspect. 33 (2), 31–49 (2019)

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Acknowledgments

We wish to thank Xinlei Zhou, Zhiyi He, Xinfeng Lin for sending out questionnaire and some commissions for the research assistance. This study is supported by National Social Science Fund of China(16BGL201), Key Project of humanities and social sciences in Anhui Province(SK2018A0111) and General Project of philosophy and social science in Anhui Province(AHSKY2019D022).

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Wang, F., Hu, M., Zhu, M. (2020). Threat or Opportunity – Analysis of the Impact of Artificial Intelligence on Future Employment. In: Duffy, V. (eds) Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Human Communication, Organization and Work. HCII 2020. Lecture Notes in Computer Science(), vol 12199. Springer, Cham. https://doi.org/10.1007/978-3-030-49907-5_21

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Is artificial intelligence the biggest threat to jobs?

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Stay up to date:, emerging technologies.

The HAL 9000 wants your job.

OK, it’s not the HAL 9000 (yet) but all over the world, intelligent machines are replacing jobs at an alarming rate. And the smarter they get, the faster they’re going to be replacing us. What I am talking about here is not a subtle shift to more automation but a real threat to society and the human race.

From self-driving cars and robot waiters to robotic doctors and robot journalists , what seem like novelties today will soon be commonplace. As just one example take Foxconn, the largest private employer in China that contract manufactures of products such as the iPhone, Kindle, Playstation etc. This giant company is installing 30,000 robots each year to perform tasks — tasks that used to be performed by a human worker. Terry Gou, Foxconn’s CEO, told his annual meeting , “We have over one million workers. In the future we will add one million robotic workers.”

And those one million robots will displace at least one million human workers.

What’s more, as the price of robots comes down each year, it will soon make sense to replace workers even in the lowest cost economies around the world.

The Rise of The Intelligent Robot

The threat, however, isn’t just from having more machines and trying to find work for all the manual workers that are being replaced, but from having smarter machines.

Computers (not necessarily robots in the physical sense) are already taking over certain jobs that traditionally only humans could perform. Economist Brian Arthur has coined the term “ Second Economy ” to describe transactions that take place between two computers, with no input from a worker.

Arthur estimates that the Second Economy will be as large as the first by 2025 — removing the need for as many as 100 million jobs.

The problem is that as computers get smarter, more and more people will be displaced from the workforce.

In an article in the Harvard Business Review , the authors postulate that if computers could be said to have an average IQ today of, say, 100 points, increasing their IQ by just 1.5 points per year would result in computers being smarter than 90 percent of the American population by 2025.

This is a particularly scary thought considering that over the history of commuting we have seen computers double their processing power every two years or so, which means they are indeed getting a lot smarter year by year.

When Machines Outsmart Humans

What happens when we create machines that have artificial intelligence (AI), when computers are smarter than humans and can act on their own?

Well, nothing good, according to Elon Musk, founder of Tesla, and Professor Stephen Hawking , one of the world’s most respected scientists.

Both men have said in recent interviews that unless we find a way to control AI, the results could be disastrous. Popular fiction from Do Androids Dream of Electric Sheep to Terminator to 2001: A Space Oddessy have imagined how AI might rise up and destroy us, but some of the greatest thinkers of our time are suggesting it’s not that far fetched.

(If you want to be completely freaked out by the possibilities, read this excellent article that details “the button problem” with AI. )

Others say we have much bigger problems to worry about than being destroyed by sentient robots; but if we continue along this path, outsourcing so many human jobs to robots and computers without making up for it with better education and training, we may not need a fanciful all-knowing computer to destroy us. We’ll have done it to ourselves.

“This is the way the world ends: Not with a bang but a whimper.”

This article is published in collaboration with LinkedIn . Publication does not imply endorsement of views by the World Economic Forum.

To keep up with Forum:Agenda  subscribe to our weekly newsletter .

Author: Bernard Marr is a globally recognized expert in strategy, performance management, analytics, KPIs and big data.

Image: Image: Robot arms coat a Porsche Macan at the new plant in the eastern German city of Leipzig February 5, 2014. REUTERS/Tobias Schwarz.

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Artificial intelligence: threats and opportunities

Artificial intelligence (AI) affects our lives more and more. Learn about the opportunities and threats for security, democracy, businesses and jobs.

Europe's growth and wealth are closely connected to how it will make use of data and connected technologies. AI can make a big difference to our lives – for better or worse . In June 2023, The European Parliament adopted its negotiating position on the AI Act – the world’s first set of comprehensive rules to manage AI risks.Below are some key opportunities and threats connected to future applications of AI.

Read more about what artificial intelligence is and how it is used

175 zettabytes

The volume of data produced in the world is expected to grow from 33 zettabytes in 2018 to 175 zettabytes in 2025 (one zettabyte is a thousand billion gigabytes)

Advantages of AI

EU countries are already strong in digital industry and business-to-business applications. With a high-quality digital infrastructure and a regulatory framework that protects privacy and freedom of speech, the EU could become a global leader in the data economy and its applications .

Benefits of AI for people

AI could help people   with improved health care, safer cars and other transport systems, tailored, cheaper and longer-lasting products and services. It can also facilitate access to information, education and training.  The need for distance learning became more important because of the Covid-19 pandemic . AI can also make workplace safer as robots can be used for dangerous parts of jobs, and open new job positions as AI-driven industries grow and change.

Opportunities of artificial intelligence for businesses

For businesses , AI can enable the development of a new generation of products and services, including in sectors where European companies already have strong positions: green and circular economy, machinery, farming, healthcare, fashion, tourism. It can boost sales, improve machine maintenance, increase production output and quality, improve customer service, as well as save energy.

Estimated increase of labour productivity related to AI by 2035 (Parliament's Think Tank 2020)

AI opportunities in public services

AI used in public services can reduce costs and offer new possibilities in public transport, education, energy and waste management and could also improve the sustainability of products. In this way AI could contribute to achieving the goals of the EU Green Deal .

Estimate of how much AI could help reduce global greenhouse emissions by 2030 (Parliament's Think Tank 2020)

Strengthening democracy

Democracy could be made stronger by using data-based scrutiny, preventing disinformation and cyber attacks and ensuring access to quality information . AI could also support diversity and openness, for example by mitigating the possibility of prejudice in hiring decisions and using analytical data instead.

AI, security and safety

AI is predicted to be used more in crime prevention and the criminal justice system , as massive data sets could be processed faster, prisoner flight risks assessed more accurately, crime or even terrorist attacks predicted and prevented. It is already used by online platforms to detect and react to unlawful and inappropriate online behaviour.

In military matters , AI could be used for defence and attack strategies in hacking and phishing or to target key systems in cyberwarfare.

Threats and challenges of AI

The increasing reliance on AI systems also poses potential risks.

Underuse and overuse of AI

Underuse of AI is considered as a major threat: missed opportunities for the EU could mean poor implementation of major programmes, such as the EU Green Deal, losing competitive advantage towards other parts of the world, economic stagnation and poorer possibilities for people. Underuse could derive from public and business' mistrust in AI, poor infrastructure, lack of initiative, low investments, or, since AI's machine learning is dependent on data, from fragmented digital markets.

Overuse can also be problematic: investing in AI applications that prove not to be useful or applying AI to tasks for which it is not suited, for example using it to explain complex societal issues.

Liability: who is responsible for damage caused by AI?

An important challenge is to determine who is responsible for damage caused by an AI-operated device or service: in an accident involving a self-driving car. Should the damage be covered by the owner, the car manufacturer or the programmer?

If the producer was absolutely free of accountability, there might be no incentive to provide good product or service and it could damage people’s trust in the technology; but regulations could also be too strict and stifle innovation.

Threats of AI to fundamental rights and democracy

The results that AI produces depend on how it is designed and what data it uses. Both design and data can be intentionally or unintentionally biased. For example, some important aspects of an issue might not be programmed into the algorithm or might be programmed to reflect and replicate structural biases. In adcition, the use of numbers to represent complex social reality could make the AI seem factual and precise when it isn’t . This is sometimes referred to as mathwashing.

If not done properly, AI could lead to decisions influenced by data on  ethnicity, sex, age when hiring or firing, offering loans, or even in criminal proceedings.

AI could severely affect the right to privacy and data protection. It can be for example used in face recognition equipment or for online tracking and profiling of individuals. In addition, AI enables merging pieces of information a person has given into new data, which can lead to results the person would not expect.

It can also present a threat to democracy; AI has already been blamed for creating online echo chambers based on a person's previous online behaviour, displaying only content a person would like, instead of creating an environment for pluralistic, equally accessible and inclusive public debate. It can even be used to create extremely realistic fake video, audio and images, known as deepfakes, which can present financial risks, harm reputation, and challenge decision making. All of this could lead to separation and polarisation in the public sphere and manipulate elections.

AI could also play a role in harming freedom of assembly and protest as it could track and profile individuals linked to certain beliefs or actions.

AI impact on jobs

Use of AI in the workplace is expected to result in the elimination of a large number of jobs. Though AI is also expected to create and make better jobs, education and training will have a crucial role in preventing long-term unemployment and ensure a skilled workforce.

of jobs in OECD countries are highly automatable and another 32% could face substantial changes (estimate by Parliament's Think Tank 2020).

Competition

Amassing information could also lead to distortion of competition as  companies with more information could gain an advantage and effectively eliminate competitors.

Safety and security risks

AI applications that are in physical contact with humans or integrated into the human body could pose safety risks as they may be poorly designed, misused or hacked. Poorly regulated use of AI in weapons could lead to loss of human control over dangerous weapons.

Transparency challenges

Imbalances of access to information could be exploited. For example, based on a person's online behaviour or other data and without their knowledge, an online vendor can use AI to predict someone is willing to pay, or a political campaign can adapt their message. Another transparency issue is that sometimes it can be unclear to people whether they are interacting with AI or a person.

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Artificial Intelligence and Its Impact on Jobs

Everywhere you turn today is some unbelievable technological advancement on a variety of fronts. In our everyday lives, we hear or experience things about autonomous vehicles, warehouse robots, chatbots, Alexa, Siri, Uber, automated email responses, robotic surgeries, Netflix recommendation systems, smart factories, smart buildings and search retargeting. Technology giants are becoming the most valuable companies on the planet, and we see our lives shifting from what we thought was kids and their smartphone addictions and gaming to encroaching on our daily lives across the board. They are typically revolving around a variety of enabling technology layers, namely, cloud computing, computational systems, networks and sensors, robotics, material sciences, digital manufacturing and artificial intelligence. However, at the center of it, is AI that permeates many of the other advances in some shape or form in creating intelligent systems on top of advances in core products or technologies.

“Computers, intelligent machines and robots seem like the workforce of the future. And as more and more jobs are replaced by technology, people will have less work to do and ultimately will be sustained by payments from the government,” predicts Elon Musk, the cofounder and CEO of Tesla. This is a scary proposition in some sense, in that what will we do if all the work is done by AI or robots? Isn’t life tough enough? Don’t we have enough economic disparity and can barely make ends meet today? To add insult to injury, many of the analyses seem to center on displacing the low wage workers. As if they didn’t have enough disadvantages already, their entire economic class will be wiped out is the feeling we get from the news cycle. This is evidenced by robotic warehouses and chatbots or automated customer service and we can really feel the changes all around us.

Innovation and technology are certainly changing; skills and jobs as we know them today will need to change. Our frame of reference is being disrupted like never before, the guideposts and rules are changing, and this causes discomfort, uncertainty and worry. How can we chart the course if we are uncertain that the traditional methods (hard work, educational degrees, etc.) do not necessarily guarantee a certain quality of life? News flash, it is changing rapidly and therefore uncertain. We need to all become comfortable with being uncomfortable, with adapting to change, continuing education and reskilling. Some reports predict that millennials will change their jobs 17 times, but that might be a low number when you really factor in the gig economy.

According to various reports, the warnings suggest that AI could lead to the loss of tens of millions of jobs. It begs the question, when or what is the time horizon of the adoption of AI and the job loss a reality? Many reports suggest of job displacement or the very nature of jobs shifting. Automation and technology have shifted work in pursuit of lowering costs, increasing efficiency and production. The automobile “displaced” work that was done via horse and buggy, electricity or fluorescent lighting displaced gas lamps and gas replaced coal in many instances. Jobs have been displaced in the past, but in today’s case the rate at which these exponential technologies are growing is moving faster than the rate of human adaptation. That speed at which we are experiencing technological and societal change is only the beginning as many futurists, such as Peter Diamandis, prophesize.

Bloomberg reports that “more than 120 million workers globally will need retraining in the next three years due to artificial intelligence’s impact on jobs, according to an IBM survey.” That report and interpretations of it seem to suggest that adoption of AI may result in massive job losses and requires massive retraining. This paints a doomsday scenario, creates uncertainty and worry. The interpretation is AI equals job loss; we would argue that the interpretation should be interpreted as AI and technology advancements will require job retraining and job reskilling. The reports also seem to suggest that our educational system is preparing for jobs of today, when we see that the jobs of the future will be quite different, with different resources and tools at our disposal. This further creates panic in that we see nothing but chaos and the inability to control our destiny for ourselves and our children.

The report was MIT-IBM Watson Lab research that shed light on the reorganization of tasks within occupations by analyzing 170 million online job postings in the U.S. between 2010-17. There is no question that AI and related technologies will affect all jobs; what the report did shed light on was the fact how the nature of work is changing, how tasks are changing and tried to link the implications for employment and wages. There were some key findings in the report, that tasks are shifting between people and machines (or AI), but the change has been small (Figure 1).

Automation or AI is disappearing from job requirements, shifting in the way work gets done; as technology reduces the cost of some tasks, the value of remaining tasks increases, particularly soft skills such as creativity, common sense, judgment and communication skills.

This type of analysis is what experts refer to as the “future of work” and how the work is shifting, job requirements are changing, and automation and AI are displacing certain sectors of the labor market. It also informs policymakers of where to focus attention and resources in order to best prepare for the future. Many of the takeaways and political talk seem to focus on “the vulnerable will be the most vulnerable” as a key takeaway, and that better-educated workers will fare out alright as AI/automation spreads. As a McKinsey report forecasted 800 million global workers could be replaced by robots by 2030, they further stated that blue-collar jobs, such as machine operating, warehouse workers and fast food are particularly susceptible to disruption.

But a new study published by the Brookings institution states that might not be the case. The report looked at thousands of AI patents and job descriptions and that educated, well-paid workers may be affected even more by the spread of AI. Most consider robotics and software as impacting the physical and routine work of traditionally blue-collar jobs. The report goes on to state that workers with a bachelor’s degree, for example, would be exposed to AI over five times more than those with only a high school degree. That is due to the fact AI is very strong at completing tasks that require planning, learning, reasoning, problem-solving and predicting – most of which are skills we think of as white-collar jobs.

This analysis of patent data and tasks and exposure to risk on a sampling of various occupations in Table 2.

AI’s impact on the workplace, the future of work, sectors of the economy and global domination are hard to assess. Most forecasts are rooted in well-established, well-understood technologies such as robotics and extrapolated across of a range of tasks, functions and jobs. The nature of AI being new and poorly understood, nonetheless unsuccessfully implemented across all industries, makes it even more difficult to understand. There is no shared agreement on the tasks, nor the expected impacts on the workforce or economy. The best scholars concede to the limitations of their economic or forecasts for the future. What we do know is that the nature of work will change, as it has through the centuries with innovation. We do know that disruption will occur in sectors of the economy, and we should brace for that change and try to harness that change for good. Perhaps AI can see patterns in deadly diseases, fight climate change and explore the universe. We should be as excited as nervous about change, and try to the best of our abilities to shape our society for that coming change.

Author bios:

Manjeet Rege is an associate professor of Graduate Programs in Software and Data Science and Director of Center for Applied Artificial Intelligence at the University of St. Thomas. Dr. Rege is an author, mentor, thought leader, and a frequent public speaker on big data, machine learning and artificial intelligence technologies. He is also the co-host of the "All Things Data" podcast that brings together leading data scientists, technologists, business model experts and futurists to discuss strategies to utilize, harness and deploy data science, data-driven strategies and enable digital transformation. Apart from being engaged in research, Dr. Rege regularly consults with various organizations to provide expert guidance for building big data and AI practice, and applying innovative data science approaches. He has published in various peer-reviewed reputed venues such as IEEE Transactions on Knowledge and Data Engineering, Data Mining & Knowledge Discovery Journal, IEEE International Conference on Data Mining, and the World Wide Web Conference. He is on the editorial review board of Journal of Computer Information Systems and regularly serves on the program committees of various international conferences.

For more thought leadership on AI, read about the global battle for AI dominance in this Tommie Experts piece.

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The profound impact of Artificial Intelligence on society – Exploring the far-reaching implications of AI technology

Artificial intelligence (AI) has revolutionized the way we live and work, and its influence on society continues to grow. This essay explores the impact of AI on various aspects of our lives, including economy, employment, healthcare, and even creativity.

One of the most significant impacts of AI is on the economy. AI-powered systems have the potential to streamline and automate various processes, increasing efficiency and productivity. This can lead to economic growth and increased competitiveness in the global market. However, it also raises concerns about job displacement and income inequality, as AI technologies replace certain job roles.

In the realm of healthcare, AI has already made its mark. From early detection of diseases to personalized treatment plans, AI algorithms have become invaluable in improving patient outcomes. With the ability to analyze vast amounts of medical data, AI systems can identify patterns and make predictions that human doctors may miss. Nevertheless, ethical considerations regarding patient privacy and data security need to be addressed.

Furthermore, AI’s impact on creativity is an area of ongoing exploration. While AI technologies can generate artwork, music, and literature, the question of whether they can truly replicate human creativity remains. Some argue that AI can enhance human creativity by providing new tools and inspiration, while others fear that it may diminish the value of genuine human artistic expression.

In conclusion, the impact of artificial intelligence on society is multifaceted. While it brings economic advancements and improvements in healthcare, it also presents challenges and ethical dilemmas. As AI continues to evolve, it is crucial to strike a balance that maximizes its benefits while minimizing its potential drawbacks.

The Definition of Artificial Intelligence

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. It involves the development of computer systems that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and problem-solving.

AI has a profound impact on society, revolutionizing various industries and sectors. Its disruptive nature has led to significant advancements in the way businesses operate, healthcare is delivered, and everyday tasks are performed. AI technologies have the potential to automate repetitive tasks, analyze vast amounts of data with speed and accuracy, and enhance the efficiency and effectiveness of various processes.

Furthermore, AI has the potential to transform the workforce, leading to changes in the job market. While some fear that AI will replace human workers and result in unemployment, others argue that it will create new job opportunities and improve overall productivity. The societal impact of AI is complex and multifaceted, necessitating careful consideration and management.

In summary , artificial intelligence is the development of computer systems that can mimic human intelligence and perform tasks that traditionally require human thinking. Its impact on society is vast, affecting industries, job markets, and everyday life. Understanding the definition and implications of AI is crucial as we navigate the ever-evolving technological landscape.

The History of Artificial Intelligence

The impact of artificial intelligence on society is a topic that has gained increasing attention in recent years. As technology continues to advance at a rapid pace, the capabilities of artificial intelligence are expanding as well. But how did we get to this point? Let’s take a brief look at the history of artificial intelligence.

The concept of artificial intelligence dates back to ancient times, with the development of mechanical devices that were capable of performing simple calculations. However, it wasn’t until the mid-20th century that the field of AI began to take shape.

In 1956, a group of researchers organized the famous Dartmouth Conference, where the field of AI was officially born. This conference brought together leading experts from various disciplines to explore the possibilities of creating “machines that can think.”

During the following decades, AI research progressed with the development of first-generation computers and the introduction of programming languages. In the 1960s, researchers focused on creating natural language processing systems, while in the 1970s, expert systems became popular.

However, in the 1980s, AI faced a major setback known as the “AI winter.” Funding for AI research significantly declined due to the lack of significant breakthroughs. The field faced criticism and skepticism, and it seemed that the promise of AI might never be realized.

But in the 1990s, AI began to emerge from its winter. The introduction of powerful computers and the availability of massive amounts of data fueled the development of machine learning algorithms. This led to significant advancements in areas such as computer vision, speech recognition, and natural language processing.

Over the past few decades, AI has continued to evolve and impact various aspects of society. From virtual assistants like Siri and Alexa to autonomous vehicles and recommendation systems, artificial intelligence is becoming increasingly integrated into our daily lives.

As we move forward, the impact of artificial intelligence on society is only expected to grow. With ongoing advancements in AI technology, we can expect to see even more significant changes in fields such as healthcare, finance, transportation, and more.

In conclusion, the history of artificial intelligence is one of perseverance and innovation. From its humble beginnings to its current state, AI has come a long way. It has evolved from simple mechanical devices to complex algorithms that can learn and make decisions. The impact of artificial intelligence on society will continue to shape our future, and it is essential to consider both the positive and negative implications as we navigate this technological revolution.

The Advantages of Artificial Intelligence

Artificial intelligence (AI) is a rapidly developing technology that is having a significant impact on society. It has the potential to revolutionize various aspects of our lives, bringing about many advantages that can benefit individuals and communities alike.

1. Increased Efficiency

One of the major advantages of AI is its ability to automate tasks and processes, leading to increased efficiency. AI systems can analyze large amounts of data and perform complex calculations at a speed much faster than humans. This can help businesses optimize their operations, reduce costs, and improve productivity.

2. Enhanced Accuracy

AI technologies can also improve accuracy and precision in various domains. Machine learning algorithms can learn from large datasets and make predictions or decisions with a high level of accuracy. This can be particularly beneficial in fields such as healthcare, where AI can assist doctors in diagnosing diseases, detecting patterns in medical images, and recommending personalized treatments.

Additionally, AI-powered systems can minimize human error in areas where precision is crucial, such as manufacturing and transportation. By automating repetitive tasks and monitoring processes in real-time, AI can help avoid costly mistakes and improve overall quality.

Overall, the advantages of artificial intelligence are numerous and diverse. From increased efficiency to enhanced accuracy, AI has the potential to transform various industries and improve the quality of life for individuals and societies as a whole. It is crucial, however, to continue exploring the ethical implications of AI and ensure that its development is guided by principles that prioritize the well-being and safety of humanity.

The Disadvantages of Artificial Intelligence

While the impact of artificial intelligence on society has been largely positive, it is important to also consider its disadvantages.

1. Job Displacement

One of the biggest concerns regarding artificial intelligence is the potential for job displacement. As machines become more intelligent and capable of performing complex tasks, there is a growing fear that many jobs will become obsolete. This can lead to unemployment and economic instability, as individuals struggle to find work in a society increasingly dominated by artificial intelligence.

2. Ethical Concerns

Another disadvantage of artificial intelligence is the ethical concerns it raises. As artificial intelligence systems become more advanced, there is a need for clear guidelines and regulations to ensure that they are used responsibly. Issues such as privacy, data protection, and algorithmic bias need to be addressed to prevent misuse or unintended consequences.

In conclusion, while artificial intelligence has had a positive impact on society, there are also disadvantages that need to be considered. Job displacement and ethical concerns are just a few of the challenges that need to be addressed as we continue to advance in the field of artificial intelligence.

The Ethical Concerns of Artificial Intelligence

As artificial intelligence continues to impact society in numerous ways, it is important to address the ethical concerns that arise from its use. As AI becomes more commonplace in various industries, including healthcare, finance, and transportation, the potential for unintended consequences and ethical dilemmas increases.

One of the primary ethical concerns of artificial intelligence is the issue of privacy. With the advancements in AI technology, there is a growing ability for machines to collect and analyze vast amounts of personal data. This raises questions about how this data is used, who has access to it, and whether individuals have a right to control and protect their own information.

Another ethical concern is the potential for AI to perpetuate and amplify existing biases and discrimination. AI algorithms are trained on existing data, which can reflect societal biases and prejudices. If these biases are not identified and addressed, AI systems can inadvertently perpetuate unfair practices and discrimination, leading to negative impacts on marginalized communities.

Additionally, the use of AI in decision-making processes raises concerns about accountability and transparency. As AI systems make more complex decisions that affect individuals’ lives, it becomes crucial to understand how these decisions are made. Lack of transparency and accountability can result in a loss of trust in AI systems, especially if they make decisions that have significant consequences.

Furthermore, there is the concern of the impact of AI on employment and the workforce. As AI technology advances, there is the potential for job displacement and the loss of livelihoods. This raises questions about the responsibility of society to provide support and retraining for individuals who are affected by the automation of tasks previously carried out by humans.

Overall, as artificial intelligence continues to evolve and become more integrated into society, it is crucial to actively address the ethical concerns that arise. This involves establishing clear guidelines and regulations to safeguard privacy, address biases, ensure transparency, and mitigate the impact on employment. By addressing these concerns proactively, society can harness the benefits of AI while minimizing its negative impacts.

The Impact of Artificial Intelligence on Jobs

The advancement of artificial intelligence (AI) technology is having a profound impact on society as a whole. One area that is particularly affected by this technological revolution is the job market. The introduction of AI into various industries is changing the way we work and the types of jobs that are available. It is important to understand the implications of this impact on jobs and how it will shape the future of work.

The Rise of Automation

One of the main ways AI impacts jobs is through automation. AI algorithms and machines are increasingly replacing human workers in repetitive and routine tasks. Jobs that involve tasks that can be easily automated, such as data entry or assembly line work, are being taken over by AI-powered technology. This shift towards automation has the potential to lead to job displacement and unemployment for many individuals.

New Opportunities and Skill Requirements

While AI may be replacing certain jobs, it is also creating new opportunities. As industries become more automated, there is a growing demand for workers who are skilled in managing and developing AI technology. Jobs that require expertise in AI programming and data analysis are becoming increasingly important. This means that individuals who possess these skills will have an advantage in the job market, while those without them may struggle to find employment.

Furthermore, AI technology has the potential to transform existing jobs rather than eliminate them entirely. As AI systems become more sophisticated, they can assist human workers in performing tasks more efficiently and accurately. This collaboration between humans and machines can lead to increased productivity and job growth in certain industries.

The Need for Adaptation and Lifelong Learning

The impact of AI on jobs highlights the importance of adaptation and lifelong learning. As technology continues to evolve, workers must be willing to learn new skills and adapt to changing job requirements. The ability to continuously update one’s skills will be crucial in order to remain relevant in the job market. This necessitates a shift towards lifelong learning and a willingness to embrace new technologies.

In conclusion, the impact of artificial intelligence on jobs is significant and multifaceted. While AI technology has the potential to automate certain tasks and lead to job displacement, it also creates new opportunities and changes the nature of existing jobs. The key to navigating this changing job market is adaptation, lifelong learning, and acquiring new skills in AI-related fields. By understanding and adapting to the impact of AI on jobs, society can ensure that the benefits of this technology are maximized while minimizing negative consequences.

The Impact of Artificial Intelligence on Education

Artificial intelligence (AI) is rapidly transforming various aspects of society, and one area where its impact is particularly noteworthy is education. In this essay, we will explore how AI is revolutionizing the educational landscape and the implications it has for both teachers and students.

AI has the potential to greatly enhance the learning experience for students. With intelligent algorithms and personalized learning platforms, students can receive customized instruction tailored to their individual needs and learning styles. This can help to bridge gaps in understanding, improve retention, and ultimately lead to better academic outcomes.

Moreover, AI can serve as a valuable tool for teachers. By automating administrative tasks, such as grading and data analysis, teachers can save time and focus on what they do best: teaching. AI can also provide valuable insights into student performance and progress, allowing teachers to identify areas where additional support may be needed.

However, it is important to recognize that AI is not a substitute for human teachers. While AI can provide personalized instruction and automate certain tasks, it lacks the emotional intelligence and interpersonal skills that are essential for effective teaching. Teachers play a critical role in creating a supportive and nurturing learning environment, and their expertise cannot be replaced by technology.

Another concern is the potential bias and ethical implications associated with AI in education. With algorithms determining the content and delivery of educational materials, there is a risk of reinforcing existing inequalities and perpetuating discriminatory practices. It is crucial to ensure that AI systems are designed and implemented in an ethical and inclusive manner, taking into account issues of fairness and equity.

In conclusion, the impact of artificial intelligence on education is profound. It has the potential to revolutionize the way students learn and teachers teach. However, it is crucial to approach AI in education with caution, being mindful of the limitations and ethical considerations. By harnessing the power of AI while preserving the irreplaceable role of human teachers, we can create a future of education that is truly transformative.

The Impact of Artificial Intelligence on Healthcare

Artificial intelligence (AI) is revolutionizing the healthcare industry, and its impact on society cannot be overstated. Through the use of advanced algorithms and machine learning, AI is transforming various aspects of healthcare, from diagnosis and treatment to drug discovery and patient care.

One of the key areas where AI is making a significant impact is in diagnosing diseases. With the ability to analyze massive amounts of medical data, AI algorithms can now detect patterns and identify potential diseases in patients more accurately and efficiently than ever before. This can lead to early detection and intervention, ultimately saving lives.

AI is also streamlining the drug discovery process, which traditionally has been a time-consuming and costly endeavor. By analyzing vast amounts of data and simulating molecular structures, AI can help researchers identify potential drug candidates more quickly and accurately. This has the potential to accelerate the development of new treatments and improve patient outcomes.

Furthermore, AI is transforming patient care through personalized medicine. By analyzing an individual’s genetic and medical data, AI algorithms can provide personalized treatment plans tailored to the specific needs of each patient. This can lead to more effective treatments, reduced side effects, and improved overall patient satisfaction.

In addition to diagnosis and treatment, AI is also improving healthcare delivery and efficiency. AI-powered chatbots and virtual assistants can now provide patients with personalized medical advice and answer their questions 24/7. This reduces the burden on healthcare providers and allows for more accessible and convenient healthcare services.

However, as with any new technology, there are also challenges and concerns surrounding the use of AI in healthcare. Issues such as data privacy, ethical considerations, and bias in algorithms need to be addressed to ensure that AI is used responsibly and for the benefit of all patients.

In conclusion, the impact of artificial intelligence on healthcare is immense. With advancements in AI, the healthcare industry is poised to revolutionize patient care, diagnosis, and treatment. However, it is crucial to address the ethical and privacy concerns associated with AI to ensure that it is used responsibly and for the greater good of society.

The Impact of Artificial Intelligence on Transportation

Artificial intelligence (AI) has had a significant impact on society in many different areas, and one of the fields that has benefited greatly from AI technology is transportation. With advances in AI, transportation systems have become more efficient, safer, and more environmentally friendly.

Improved Safety

One of the key impacts of AI on transportation is the improved safety of both passengers and drivers. AI technology has enabled the development of autonomous vehicles, which can operate without human intervention. These vehicles use AI algorithms and sensors to navigate roads, avoiding accidents and minimizing collisions. By removing the human element from driving, the risk of human error and accidents caused by fatigue, distraction, or impaired judgment can be significantly reduced.

Efficient Traffic Management

AI has also revolutionized traffic management systems, leading to more efficient transportation networks. Intelligent traffic lights, for example, can use AI algorithms to adjust signal timings based on real-time traffic conditions, optimizing traffic flow and reducing congestion. AI-powered algorithms can analyze large amounts of data from various sources, such as traffic cameras and sensors, to provide accurate predictions and recommendations for traffic management and planning.

Enhanced Logistics and Delivery

AI has significantly impacted the logistics and delivery industry. AI-powered software can optimize route planning for delivery vehicles, taking into account factors such as traffic conditions, weather, and delivery time windows. This improves efficiency and reduces costs by minimizing fuel consumption and maximizing the number of deliveries per trip. Additionally, AI can also assist in package sorting and tracking, enhancing the overall speed and accuracy of the delivery process.

The impact of AI on transportation is continuously evolving, with ongoing research and development leading to even more advanced applications. As AI technology continues to improve, we can expect transportation systems to become even safer, more efficient, and more sustainable.

The Impact of Artificial Intelligence on Communication

Artificial intelligence has had a profound impact on society, affecting various aspects of our lives. One area where its influence can be seen is in communication. The advancements in artificial intelligence have revolutionized the way we communicate with each other.

One of the main impacts of artificial intelligence on communication is the development of chatbots. These computer programs are designed to simulate human conversation and interact with users through messaging systems. Chatbots have become increasingly popular in customer service, providing quick and automated responses to customer inquiries. They are available 24/7, ensuring constant support and improving customer satisfaction.

Moreover, artificial intelligence has contributed to the improvement of language translation. Translation tools powered by AI technology have made it easier for people to communicate across languages and cultures. These tools can instantly translate text and speech, enabling effective communication in real-time. They have bridged the language barrier and facilitated global collaboration and understanding.

Another impact of artificial intelligence on communication is the emergence of voice assistants. These virtual assistants, such as Siri and Alexa, use natural language processing and machine learning algorithms to understand and respond to user commands. Voice assistants have become integral parts of our daily lives, helping us perform various tasks, from setting reminders to controlling smart home devices. They have transformed the way we interact with technology and simplified communication with devices.

Artificial intelligence has also played a role in enhancing communication through personalized recommendations. Many online platforms, such as social media and streaming services, utilize AI algorithms to analyze user preferences and provide personalized content suggestions. This has improved user engagement and facilitated communication by connecting users with relevant information and like-minded individuals.

In conclusion, artificial intelligence has had a significant impact on communication. From chatbots and language translation to voice assistants and personalized recommendations, AI technology has revolutionized the way we interact and communicate with each other. It has made communication faster, more efficient, and more accessible, bringing people closer together in an increasingly interconnected world.

The Impact of Artificial Intelligence on Privacy

Artificial intelligence (AI) has had a profound impact on various aspects of our society, and one area that is greatly affected is privacy. With the advancements in AI technology, there are growing concerns about how it can impact our privacy rights.

AI-powered systems have the ability to collect and analyze vast amounts of personal data, ranging from social media activity to online transactions. This presents significant challenges when it comes to protecting our privacy. For instance, AI algorithms can mine and analyze our personal data to generate targeted advertisements, which can result in intrusion into our personal lives.

Additionally, AI systems can be used to monitor and track individuals’ online activities, which raises concerns about surveillance and the erosion of privacy. With AI’s ability to process and interpret large volumes of data, it becomes easier for organizations and governments to gather information about individuals without their knowledge or consent.

Furthermore, AI algorithms can make predictions about individuals’ behaviors and preferences based on their data. While this can be beneficial in some cases, such as providing tailored recommendations, it also raises concerns about the potential misuse of this information. For example, insurance companies could use AI algorithms to assess an individual’s health risks based on their online activity, resulting in potential discrimination or exclusion.

It is crucial to strike a balance between the benefits of AI technology and protecting individuals’ right to privacy. Steps must be taken to ensure that AI systems are designed and implemented in a way that respects and safeguards privacy. This can include implementing strict regulations and guidelines for data collection, storage, and usage.

In conclusion, the impact of artificial intelligence on privacy cannot be ignored. As AI continues to advance, it is essential to address the potential risks and challenges it poses to privacy rights. By taking proactive measures and promoting ethical practices, we can harness the benefits of AI while ensuring that individuals’ privacy is respected and protected.

The Impact of Artificial Intelligence on Security

Artificial intelligence (AI) has had a profound impact on society, and one area where its influence is particularly noticeable is in the field of security. The development and implementation of AI technology have revolutionized the way we approach and manage security threats.

AI-powered security systems have proven to be highly effective in detecting and preventing various types of threats, such as cyber attacks, terrorism, and physical breaches. These systems are capable of analyzing vast amounts of data in real-time, identifying patterns, and recognizing anomalies that may indicate a security risk.

One major advantage of AI in security is its ability to continuously adapt and learn. AI algorithms can quickly analyze new data and update their knowledge base, improving their ability to detect and respond to emerging threats. This dynamic nature allows AI-powered security systems to stay ahead of potential attackers and respond to evolving security challenges.

Furthermore, AI can enhance the efficiency and accuracy of security operations. By automating certain tasks, such as video surveillance monitoring and threat analysis, AI technology can significantly reduce the workload for human security personnel. This frees up resources and enables security teams to focus on more critical tasks, such as responding to incidents and developing proactive security strategies.

However, the increasing reliance on AI in security also raises concerns. The use of AI technology can potentially lead to privacy breaches and unethical surveillance practices. It is crucial to strike a balance between utilizing AI for security purposes and respecting individual privacy rights.

In conclusion, the impact of artificial intelligence on security has been significant. AI-powered systems have revolutionized the way we detect and prevent security threats, enhancing efficiency and accuracy in security operations. However, ethical concerns need to be addressed to ensure that AI is used responsibly and in a way that respects individual rights and privacy.

The Impact of Artificial Intelligence on Economy

Artificial intelligence (AI) is revolutionizing the economy in various ways. Its impact is prevalent across different sectors, leading to both opportunities and challenges.

One of the key benefits of AI in the economy is increased productivity. AI-powered systems and algorithms can perform tasks at a much faster pace and with a higher level of accuracy compared to humans. This efficiency can lead to significant cost savings for businesses and result in increased output and profits.

Moreover, AI has the potential to create new job opportunities. While some jobs may be replaced by automation, AI also leads to the creation of new roles that require specialized skills in managing and maintaining AI systems. This can contribute to economic growth and provide employment opportunities for individuals with the necessary technical expertise.

The impact of AI on the economy is not limited to individual businesses or sectors. It has the potential to transform entire industries. For example, AI-powered technologies can optimize supply chain operations, enhance customer experience, and improve decision-making processes. These advancements can lead to increased competitiveness, improved efficiency, and overall economic growth.

However, the widespread implementation of AI also brings challenges. The displacement of jobs due to automation can result in unemployment and income inequality. It is crucial for policymakers to address these issues and ensure that the benefits of AI are distributed equitably across society.

Additionally, the ethical implications of AI in the economy must be considered. As AI systems continue to advance, it raises questions about privacy, data security, and algorithmic bias. Safeguards and regulations need to be in place to protect individuals’ rights and prevent any potential harm caused by AI applications.

In conclusion, the impact of artificial intelligence on the economy is significant. It offers opportunities for increased productivity, job creation, and industry transformation. However, it also poses challenges such as job displacement and ethical concerns. To fully harness the potential of AI in the economy, policymakers and stakeholders must work together to address these challenges and ensure a balanced and inclusive approach to its implementation.

The Impact of Artificial Intelligence on Entertainment

Artificial intelligence is revolutionizing the entertainment industry, transforming the way we consume and experience various forms of media. With its ability to analyze massive amounts of data, AI has the potential to enhance entertainment in numerous ways.

One area where AI is making a significant impact is in content creation. AI algorithms can generate music, art, and even scripts for movies and TV shows. By analyzing patterns and trends in existing content, AI can create new and original pieces that appeal to different audiences. This not only increases the diversity of entertainment options but also reduces the time and effort required for human creators.

AI also plays a crucial role in enhancing the user experience in the entertainment industry. For example, AI-powered recommendation engines can suggest relevant movies, TV shows, or songs based on individual preferences and viewing habits. This personalized approach ensures that users discover content that aligns with their interests, leading to a more enjoyable and engaging entertainment experience.

In the gaming industry, AI is transforming the way games are developed and played. AI algorithms can create lifelike characters and virtual worlds, providing players with immersive and realistic experiences. Additionally, AI-powered game assistants can adapt to the player’s skill level and offer personalized guidance, making games more accessible and enjoyable for players of all abilities.

Furthermore, AI is revolutionizing the way we consume live events, such as sports or concerts. AI-powered cameras and sensors can capture and analyze data in real-time, providing enhanced viewing experiences for spectators. This includes features like instant replays, personalized camera angles, and in-depth statistics. AI can also generate virtual crowds or even simulate the experience of attending a live event, bringing the excitement of the event to a global audience.

The impact of artificial intelligence on the entertainment industry is undeniable. It is transforming content creation, enhancing the user experience, and revolutionizing the way we consume various forms of media. As AI continues to advance, we can expect even more innovative and immersive entertainment experiences that cater to individual preferences and push the boundaries of creativity.

The Impact of Artificial Intelligence on Human Interaction

In today’s modern world, the rise of artificial intelligence (AI) has had a profound impact on many aspects of society, including human interaction. AI technology has revolutionized the way we communicate and interact with one another, both online and offline.

One of the most noticeable impacts of AI on human interaction is in the realm of communication. AI-powered chatbots and virtual assistants have become increasingly common, allowing people to interact with machines in a more natural and intuitive way. Whether it’s using voice commands to control smart home devices or chatting with a virtual assistant to get information, AI has made it easier to communicate with technology.

AI has also had a significant impact on social media and online communication platforms. Social media algorithms use AI to analyze user data and tailor content to individual preferences, which can shape the way we interact with each other online. This can lead to both positive and negative effects, as AI algorithms may reinforce existing beliefs and create echo chambers, but they can also expose us to new ideas and perspectives.

Furthermore, AI technology has the potential to enhance human interaction by augmenting our capabilities. For example, AI-powered translation tools can break down language barriers and facilitate communication between people who speak different languages. This can foster cross-cultural understanding and enable collaboration on a global scale.

On the other hand, there are concerns about the potential negative impact of AI on human interaction. Some argue that the increasing reliance on AI technology for communication could lead to a decline in human social skills. As people become more accustomed to interacting with machines, they may struggle to engage in authentic face-to-face interactions.

Despite these concerns, it is clear that AI has had a profound impact on human interaction. From enhancing communication to breaking down language barriers, AI technology has transformed the way we interact with one another. It is crucial to continue monitoring and studying the impact of AI on human interaction to ensure we strike a balance between technological advancement and preserving our social connections.

The Role of Artificial Intelligence in Scientific Research

Artificial intelligence (AI) has had a significant impact on society in various fields, and one area where it has shown great promise is scientific research. The use of AI in scientific research has revolutionized the way experiments are conducted, data is analyzed, and conclusions are drawn.

Improving Experimental Design and Data Collection

One of the key contributions of AI in scientific research is its ability to improve experimental design and data collection. By utilizing machine learning algorithms, AI systems can analyze massive amounts of data and identify patterns, allowing researchers to optimize their experimental approaches and make more informed decisions. This not only saves time and resources but also increases the accuracy and reliability of scientific findings.

Enhancing Data Analysis and Interpretation

Another crucial role of AI in scientific research is its ability to enhance data analysis and interpretation. Traditional data analysis methods can be time-consuming and subjective, leading to potential biases. However, AI systems can process vast amounts of data quickly and objectively, revealing hidden relationships, trends, and insights that may be missed by human researchers. This enables scientists to extract meaningful information from complex datasets, leading to more accurate and comprehensive conclusions.

While AI has significant potential in scientific research, it also presents challenges and ethical considerations that need to be addressed. Privacy and security concerns, biases in AI algorithms, ethical implications of AI decision-making, and the impact on human researchers’ roles are some of the critical issues that require scrutiny.

In conclusion, the role of artificial intelligence in scientific research is undeniable. AI has the potential to revolutionize how experiments are designed, data is analyzed, and conclusions are drawn. By improving experimental design and data collection, enhancing data analysis and interpretation, and accelerating scientific discovery, AI can significantly contribute to the advancement of scientific knowledge and its impact on society as a whole.

The Role of Artificial Intelligence in Space Exploration

Artificial intelligence (AI) has had a significant impact on various fields and industries, and space exploration is no exception. With its ability to analyze vast amounts of data and make decisions quickly, AI has revolutionized the way we explore space and gather information about the universe.

One of the primary roles of artificial intelligence in space exploration is in the analysis of data collected by space probes and telescopes. These devices capture enormous amounts of data that can often be overwhelming for human scientists to process. AI algorithms can sift through this data, identifying patterns, and extracting valuable insights that humans may not have noticed.

Additionally, AI plays a crucial role in autonomous navigation and spacecraft control. Spacecraft can be sent to explore distant planets and moons in our solar system, and AI-powered systems can ensure their safe and efficient navigation through unknown terrain. AI algorithms can analyze data from onboard sensors and make real-time decisions to avoid obstacles and hazards.

Benefits of AI in space exploration

• Efficiency: AI systems can process vast amounts of data much faster than humans, allowing for quicker analysis and decision-making.
• Exploration of inhospitable environments: AI-powered robots can be sent to explore extreme environments, such as the surface of Mars or the icy moons of Jupiter, where it would be challenging for humans to survive.
• Cost reduction: By using AI to automate certain tasks, space exploration missions can become more cost-effective and efficient.

The impact of artificial intelligence on space exploration is still in its early stages, but its potential is vast. As AI technology continues to advance, we can expect to see even more significant contributions to our understanding of the universe and our ability to explore it.

The Role of Artificial Intelligence in Environmental Conservation

Artificial intelligence (AI) has the potential to revolutionize various aspects of society, and environmental conservation is no exception. With the growing concern about climate change and the need to preserve the planet’s resources, AI can play a crucial role in helping us address these challenges.

Monitoring and Predicting Environmental Changes

One of the key benefits of AI in environmental conservation is its ability to monitor and predict environmental changes. Through the use of sensors and data analysis, AI systems can gather and analyze vast amounts of information about the environment, including temperature, air quality, and water levels.

This data can then be used to identify patterns and trends, allowing scientists to make predictions about future changes. For example, AI can help predict the spread of wildfires or the impact of deforestation in certain areas. By understanding these threats in advance, we can take proactive measures to protect our natural resources.

Optimizing Resource Management

Another important role of AI in environmental conservation is optimizing resource management. By using AI algorithms, we can efficiently allocate resources such as energy, water, and waste management.

AI can analyze data from various sources, such as smart meters and sensors, to understand patterns of resource usage. This information can then be used to develop strategies for more sustainable resource management, reducing waste and improving efficiency.

For example, AI can help optimize energy consumption in buildings by analyzing data from smart thermostats and occupancy sensors. It can identify usage patterns and make adjustments to reduce energy waste, saving both money and environmental resources.

Supporting Conservation Efforts

AI can also support conservation efforts through various applications. One example is the use of AI-powered drones and satellite imagery to monitor and protect endangered species.

By analyzing images and data collected by these technologies, AI algorithms can identify and track animals, detect illegal activities such as poaching, and even help with habitat restoration. This technology can greatly enhance the effectiveness and efficiency of conservation efforts, allowing us to better protect our biodiversity.

In conclusion, artificial intelligence has a significant role to play in environmental conservation. From monitoring and predicting environmental changes to optimizing resource management and supporting conservation efforts, AI can provide valuable insights and help us make more informed decisions. By harnessing the power of AI, we can work towards a more sustainable and environmentally conscious society.

The Role of Artificial Intelligence in Manufacturing

Artificial intelligence (AI) has had a profound impact on society in various fields, and manufacturing is no exception. In this essay, we will explore the role of AI in manufacturing and how it has revolutionized the industry.

AI has transformed the manufacturing process by introducing automation and machine learning techniques. With AI, machines can perform tasks that were previously done by humans, leading to increased efficiency and productivity. This has allowed manufacturers to streamline their operations and produce goods at a faster rate.

One of the key benefits of AI in manufacturing is its ability to analyze large amounts of data. Through machine learning algorithms, AI systems can collect and process data from various sources, such as sensors and machines, to identify patterns and make informed decisions. This allows manufacturers to optimize their production processes and minimize errors.

Furthermore, AI can improve product quality and reduce defects. By analyzing data in real-time, AI systems can detect anomalies and deviations from the norm, allowing manufacturers to identify and address issues before they escalate. This not only saves time and costs but also ensures that consumers receive high-quality products.

Additionally, AI has enabled the development of predictive maintenance systems. By analyzing data from machines and equipment, AI can anticipate and prevent failures before they occur. This proactive approach minimizes downtime, reduces maintenance costs, and extends the lifespan of machinery.

Overall, the role of AI in manufacturing is transformative. It empowers manufacturers to optimize their processes, improve product quality, and reduce costs. However, it is important to note that AI is not a replacement for humans in the manufacturing industry. Instead, it complements human skills and expertise, allowing workers to focus on more complex tasks while AI handles repetitive and mundane tasks.

In conclusion, artificial intelligence has had a significant impact on the manufacturing industry. It has revolutionized processes, improved product quality, and increased productivity. As AI continues to advance, we can expect even more transformative changes in the manufacturing sector.

The Role of Artificial Intelligence in Agriculture

Artificial intelligence has had a profound impact on society in various fields, and agriculture is no exception. With the advancements in technology, AI has the potential to revolutionize the agricultural industry, making it more efficient, sustainable, and productive.

One of the key areas where AI can play a significant role in agriculture is in crop management. AI-powered systems can analyze vast amounts of data, such as weather patterns, soil conditions, and crop health, to provide farmers with valuable insights. This allows farmers to make more informed decisions on irrigation, fertilization, and pest control, leading to optimal crop yields and reduced resource waste.

Moreover, AI can also aid in the early detection and prevention of crop diseases. By using machine learning algorithms, AI systems can identify patterns and anomalies in plant health, indicating the presence of diseases or pests. This enables farmers to take timely action, prevent the spread of diseases, and minimize crop losses.

Another area where AI can contribute to agriculture is in the realm of precision farming. By combining AI with other technologies like drones and sensors, farmers can gather precise and real-time data about their crops and fields. This data can then be used to create detailed maps, monitor crop growth, and optimize resource allocation. Whether it’s optimizing water usage or determining the ideal time for harvesting, AI can help farmers make data-driven decisions that maximize productivity while minimizing environmental impact.

Furthermore, AI can enhance livestock management. With AI-powered systems, farmers can monitor the health and behavior of their livestock, detect diseases or anomalies, and provide personalized care. This not only improves animal welfare but also increases the efficiency of livestock production.

In conclusion, artificial intelligence has a crucial role to play in the agricultural sector. From crop management to livestock monitoring, AI can bring numerous benefits to farmers, leading to increased productivity, sustainability, and overall growth. As AI continues to advance, we can expect further innovations and improvements in the integration of AI in agriculture, shaping the future of food production.

The Role of Artificial Intelligence in Finance

Artificial intelligence (AI) has had a significant impact on society, revolutionizing various industries, and finance is no exception. In this essay, we will explore the role of AI in the financial sector and its implications.

The use of AI has transformed numerous aspects of finance, from trading and investment to risk management and fraud detection. One of the key benefits of AI in finance is its ability to process vast amounts of data in real-time. This enables more accurate predictions and informed decision-making, giving financial institutions a competitive edge.

AI-powered algorithms have become vital tools for traders and investors. These algorithms analyze market trends, historical data, and other factors to identify patterns and make investment recommendations. By leveraging AI, financial professionals can make more informed decisions and optimize their portfolios.

Furthermore, AI plays a crucial role in risk management. Traditional risk models often fall short in assessing complex and evolving risks, making it challenging to mitigate them effectively. AI, with its machine learning capabilities, can enhance risk assessment by analyzing a wide range of variables and identifying potential threats. This helps financial institutions proactively manage risks and minimize losses.

Another area where AI has made significant strides in finance is fraud detection. With the increasing sophistication of fraudulent activities, traditional rule-based systems struggle to keep up. AI, on the other hand, can detect anomalies and unusual patterns by leveraging machine learning algorithms that constantly learn and adapt. This enables faster and more accurate detection of fraudulent transactions, protecting both financial institutions and their customers.

In conclusion, AI has had a profound impact on the finance industry and has revolutionized various aspects of it. The ability to process large amounts of data, make informed decisions, and detect risks and frauds more effectively has made AI an invaluable tool. As technology continues to advance, we can expect AI to play an even greater role in shaping the future of finance.

The Role of Artificial Intelligence in Customer Service

Artificial intelligence has had a profound impact on various industries, and one area where its influence is increasingly being felt is customer service. AI technology is transforming how businesses interact with their customers, providing enhanced communication and support.

One of the main benefits of AI in customer service is its ability to provide instant and personalized responses to customer inquiries. Through the use of chatbots and virtual assistants, businesses can now offer round-the-clock support, ensuring that customers receive the assistance they need, no matter the time of day.

Furthermore, AI-powered customer service can analyze vast amounts of data to gain insights into customer preferences and behavior. This information can then be used to tailor interactions and improve customer experiences. By understanding customer needs better, businesses can provide more relevant and targeted solutions, leading to increased customer satisfaction and loyalty.

Another crucial role of AI in customer service is its ability to automate repetitive tasks and processes. AI-powered systems can handle routine tasks such as order tracking, appointment scheduling, and basic troubleshooting, freeing up human agents to focus on more complex issues. This results in increased efficiency and productivity, as well as faster response times.

However, it’s important to note that AI should not replace human interaction entirely. While AI can handle routine tasks effectively, there are situations where human empathy and judgment are essential. Building a balance between AI and human involvement is crucial to ensure the best possible customer service experience.

In conclusion, artificial intelligence is revolutionizing customer service by providing instant and personalized support, analyzing customer data for improved experiences, and automating repetitive tasks. While AI offers numerous benefits, it is vital to strike a balance between AI and human interaction to deliver exceptional customer service in the digital age.

The Role of Artificial Intelligence in Gaming

Gaming has been greatly impacted by the advancements in artificial intelligence (AI). AI has revolutionized the way games are created, played, and experienced by both developers and players.

One of the key roles that AI plays in gaming is in creating realistic and challenging virtual opponents. AI algorithms can be programmed to assess player actions and adjust the difficulty level accordingly. This allows for a more immersive and engaging gaming experience, as players can compete against opponents that adapt to their skills and strategies.

Moreover, AI is also used in game design to create intelligent non-player characters (NPCs) that can interact with players in a more natural and realistic manner. These NPCs can simulate human-like behavior and responses, making the game world feel more alive and dynamic.

Another important role of AI in gaming is in improving game mechanics and gameplay. AI algorithms can analyze player data and preferences to provide personalized recommendations and suggestions. This helps players discover new games, unlock achievements, and improve their overall gaming experience.

Furthermore, AI has also been used in game testing and bug detection. AI algorithms can simulate various scenarios and interactions to identify potential glitches and bugs. This improves the overall quality and stability of games before their release.

In conclusion, artificial intelligence has had a profound impact on the gaming industry. It has enhanced the realism, challenge, and overall experience of games. The role of AI in gaming is ever-evolving, and it will continue to shape the future of the gaming industry.

The Future of Artificial Intelligence

Artificial intelligence (AI) has already made a significant impact on society, and its role is only expected to grow in the future. As advancements in technology continue to push boundaries, the potential applications of AI are expanding, potentially transforming various industries and aspects of our daily lives.

One of the most prominent areas where AI is expected to make a difference is in autonomous vehicles. Self-driving cars have already become a reality, and AI is set to play a crucial role in improving their capabilities further. With AI-powered sensors and algorithms, autonomous vehicles can navigate complex road conditions, reduce traffic congestion, and even enhance road safety.

Another domain that is likely to benefit from AI is healthcare. Intelligent machines can analyze vast amounts of medical data and assist doctors in making accurate diagnoses. This can lead to faster identification of diseases, more effective treatment plans, and ultimately, better patient outcomes. AI can also aid in the development of new drugs and therapies by analyzing genetic information and identifying potential targets for treatment.

In addition to healthcare and transportation, AI has the potential to revolutionize sectors such as finance, manufacturing, and agriculture. AI algorithms can analyze market data, identify trends, and make accurate predictions, enabling financial institutions to make informed investment decisions. In manufacturing, AI-powered robots can perform repetitive tasks with precision and efficiency, improving productivity and reducing costs. AI can also optimize crop production by analyzing variables such as weather conditions, soil quality, and crop health, leading to increased yields and more sustainable farming practices.

However, with the increasing integration of AI into various aspects of society, ethical considerations become crucial. As AI becomes more advanced and autonomous, questions arise about the implications of AI decision-making processes and potential biases. It is important to ensure that AI systems are designed and regulated in a way that prioritizes fairness, transparency, and accountability.

In conclusion, the future of artificial intelligence holds immense potential for transforming society in numerous ways. From autonomous vehicles and healthcare to finance and agriculture, AI is poised to revolutionize various sectors and improve our lives. However, it is essential to address ethical concerns and ensure responsible development and deployment of AI technology to maximize its positive impact on society.

The Potential Risks of Artificial Intelligence

As the impact of artificial intelligence on society continues to grow, it is important to consider the potential risks associated with this rapidly advancing technology. While intelligence can be a powerful tool for improving society, artificial intelligence poses unique challenges and dangers that must be addressed.

Unemployment and Job Displacement

One of the major concerns surrounding artificial intelligence is the potential for widespread unemployment and job displacement. As AI technology advances, machines and algorithms are becoming increasingly capable of performing tasks that were previously done by humans. This could lead to significant job losses across various industries, particularly those that rely heavily on manual labor or repetitive tasks.

Additionally, as AI systems become more sophisticated, there is a possibility that they could replace jobs that require higher levels of skill and expertise. This could result in a significant shift in the job market and create challenges for workers who are unable to adapt to these changes.

Ethical Concerns

Another potential risk of artificial intelligence is the ethical concerns that arise from its use. AI systems are designed to make decisions and take actions based on data and algorithms, but they may not always make ethical choices. This raises questions about the impact of AI on issues such as privacy, bias, and discrimination.

For example, AI algorithms may inadvertently discriminate against certain groups of people if the data used to train them is biased. This could lead to unfair outcomes in areas such as hiring, lending, and law enforcement. It is essential to address these ethical concerns and ensure that AI systems are developed and used in a responsible and equitable manner.

In conclusion, while artificial intelligence has the potential to greatly benefit society, it is important to carefully consider and address the potential risks associated with its use. Unemployment and job displacement, as well as ethical concerns, are significant challenges that must be navigated to ensure the responsible and equitable development of AI.

The Importance of Ethical Guidelines for Artificial Intelligence

As artificial intelligence (AI) continues to advance at an unprecedented pace, its impact on society becomes increasingly profound. AI has the potential to transform various industries, improve efficiency, and enhance our overall quality of life. However, with this power comes great responsibility. It is crucial to establish ethical guidelines to ensure that AI is developed and deployed in a responsible and beneficial manner.

Ethics in AI Development

Ethics play a vital role in the development of AI technology. It is essential for developers to consider the potential impact that their creations may have on society. This involves addressing questions of privacy, security, and bias. AI systems should be designed to respect fundamental human rights and ensure that they do not discriminate against certain groups of people. By setting ethical standards, we can prevent the misuse and abuse of AI technology.

The Impact on Society

Without ethical guidelines, artificial intelligence can have unintended consequences on society. For example, if AI algorithms are biased, they may perpetuate social inequalities or reinforce stereotypes. Additionally, AI systems that invade privacy or compromise security can erode trust in technology, hindering its adoption and acceptance by the public. Therefore, by implementing ethical guidelines, we can help safeguard against these negative societal impacts.

The Risks of AI without Ethical Guidelines

Artificial intelligence has the potential to revolutionize society, but it also carries risks. Without ethical guidelines in place, AI can be misused for nefarious purposes, such as surveillance and manipulation. It is crucial to establish clear boundaries and regulations to ensure that AI is used for the benefit of humanity and not to harm individuals or society as a whole.

In conclusion , the importance of ethical guidelines for artificial intelligence cannot be overstated. These guidelines serve as a compass to steer the development and deployment of AI technology in the right direction. By considering the potential impact on society and setting ethical standards, we can harness the power of AI for the betterment of humanity and create a future that is both technologically advanced and ethically responsible.

The Need for Regulation and Governance of Artificial Intelligence

The rapid development of artificial intelligence (AI) has had a profound impact on society. With the increasing deployment of intelligent systems in various domains, it is essential to establish effective regulations and governance mechanisms to ensure that AI is used responsibly and ethically.

Safeguarding Privacy and Data Security

One of the key concerns with the growing use of AI is the potential invasion of privacy and compromise of data security. Intelligent systems are capable of analyzing vast amounts of personal data, raising concerns about the misuse and unauthorized access to sensitive information. To address this, there is a need for regulations that enforce stringent data protection measures and ensure transparency in AI algorithms and data usage.

Ethical Decision-Making and Bias Mitigation

AI systems are designed to make autonomous decisions based on data and algorithms. However, the biases embedded in these systems can result in discriminatory outcomes. Regulations must be put in place to ensure that AI systems are developed and trained in a way that mitigates bias and promotes fair and ethical decision-making. This includes diverse representation in the development of AI technologies and the establishment of clear guidelines on what is considered acceptable behavior for AI systems.

Accountability and Liability

As AI systems become increasingly autonomous, it becomes crucial to determine who should be held accountable in the event of a malfunction or failure. Clear regulations need to be established to define liability in AI-related incidents and ensure that there are mechanisms in place to address any potential harm caused by AI systems. This includes the establishment of standards for testing and certification of AI systems to ensure their reliability and safety.

In conclusion, the impact of artificial intelligence on society necessitates the establishment of regulations and governance mechanisms. By addressing concerns related to privacy, bias, and accountability, we can harness the full potential of AI while ensuring that it benefits society as a whole.

The Role of Artificial Intelligence in Shaping Society’s Future

Artificial intelligence (AI) has had a profound impact on society, and its role in shaping the future cannot be understated. As technology continues to advance at an unprecedented rate, AI is becoming increasingly integrated into various aspects of our lives, from healthcare to transportation to entertainment.

One of the key impacts of AI is its ability to automate tasks that were once performed by humans, enabling us to save time and resources. For example, AI-powered chatbots have revolutionized customer service by providing prompt and efficient responses to inquiries, reducing the need for human intervention. In the healthcare industry, AI algorithms are being developed to assist doctors in diagnosing diseases and recommending treatment options, improving both accuracy and speed.

Furthermore, AI has the potential to address complex societal challenges. For instance, in the field of environmental sustainability, AI technologies can be used to optimize energy consumption, reduce waste, and develop renewable energy sources. By analyzing large amounts of data and identifying patterns, AI can help us make more informed decisions and take proactive measures to mitigate the impact of climate change.

In addition, AI has the ability to enhance our educational systems. Intelligent tutoring systems can adapt to individual learning styles and provide personalized instruction, improving student engagement and performance. AI-powered language translation tools have also facilitated global communication, breaking down language barriers and fostering cross-cultural understanding.

However, it is important to recognize that AI is not without its challenges. There are concerns regarding privacy and security, as AI relies heavily on data collection and analysis. Ethical considerations must also be taken into account, as AI systems can perpetuate biases and discrimination if not properly designed and monitored.

In conclusion, artificial intelligence plays a significant role in shaping society’s future. Its impact can be seen in various fields, from automation to sustainability to education. While there are challenges that need to be addressed, AI has the potential to revolutionize our lives and create a more efficient and equitable society.

Questions and answers

What is the impact of artificial intelligence on society.

The impact of artificial intelligence on society is significant and far-reaching. It is transforming various sectors, including healthcare, education, finance, and transportation.

How is artificial intelligence revolutionizing healthcare?

Artificial intelligence in healthcare is revolutionizing the way diseases are diagnosed and treated. It is helping doctors in making accurate diagnoses, predicting outcomes, and assisting in surgeries.

What are the ethical concerns surrounding artificial intelligence?

There are several ethical concerns surrounding artificial intelligence, such as the potential loss of jobs, bias in algorithms, invasion of privacy, and the possibility of autonomous weapons.

How can artificial intelligence improve productivity in the workplace?

Artificial intelligence can improve productivity in the workplace by automating repetitive tasks, analyzing large amounts of data quickly and accurately, and providing personalized recommendations and insights.

What are the potential risks of artificial intelligence?

The potential risks of artificial intelligence include job displacement, widening economic inequalities, security threats, loss of human control, and the potential for AI systems to be hacked or manipulated.

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Cohere: Bridging Language and AI for a Smarter Future

Microsoft office 365 ai. microsoft copilot, understanding the distinctions between artificial intelligence and human intelligence, exploring the impact of artificial intelligence on discrimination in insurance pricing and underwriting.

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The Week in Tech: A.I.’s Threat to White-Collar Jobs

Some workers may be more exposed to artificial intelligence than previously thought. But worry more about automation’s threat to less skilled employees.

By Jamie Condliffe

Each week, we review the week’s news , offering analysis about the most important developments in the tech industry.

Hi, I’m Jamie Condliffe. Greetings from London. For one last time before I leave The New York Times, here’s a look at the week’s tech news:

The story usually goes like this: Automation is going to take our jobs.

But the reality is far more nuanced, and debate rages about which jobs will be automated, at what scale and where. For the most part, one thing is agreed on: Blue-collar workers who perform repetitive work are most exposed.

That might not be quite right, though. A study published by the Brookings Institution on Wednesday looks at the degree to which professions are exposed to A.I. by comparing job descriptions with patent descriptions of new A.I. technologies, a method developed by the Stanford researcher Michael Webb. It found that A.I. will be “a significant factor in the future work lives of relatively well-paid managers, supervisors and analysts,” including those in relatively technical roles.

Perhaps the most surprising finding: Holders of bachelor’s degrees would be exposed to A.I. over five times more than workers with only a high school degree.

“Lots of math, science, technology and business roles involve, say, operating a power plant to maximize energy efficiency, or running an ad campaign to minimize cost per click,” explained Mark Muro, a senior fellow at Brookings and one of the study’s authors. “And these are exactly the things that A.I. is best at.”

Previously, similar studies lumped together robotics and A.I. But when they are picked apart, it makes sense that A.I. — which is about planning, perceiving and so on — would hit white-collar roles.

Still, workers needn’t panic. Carl Benedikt Frey, an economist at Oxford University who specializes in technology and employment, said A.I. was “more likely to complement people in those jobs rather than replacing them.” And Mr. Muro points out that “these workers are frequently the ones that companies have already invested in” and are likely to have been consulted about their futures.

Mr. Muro added: “I for one am a bit less concerned about the white-collar folks than the less educated ones stuck in dead-end service work or the gig economy.”

TikTok’s Reboot

I recently explained how TikTok is in trouble because the red-hot video app, which is owned by the Chinese company ByteDance, is under scrutiny from lawmakers in the United States. At the heart of this is a big, untested argument that Chinese laws could force TikTok, in theory, to send data to the Chinese government.

In an interview with The Times, TikTok’s chief executive, Alex Zhu, tried to assuage Washington’s fears :

No, TikTok does not censor videos that displease China, he said. And no, it does not share user data with China, or even with its Beijing-based parent company.

Mr. Zhu said he’d personally reject an appeal for data even if it came from President Xi Jinping.

And it’s reportedly trying other stuff, too. The Wall Street Journal reported that TikTok executives had discussed “rebranding it in the United States” and “expanding operations in Southeast Asia, possibly Singapore — which would allow executives to distance the video-sharing app from China.”

But it’s unclear how far such assurances can go.

“There doesn’t seem to be a way to assuage regulators in the U.S. without removing that ownership issue,” Adam Segal, the director of the digital and cyberspace policy program at the Council on Foreign Relations, told me.

In the Times interview, Mr. Zhu said a sale of TikTok’s American operations hadn’t been discussed. But he didn’t rule out the possibility of ByteDance’s reorganizing it as a separate company with a new board. It might not have much choice.

Disconnected Iran

Iran has demonstrated that it’s willing to take its citizens offline — and, perhaps more worryingly, that it’s able to do so without plunging domestic infrastructure into chaos.

The Iranian government recently imposed an almost complete nationwide internet blackout that lasted for almost five days . It came after protests erupted across the country after the government said it would raise gasoline prices . Amnesty International estimated that as many as 106 people were killed.

Mahsa Alimardani, a researcher at the Oxford Internet Institute, explained to me in an email that the Iranian government was trying to limit the spread of evidence of state violence.

“The deaths and the ruthless images of authorities raining bullets on protesters that are being disseminated are not the images they want dominating their narrative,” she said.

Blocking internet traffic and, by extension, social media certainly cuts information flows. But there’s little evidence that internet blackouts undermine protests. A 2018 report by Human Rights Watch found “no substantive data or evidence to prove that internet shutdowns can scale down violence.” That Iran’s blackout persisted, Ms. Alimardani said, was a strong indication that it had done little to calm the protests.

But the shutdown revealed one success for Iran’s government: its National Information Network, a domestic, highly censored digital infrastructure. That infrastructure enabled the nation’s critical services, such as finance and health care, to largely operate normally, demonstrating that the country is well equipped to shut down the public internet.

“They are proving they can and will cut people off if they question authorities again,” Ms. Alimardani said.

Google’s Staff Clash

“Don’t be evil,” it once said. But Google’s internal mantra now looks like it could be more like: “Don’t question the management.”

It has come to light that Google has ended its biweekly all-hands meetings . The decision was made just days after Google employees protested the interrogation of two colleagues by the company’s investigations team, according to CNBC. And it all comes on the back of a staff protest last year over the company’s handling of sexual harassment complaints, vibrant discussions on internal memo boards about company policies and pushback from some workers about Google’s work in China and with the United States military.

Then, this past week, it transpired that Google had hired an anti-union consulting firm to advise its management as it deals with worker unrest.

It’s still too early to tell how this will shake out at Google. But what’s clear is that the company’s traditional embrace of transparency and flexibility for workers is straining as more employees question its motives and actions.

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What caused Uber’s autonomous car crash in 2018? The main reason, according to the National Transportation Safety Board, was the safety driver’s failure to monitor the road .

President Trump visited a Texas factory that builds Apple computers and made a series of inaccurate comments . Apple’s chief executive, Timothy D. Cook, didn’t correct him — perhaps thinking that it might make it harder for the company to get a tariff waiver?

The Commerce Department extended Huawei’s reprieve so that it can still buy goods from American companies for another 90 days , and approved “ several ” individual licenses for American companies to do business with Huawei, while it remains on a trade blacklist.

The Federal Trade Commission said it was pursuing “multiple” antitrust investigations into major digital platforms alongside its inquiry into Facebook.

Expect Europe to get even tougher on Big Tech. In her second term as the head of the European Commission’s antitrust division, Margrethe Vestager plans to double down .

Google’s new cloud gaming platform, Stadia, went on sale. It’s supposed to replace consoles, but the verdict of our reviewer was: Don’t bother .

Disney Plus was hacked , according to an investigation by ZDNet , and leaked user credentials apparently changed hands for as little as $3 each.

T-Mobile’s John Legere will step down as chief executive early next year. It’s unlikely that his successor, Mike Sievert, can possibly wear as much magenta.

Deep fakes: Believe at your own risk. A.I. engineers create ultrarealistic videos that will have you questioning reality on “The Weekly,” our TV show Sunday on FX and streaming Monday on Hulu.

The Bits newsletter will take a break next week for the Thanksgiving holiday in the United States. See you in December.

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The Rise of TikTok

News and Analysis

Court records, mistakenly made public, reveal a complex origin story for ByteDance , the Chinese owner of TikTok, and the role played by the firm of Republican megadonor Jeff Yass .

The House made another push to force through legislation that would require the sale of TikTok by its Chinese owner or ban the app in the United States by packaging the measure with aid to Ukraine and Israel .

By targeting TikTok, the United States may undermine its decades-long efforts to promote an open internet , and digital rights advocates are worried that other countries could follow suit.

“Being labeled a “yapper” on TikTok isn’t necessarily a compliment, but on a platform built on talk, it isn’t an insult either .

“Who TF Did I Marry?!?,” the TikTok user Reesa Teesa’s account of her relationship with her ex-husband, is a story for grown-ups  in their midlife crisis era.

Return fraud is a rampant problem  for both shoppers and retailers — and the mishaps often make for viral videos on TikTok.

The Pink Stuff, a home cleaning paste, went from total obscurity to viral sensation — and Walmart staple — thanks to one “cleanfluencer” and her legion of fans .

Why Artificial Intelligence Is Not a Threat to Jobs

Artificial intelligence can learn how to perform routine tasks by looking at thousands of relevant examples. But it still needs human supervision.

Machines taking people’s jobs is already a cliché. Although we’ve been hearing this idea for decades now, but if we look around, there is no immediate threat. In fact, there is no threat at all, since we are just talking about another step of the technological revolution. Just like computers did not leave people out of their jobs in the ‘80s and ‘90s, AI will have a similar impact.

Forbes estimates Opens a new window that while 72% of Americans are worried about losing their jobs to AI, such concerns have no factual backing. The World Economic Forum says Opens a new window that 75 million jobs will vanish by 2022, but 133 million new positions will replace these. In fact, with the current rate of development, AI is not by far a competitor but at most a junior assistant.

Job vs.Tasks

To understand that, we need to think about the difference between a job and a task. In Henry Ford’s times, most jobs consisted of a single function or at most a few tasks bundled together. Now, these have already disappeared due to automation. Most positions are based more on thinking, reasoning, making logical connections, and using such skills as communication. Each job position consists of hundreds of interconnected tasks, daily.

AI can indeed be trained to perform repetitive tasks flawlessly if given enough (anything between 1,000 and 20, 000) good examples.

You are already experiencing this in Gmail’s predictive text. It can learn a lot more than simple sentences. However, it is highly unlikely it could replace a trustworthy office assistant in drafting corporate emails. It is more a matter of the assistant using predictive writing to finish this task faster and attend to other things, like travel planning or conference room setup.

Jobs to Be Revisited, But Human Skills Prevail

As described in the previous example, AI can take care of some of the most tedious tasks. This will call for a rethinking of most job flows, but it will not make them obsolete. Ii will also mean a significant change in the necessary training for specific jobs. The role of the humans will shift from performing the task to supervising the machine.

Right now, there are few jobs which can be completely wiped out due to AI. That happens because in every position there is a feedback loop. Some tasks are not fitted for machine learning. Everything which is related to people’s skills, judgment, and ability to combine information to create something new is beyond the current capacities of AI.

Automation will most likely speed up some parts of the jobs which are already considered tedious and time-consuming. It is a matter of giving employees the time back to be more human. This will likely result in people becoming more focused and creative.

Supervised Learning & Human Intervention

Before AI can be safely introduced in a workplace and become part of the natural workflow, it needs to be trained. The transition period in any company looking at these solutions will include a learning curve. Employees will need to learn the operating way of the AI and correct it as they would do with an intern.

When the system learns more, it will make fewer mistakes. Yet over time, it might even be necessary to re-label some things to help the software perform accurately.

Even after the “internship” period is over, the employee, not the machine, will still be held accountable for the results. The AI is just another tool, even if a highly impressive one. It will be more a matter of cooperation than replacement.

Of course, since AI saves a considerable number of hours, some people’s jobs will be at risk. When the employee just needs to supervise and correct the machine, far fewer human working hours are necessary. Yet, most companies will find new ways to use the workforce. There will be a consistent shift from low-skill to high-skill jobs.

Also Read:  3 Ways Artificial Intelligence (AI) will Transform Recruitment Opens a new window

Future Uses of AI

Coming back to the example with the office assistant, let’s imagine some of the tasks include documenting travel expenses. This means that information retrieved from invoices and tickets would need to be manually entered into some accounting platform. This is where AI can speed up the process through OCR. With AI’s help, the assistant can just photograph the travel documents, and the software will automatically identify the amounts and input them into the accounting platform. Of course, the assistant would need to take one final look and check the results.

The healthcare sector provides another example. Some radiology and oncology departments already use AI to augment doctors’ skills instead of replacing them. Dr. Tufia Haddad, an oncology expert, reports that she spends about two hours documenting each patient’s case. She hopes that AI will help her focus more on the patients’ needs and less on the bureaucracy. The perspective also includes the opportunity to build large, well-indexed repositories of information. However, these changes are met with resistance by the medical staff so far.

Which Jobs Will Not Be Replaced by AI

Even if AI can create art on its own, it is still tributary to what it has learned from countless examples provided by humans. The jobs which are safe from the “AI attack” are those focused on human interaction, value, and creativity.

Even if an AI system can self-teach some things, all jobs related to Big Data, Data Mining, and AI will still be on the rise. The medical sector is also safe, as we will still need physicians, nurses, and dentists: the AI is not capable enough to trust it with our lives.

Writers, editors, and graphic designers are also safe Opens a new window , while proofreaders should already think about new career options.

The overarching takeaway is that AI is a natural evolution of information technologies, and we are just witnessing another chapter in the technological revolution. It is a matter of one door closing, while many others will be opening.

Also Read:  Can Artificial Intelligence Eliminate Bias in Hiring? Opens a new window

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Essay on Artificial Intelligence as a Threat in the Society

Introduction

Artificial Intelligence is defined as “the scientific knowledge of the mechanisms that underlie cognition and intelligent behavior and its integration in machines,” according to the Association for the Advancement of Artificial Intelligence. For the past few decades, several predictions were made based on the high incoming of Artificial Intelligence (AI). The transition and its effects on most aspects of the society of businesses and everyday life. It is also essential to note that adequately anticipating the impact of the AI revolution has its implications since AI- automated machines might be our “final invention,” putting an end to human supremacy (Makridakis, 2017, p. 55). Without a doubt, artificial intelligence has a high potential, as both its technology and automation will most likely achieve highly productive and sustainable economic growth. Within the next two decades, its high human intellectual ability poses a severe threat to the workforce market that is initially under human labor. For the first time, it raises concerns about the end of human superiority. While AI can boost the economic growth rate, it also faces significant risks such as employment market fragmentation, increasing inequality, underemployment, and new undesirable industrial structures. EU policy must establish the circumstances for AI’s potential to thrive while also carefully examining how to manage the threats it entails.

Challenges of Artificial Intelligence on the Society

The study re-examines assumptions made about AI’s effects on jobs, inequality, and production, as well as general economic growth. For two reasons, we do so. A few theoretical economic frameworks include AI, and almost none that take demand-side restrictions into account. The second point is that expectations of AI producing enormous job losses and quicker economic and GDP growth conflict with reality: in the developed nations, unemployment is at crisis levels. Income and output growth, on the other hand, is stagnant, and disparities are rising. In the light of accelerating AI progress, this model is a guide to provide a theoretical justification. Jobs aren’t the only thing that might be affected. Economic growth and income stability are certain to be impacted as well. According to (Frey et al., 2017, p.268), the influence of emerging technologies such as AI is subject to an ‘execution lag.’ As AI adoption proceeds, ‘high productivity rate will also be increasing dramatically as an ever-increasing rate of unemployment cascades through the economy,’ according to the report (Nordhaus, 2015, p.2).

Impact on Jobs

Several widely cited original reports suggested that automation of occupations and functions will eventually displace a significant portion of the human labor force. They are anticipated that up to 47% of US occupations might be automated in ten to twenty years in a widely regarded paper (Syverson, 2017, p. 171). This might be even higher in a similar study case of the EU, with up to 54% of occupations being computerized in 10 to 20 years, using a similar methodology. Regular tasks can readily be automated, making specific roles obsolete over time. Customer service/call center operations, document categorization, and recovery, and content moderation, for example, are increasingly relying on increased automation rather than human labor. People are being replaced by automated robotic systems which can effectively move around the area, locate and move stuff, and carry out complex assembling operations. As frightening as these projections may be, recent theoretical and empirical research suggests that the effect of AI-automated jobs lost may be significantly exaggerated. New theoretical revisions, such as those by Bessen (2018), reveal that, based on the flexibility of demand for the product in issue, there is a reasonable probability that jobs might rise as a result of the AI-automation.

Impact on Inequality

Since Artificial intelligence has a diverse influence on various jobs and workers, it may negatively affect earnings. In research in six European nations, two significant channels have been identified through which AI-automation will deteriorate wealth inequality: The benefits, for example, may only flow to a small number of firms due to increased ‘invention costs’ from AI, while the other is when Artificial Intelligence is moving relative labor supply, which in turn affects comparable salaries (Nordhaus, 2015, p. 18). Ideally, as more manual work is substituted by Ai technologies, productivity rises and general earnings growth will be, and the more significant the gap between rich and poor will widen.

There are legitimate concerns that AI would worsen present trends of changing the national income distribution away from labor, resulting in more disparity and wealth concentration in “superstar” enterprises and industries. Another source of rising income inequality may be our inability to categorize revenue at the conventional point—income or exchange— as a smaller percentage of the market is registered, taxed, and dispersed. Instead of taxing income, one apparent alternative would be to tax the wealthy directly, such as a company’s market value (Makridakis, 2017, p. 55). The information era may make tracking income equality simpler than previously, making this technique more feasible than it has been in the past, especially given the difficulties of tracking income.

Impact on Privacy and Autonomy

When evaluating the impact of Artificial Intelligence on behavioral patterns, we’ve finally arrived at a point where ICT has a distinct effect. Domestic surveillance has a long history, and it has been linked to anything from skewed employment prospects to pogroms. However, information and communication technology (ICT) now allows us to preserve permanent records on everyone who generates stored data, such as invoices, bank statements, digital gadgets, or credit history, not to forget any open publishing or social network usage. Our civilization is being transformed by storing and accessing digital information and by the fact that all this data may be accessed using a pattern detection algorithm. By complexity, we have lost the basic presumption of being anonymous. We are all famous to some extent now: random people can identify any of us, whether through facial – recognition or information extraction of shopping or social networks activities (Reed et al., 2016, p.1065). Artificial Intelligence has facilitated robotic cognitive abilities in speech transcription, emotion recognition from audiovisual recordings, and written or video forgery. This technique enables forging by mixing a model of various people’s handwriting or their utterances with a text flow to get a “prediction” or interpretation of how the person would probably write or pronounce that text.

Artificial intelligence has been transforming societies faster than we understand, yet it isn’t as original or distinctive in human experience as we are frequently made to believe corporations and governments, telecommunications, and natural gas, among other artifactual entities, have previously expanded our powers, changed our economies, and upset our social co-existence, but not universally, for the better. However, we must keep in mind that, above and beyond the economical and governance issues, AI enhances and improves what makes us unique in the first place, especially our problem-solving ability. Considering the ongoing worldwide challenges including security, privacy and development, such improvements are anticipated to remain to be beneficial. Because AI lacks a soul, its philosophy should be transcendental to compensate for its incapacity to sympathize. Artificial intelligence (AI) is a fact of life. We must remember what AI inventor Joseph Weizenbaum said: “We cannot let machines make critical decisions for humanity since AI will never have human attributes such as empathy and intelligence to perceive and judge morally.”

Frey, C. and Osborne, M. (2013). The Future of Employment: How Susceptible are Jobs to Computerization? Oxford Martin Programme on the Impacts of Future Technology, University of Oxford: p. 50-67.

Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46-60. doi.org/10.1016/j.futures.2017.03.006

Nordhaus, W. (2015). Are We Approaching an Economic Singularity? Information Technology and the Future of Economic Growth. Cowles Foundation Discussion Paper no. 2021. Yale University: 1-30.

Reed, S., Akata, Z., Yan, X., Logeswaran, L., Schiele, B., and Lee, H. 2016. “Generative adversarial text to image synthesis.” In  Proceedings of the 33rd International Conference on Machine Learning  48: 1060–1069.

Syverson, C. (2017). Challenges to Mismeasurement Explanations for the US Productivity Slowdown. Journal of Economic Perspectives, 31(2):165–186.

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TechBullion

The impact of artificial intelligence on job market trends.

Are robots taking over our jobs? Will artificial intelligence make human labor obsolete? These questions have been wandering over the job market for years, sparking debates and fears about the future of employment. As technology advances at an unprecedented rate, the impact of artificial intelligence on job market trends cannot be overstated. In the following comprehensive blog, we’ll dive into the revolutionary effects of AI on employment, explore emerging job market trends, and discuss strategies for navigating the evolving landscape of work. What are you waiting for? Come, let’s explore!

The Rise of Artificial Intelligence: 

According to a popular artificial intelligence course , artificial intelligence – once a concept confined to science fiction has now become a reality permeating different aspects of our lives. From virtual assistants like Siri and Alexa to sophisticated algorithms that power recommendation systems and self-driving cars, AI is redefining industries and changing the way we live and work. 

Further, as discussed in most artificial intelligence course , one of the key areas where AI is making significant inroads is in the world of employment. Automation, driven by AI and robotics, is actively replacing repetitive and routine tasks across industries, leading to concerns about job displacement and unemployment. 

Navigating The Job Market Trends in the Age of AI: 

While the widespread adoption of AI is undoubtedly interrupting traditional job roles, it is also giving rise to new prospects and reshaping the labor market in innumerable ways. 

Here are some key job market trends emerging in the era of AI as discussed in top-rated artificial intelligence online training or offline training: 

• Automation and Job Displacement: Routine tasks in manufacturing, customer service, and administrative roles are becoming more automated, resulting in job displacement for many workers. Further, industries that excessively depend on manual labor are witnessing the most significant impact, as AI-driven technologies simplify processes and enhance efficiency.
• Rise of AI-Enabled Jobs: Although some roles are slowly becoming automated, the demand for workers holding AI-related skills is soaring higher than ever before. Jobs like data scientists, machine learning engineers, and AI ethicists are witnessing high demand as businesses invest in AI-driven technologies. In addition, there is a rising demand for professionals who can develop, maintain, and oversee AI systems, guaranteeing they operate ethically and responsibly.
• Hybrid Roles: The integration of AI into different industries is giving rise to hybrid roles that demand a combination of technical expertise and domain knowledge. For instance, healthcare professionals holding proficiency in AI and medical data analysis are in high demand to develop diagnostic tools and personalized treatment plans.
• Upskilling and Reskilling: According to the knowledge imparted in an artificial intelligence course, as job roles evolve in response to AI adoption, there is a rising emphasis on upskilling and reskilling the workforce. Workers must gain new skills to stay relevant in the labor market and adapt to the changing nature of work. Lifelong learning initiatives and training programs concentrated on AI and digital literacy are becoming increasingly essential for workers across all industries. 

Also Read: What is The Scope of Artificial Intelligence And Data Science

Exploring The Future World of Work: 

In light of the above-listed trends, navigating the future world of work demands a proactive strategy and a willingness to adapt to technological innovations. Here are some approaches for individuals and businesses to thrive in the age of AI: 

• Invest in Lifelong Learning: Individuals must embrace a mindset of continuous learning and skills development. They shall stay abreast of the latest trends in AI and technology and invest in a good artificial intelligence course to gain relevant skills that align with emerging job market demands.
• Cultivate Adaptability: The ability to adapt to change is paramount in a rapidly changing job market. Professionals must develop adaptability by being open to new prospects, learning new technologies, and expanding their skill set to stay competitive.
• Concentrate on Human-Centric Skills: While AI can automate certain tasks, human-centric skills like creativity, emotional intelligence, and critical thinking stay highly valued. Professionals must concentrate on developing these skills that are less susceptible to automation and are necessary for roles demanding human interaction and decision-making.
• Promote Ethical AI Practices: As AI becomes actively integrated into society , it’s essential to prioritize ethical considerations. Businesses must foster responsible AI development and implementation, guaranteeing that AI systems are transparent, fair, and accountable. 

Future Outlook: Anticipating Trends Beyond 2024: 

As we peer into the future beyond 2024, the trajectory of artificial intelligence continues to shape the employment market with profound implications. Forecasting trends in AI beyond this year offer a glimpse into a realm characterized by further integration, innovation, and adaptation. One essential trend is the continued expansion of AI into new industries and sectors. While AI has been widely adopted in technology-centric domains such as IT and banking, we may expect it to spread to traditionally non-tech industries such as healthcare, agriculture, and education. This expansion will increase the demand for individuals with a combination of domain expertise and AI ability, resulting in the rise of hybrid positions that bridge the gap between technology and certain sectors.

In addition, innovations in AI research and development will drive the creation of more sophisticated AI systems capable of complex decision-making, problem-solving, and human-like interactions. This evolution will unlock new opportunities in automation, personalization, and efficiency across different domains, fundamentally reshaping the nature of work. However, these developments bring with them issues such as ethical considerations, privacy concerns, and the possibility of employment displacement. As AI evolves, politicians, corporations, and society as a whole must address these concerns proactively, ensuring that the advantages of AI are dispersed evenly while reducing its negative effects on the workforce. Fostering cooperation, innovation, and responsible AI governance will be critical in realizing the full promise of artificial intelligence while protecting individual and community interests.

Wrapping Up!

To summarise, as discussed in a popular artificial intelligence course, AI’s impact on the job market is evident, with automation changing old occupations and offering new opportunities. While there are legitimate concerns about job displacement, the emergence of AI-enabled jobs and the demand for technical talent create opportunities for growth and innovation. Individuals and organizations may negotiate the future world of work with confidence and resilience if they embrace lifelong learning, cultivate adaptation, and prioritize human-centric skills. As we approach a new era characterized by AI, proactive involvement and ethical stewardship will be critical in realizing its full potential for societal benefit.

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4 ways leaders can alleviate fears of ai stealing employees’ careers.

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One of the biggest fears of the American workforce is that AI will snatch their jobs from underneath ... [+] them. But are these fears warranted?

April is National Stress Awareness month, and one of the constant stressors in employees’ lives is the rise of artificial intelligence (AI). Another major challenge for employees in 2024 is to come to terms with the fact that AI will eventually dominate the workplace. According to a recent Gallup poll , 22% of U.S. workers are worried they will lose their jobs to generative AI—a seven percent increase since 2021. Before leaders can help employees with the fears of AI taking their jobs, they must first understand the quandary themselves and have clear and factual explanations to the question on everyone’s mind, “Is AI a tool or a threat?”

According to a Quickbase survey , 54% of workers surveyed in the U.S. and U.K. say that it’s harder than ever to be productive in their day-to-day work. This is further proof that the way we’re working is no longer working. A main contributor to all this inefficiency is Gray Work —the outdated and spread-out tech and tools employees use just to get by. It causes the manual, repetitive and tedious tasks they’re stuck doing in between the work that actually drives results. In the age of AI, another factor is poor data collection. AI is only as useful as the data it’s fed, so without a strong and trusted way of collecting, tracking and recording data, AI can’t deliver the results you’d expect from the emerging technology.

In order to make their work easier, employees have started to seek out unauthorized software, according to Uzi Dvir, chief information officer (CIO) at WalkMe. I spoke to Dvir by email about the phenomenon of “Shadow IT”—the use of IT systems, software or services without the approval of the central IT department. He told me that it can occur when an employee uses an unapproved tool to access, store or share corporate data or when an employee accesses an approved tool in an unauthorized way. “Organizations should also want their employees to be able to do better work faster; there are undeniable benefits for both the individual and their company to employees using these apps,” Dvir states. “However, the fact that employees need to take it upon themselves to find and use unsanctioned software means that they feel something is lacking in the technology tools provided to them.”

Can AI help solve some of these problems to reduce employee stress? I spoke by email with Nikhil Arora, CEO of Epignosis , a global learning and development company, who offered four ways leaders can alleviate this stress and help prepare their employees for a more AI-dominated workplace.

1- Communicate clearly to empower. Arora emphasizes that AI is an asset for helping with repetitive tasks, crunching data and streamlining operations and processes. When employers impart this information to employees, he says, it will help change the way they work in a more positive and effective way, allowing workers to focus on higher-value work, the more creative or strategic aspects of their role.

He underscores the need for a well-rounded skill set and a growing significance of soft skills alongside AI adoption. “Educating teams on the importance of both hard and soft skills that AI can’t replace—such as critical thinking, adaptability, key interpersonal skills like active listening, empathy and genuine connection is paramount,” Arora notes. “By familiarizing themselves with the benefits of AI early on, team members can build confidence and adaptability, positioning themselves as valuable assets in an increasingly digital world.”

2- Invest in upskilling and reskilling tools. Arora believes that investing in comprehensive training resources is essential to support ongoing learning. “As with any technology, organizations and employees need to be trained in how to use AI effectively to reap the full benefits and avert potential dangers it poses,” he points out, citing TalentLMS’ latest survey on L&D trends for 2024 that shows training on AI tools is among the top three non-mandatory training topics employees want from their employers. “From implementing traditional methods like Learning & Development programs to more informal initiatives such as lunch and learns, integrating learning opportunities into the team's regular cadence promotes sustained growth,” he insists. “Making upskilling and reskilling a habitual part of the organizational culture ensures that team members are equipped to navigate technological advancements and other opportunities with greater confidence and competence.”

3- Encourage tech adopters to teach how AI is a tool not a threat. People place significant trust in their peers, Arora explains, so if they see one person implementing new ways of working through AI, they are likely to be more receptive to learning more about it or trying it out for themselves. “With five generations in the workplace, it's common for there to be a gap in confidence, he states, alluding to the TalentLMS study , which found that 58% of HR managers believe older generations will feel less confident at work because of AI. “With that in mind,” he adds, “leaders can encourage early tech adopter team members to tap into existing touchpoints—like regular team meetings—to lead by example, augmenting with AI in an effort to normalize and familiarize other team members with its benefits. By doing so, peers and leaders can demonstrate that AI is a tool and not a threat, which can help ease fears.”

4- Coach and role-model to inspire lifelong career development. Arora told me he believes that people innately desire a deep sense of purpose and connection in life, which is the ultimate motivator for humanity. “Learning serves as a pathway to fulfilling those needs, and in the context of digitization and employer-employee relationships, AI has the ability to accelerate this path and bring the power of learning to life in incredibly meaningful ways.”

He foresees a future where AI is leveraged to democratize learning—through personalization, flexibility, affordability and on-demand access—in which it empowers people, teams and organizations to truly revolutionize human potential, productivity and impact. “Encouraging and fostering a growth mindset versus fixed mindsets within teams, can help shift how employees approach any challenge,” he asserts, “including AI disruption and adoption in viewing change as an opportunity to learn, instead of a threat.”

So, is AI a tool or a threat? Perhaps it’s like asking if water is good or bad. Too much or too little can kill us. Maybe the way to consider AI is that it’s neither good nor bad, but in the final analysis, it’s how we use it to support employees and improve humanity that counts. AI might just become everyone’s virtual personal assistant, automating everything from onboarding to performance management, freeing up staff to focus on more strategic initiatives.

“When leaders coach one-on-one and role-model how they approach challenges and embrace ambiguity, this has a trickle-down effect on the performance of their teams for the long-term,” Arora concludes. “By being intentional in coaching team members, through frequent, clear and actionable feedback, leaders will build a trusting team culture and inspire adaptability—underscoring the most valuable soft skill of today—and further shift the mindset that AI is a tool, not a threat.”

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The National Pension System or NPS is a measure to introduce a degree of financial stability...

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Mutual Funds are one of the most incredible investment strategies that offer better returns...

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