technology and its impact essay

Technology and Its Impact in the World Essay

Introduction, technology impacts, works cited.

Technology is defined as the use of tools, techniques and methods of organization in solving real world problems, which aims at performing specific tasks.

Technology has a profound root in the society; this is because today’s world relies on the advances in technology. These advances in technology in today’s world has sped people’s lives and made the world a smaller place to live in as it makes different locations closer to one another.

In addition, the fact that technology has become omnipresent in the world today due to its widespread use, is vital because it helps people in carrying out their chores in their daily livelihood. It is therefore important that the technology that exists be easily adaptable and able to solve the current world issues as human progress rate is increasing at an alarming rate (Oak 1).

The advances in technology have brought huge changes in the world today. Some of the areas where technology has brought important changes are as follows. First, technology has enabled the world in automating its critical processes in industries and households. The automobile industry has evolved from mechanical to automated automobiles simply because of the driving force that is technology.

Technology is applicable in performing tasks that are not accessible to man and are vital in automating crucial industrial processes. The technologies that are applicable when performing these crucial tasks include the use of robotics and artificial intelligence in carrying out challenging tasks such as space exploration and mining (Oak 1).

Another positive effect of technology is that it has changed the manner of communication. This has been made possible through the use computer technology; computers have the ability to process huge chunks of data at one go. Information digitization has proved to be a vital technology platform since it has made it possible in storing information and helps in enriching the information quality.

The advances in technology enable harnessing of water from natural sources to homes through robust transmission systems. Technology has brought the discovery of electricity that is important in lighting up the world. Electricity is easily generated by using renewable energy resources.

On the other hand, with all the advances in technology, it is unimaginable that technology has its side effects in the society even when the world is at the epitome of technology. In the medical technology world, technology can affect and also harm patients in cases where it involves a machine that has radiation rays.

On environmental technology, there is a lot of waste in terms of chemicals, which directly go back to the environment. Lastly, technology has a negative impact on people since they tend to be lazy and rely mostly on technology (Oak 1).

In conclusion, the advances brought about by technologies, which are the Internet, cell phones, and notebook computers are vital necessity for daily living. Due to these advances, it is easy for us to forget about those who suffer while attempting to provide for their basic needs, such as clean water, food and health care.

It is a good gesture by the developed world to make use of their technologies to help the underprivileged groups of people in the society. Through the continuous use of these technologies, there are advances that targets medical services, improved economy based on the Internet, emerging technologies in information systems sector, advanced farming methods and industrial sectors.

More importantly, educational needs for the people are taken into consideration by these technologies, since they help them become prosperous nations who do not require help from others but are able to get their own resources. Moreover, transferring technology from the developed world to the developing world has various benefits. There will be improvement in living standards, production efficiency and become a base for economic growth (Oak 1).

Oak, Manali. “ Positive Effects of Technology on Society .” Buzzle. 2011. Web.

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Politics and privacy, private-sector influence and big tech, state competition and conflict, author biography, how is technology changing the world, and how should the world change technology.

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Josephine Wolff; How Is Technology Changing the World, and How Should the World Change Technology?. Global Perspectives 1 February 2021; 2 (1): 27353. doi: https://doi.org/10.1525/gp.2021.27353

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Technologies are becoming increasingly complicated and increasingly interconnected. Cars, airplanes, medical devices, financial transactions, and electricity systems all rely on more computer software than they ever have before, making them seem both harder to understand and, in some cases, harder to control. Government and corporate surveillance of individuals and information processing relies largely on digital technologies and artificial intelligence, and therefore involves less human-to-human contact than ever before and more opportunities for biases to be embedded and codified in our technological systems in ways we may not even be able to identify or recognize. Bioengineering advances are opening up new terrain for challenging philosophical, political, and economic questions regarding human-natural relations. Additionally, the management of these large and small devices and systems is increasingly done through the cloud, so that control over them is both very remote and removed from direct human or social control. The study of how to make technologies like artificial intelligence or the Internet of Things “explainable” has become its own area of research because it is so difficult to understand how they work or what is at fault when something goes wrong (Gunning and Aha 2019) .

This growing complexity makes it more difficult than ever—and more imperative than ever—for scholars to probe how technological advancements are altering life around the world in both positive and negative ways and what social, political, and legal tools are needed to help shape the development and design of technology in beneficial directions. This can seem like an impossible task in light of the rapid pace of technological change and the sense that its continued advancement is inevitable, but many countries around the world are only just beginning to take significant steps toward regulating computer technologies and are still in the process of radically rethinking the rules governing global data flows and exchange of technology across borders.

These are exciting times not just for technological development but also for technology policy—our technologies may be more advanced and complicated than ever but so, too, are our understandings of how they can best be leveraged, protected, and even constrained. The structures of technological systems as determined largely by government and institutional policies and those structures have tremendous implications for social organization and agency, ranging from open source, open systems that are highly distributed and decentralized, to those that are tightly controlled and closed, structured according to stricter and more hierarchical models. And just as our understanding of the governance of technology is developing in new and interesting ways, so, too, is our understanding of the social, cultural, environmental, and political dimensions of emerging technologies. We are realizing both the challenges and the importance of mapping out the full range of ways that technology is changing our society, what we want those changes to look like, and what tools we have to try to influence and guide those shifts.

Technology can be a source of tremendous optimism. It can help overcome some of the greatest challenges our society faces, including climate change, famine, and disease. For those who believe in the power of innovation and the promise of creative destruction to advance economic development and lead to better quality of life, technology is a vital economic driver (Schumpeter 1942) . But it can also be a tool of tremendous fear and oppression, embedding biases in automated decision-making processes and information-processing algorithms, exacerbating economic and social inequalities within and between countries to a staggering degree, or creating new weapons and avenues for attack unlike any we have had to face in the past. Scholars have even contended that the emergence of the term technology in the nineteenth and twentieth centuries marked a shift from viewing individual pieces of machinery as a means to achieving political and social progress to the more dangerous, or hazardous, view that larger-scale, more complex technological systems were a semiautonomous form of progress in and of themselves (Marx 2010) . More recently, technologists have sharply criticized what they view as a wave of new Luddites, people intent on slowing the development of technology and turning back the clock on innovation as a means of mitigating the societal impacts of technological change (Marlowe 1970) .

At the heart of fights over new technologies and their resulting global changes are often two conflicting visions of technology: a fundamentally optimistic one that believes humans use it as a tool to achieve greater goals, and a fundamentally pessimistic one that holds that technological systems have reached a point beyond our control. Technology philosophers have argued that neither of these views is wholly accurate and that a purely optimistic or pessimistic view of technology is insufficient to capture the nuances and complexity of our relationship to technology (Oberdiek and Tiles 1995) . Understanding technology and how we can make better decisions about designing, deploying, and refining it requires capturing that nuance and complexity through in-depth analysis of the impacts of different technological advancements and the ways they have played out in all their complicated and controversial messiness across the world.

These impacts are often unpredictable as technologies are adopted in new contexts and come to be used in ways that sometimes diverge significantly from the use cases envisioned by their designers. The internet, designed to help transmit information between computer networks, became a crucial vehicle for commerce, introducing unexpected avenues for crime and financial fraud. Social media platforms like Facebook and Twitter, designed to connect friends and families through sharing photographs and life updates, became focal points of election controversies and political influence. Cryptocurrencies, originally intended as a means of decentralized digital cash, have become a significant environmental hazard as more and more computing resources are devoted to mining these forms of virtual money. One of the crucial challenges in this area is therefore recognizing, documenting, and even anticipating some of these unexpected consequences and providing mechanisms to technologists for how to think through the impacts of their work, as well as possible other paths to different outcomes (Verbeek 2006) . And just as technological innovations can cause unexpected harm, they can also bring about extraordinary benefits—new vaccines and medicines to address global pandemics and save thousands of lives, new sources of energy that can drastically reduce emissions and help combat climate change, new modes of education that can reach people who would otherwise have no access to schooling. Regulating technology therefore requires a careful balance of mitigating risks without overly restricting potentially beneficial innovations.

Nations around the world have taken very different approaches to governing emerging technologies and have adopted a range of different technologies themselves in pursuit of more modern governance structures and processes (Braman 2009) . In Europe, the precautionary principle has guided much more anticipatory regulation aimed at addressing the risks presented by technologies even before they are fully realized. For instance, the European Union’s General Data Protection Regulation focuses on the responsibilities of data controllers and processors to provide individuals with access to their data and information about how that data is being used not just as a means of addressing existing security and privacy threats, such as data breaches, but also to protect against future developments and uses of that data for artificial intelligence and automated decision-making purposes. In Germany, Technische Überwachungsvereine, or TÜVs, perform regular tests and inspections of technological systems to assess and minimize risks over time, as the tech landscape evolves. In the United States, by contrast, there is much greater reliance on litigation and liability regimes to address safety and security failings after-the-fact. These different approaches reflect not just the different legal and regulatory mechanisms and philosophies of different nations but also the different ways those nations prioritize rapid development of the technology industry versus safety, security, and individual control. Typically, governance innovations move much more slowly than technological innovations, and regulations can lag years, or even decades, behind the technologies they aim to govern.

In addition to this varied set of national regulatory approaches, a variety of international and nongovernmental organizations also contribute to the process of developing standards, rules, and norms for new technologies, including the International Organization for Standardization­ and the International Telecommunication Union. These multilateral and NGO actors play an especially important role in trying to define appropriate boundaries for the use of new technologies by governments as instruments of control for the state.

At the same time that policymakers are under scrutiny both for their decisions about how to regulate technology as well as their decisions about how and when to adopt technologies like facial recognition themselves, technology firms and designers have also come under increasing criticism. Growing recognition that the design of technologies can have far-reaching social and political implications means that there is more pressure on technologists to take into consideration the consequences of their decisions early on in the design process (Vincenti 1993; Winner 1980) . The question of how technologists should incorporate these social dimensions into their design and development processes is an old one, and debate on these issues dates back to the 1970s, but it remains an urgent and often overlooked part of the puzzle because so many of the supposedly systematic mechanisms for assessing the impacts of new technologies in both the private and public sectors are primarily bureaucratic, symbolic processes rather than carrying any real weight or influence.

Technologists are often ill-equipped or unwilling to respond to the sorts of social problems that their creations have—often unwittingly—exacerbated, and instead point to governments and lawmakers to address those problems (Zuckerberg 2019) . But governments often have few incentives to engage in this area. This is because setting clear standards and rules for an ever-evolving technological landscape can be extremely challenging, because enforcement of those rules can be a significant undertaking requiring considerable expertise, and because the tech sector is a major source of jobs and revenue for many countries that may fear losing those benefits if they constrain companies too much. This indicates not just a need for clearer incentives and better policies for both private- and public-sector entities but also a need for new mechanisms whereby the technology development and design process can be influenced and assessed by people with a wider range of experiences and expertise. If we want technologies to be designed with an eye to their impacts, who is responsible for predicting, measuring, and mitigating those impacts throughout the design process? Involving policymakers in that process in a more meaningful way will also require training them to have the analytic and technical capacity to more fully engage with technologists and understand more fully the implications of their decisions.

At the same time that tech companies seem unwilling or unable to rein in their creations, many also fear they wield too much power, in some cases all but replacing governments and international organizations in their ability to make decisions that affect millions of people worldwide and control access to information, platforms, and audiences (Kilovaty 2020) . Regulators around the world have begun considering whether some of these companies have become so powerful that they violate the tenets of antitrust laws, but it can be difficult for governments to identify exactly what those violations are, especially in the context of an industry where the largest players often provide their customers with free services. And the platforms and services developed by tech companies are often wielded most powerfully and dangerously not directly by their private-sector creators and operators but instead by states themselves for widespread misinformation campaigns that serve political purposes (Nye 2018) .

Since the largest private entities in the tech sector operate in many countries, they are often better poised to implement global changes to the technological ecosystem than individual states or regulatory bodies, creating new challenges to existing governance structures and hierarchies. Just as it can be challenging to provide oversight for government use of technologies, so, too, oversight of the biggest tech companies, which have more resources, reach, and power than many nations, can prove to be a daunting task. The rise of network forms of organization and the growing gig economy have added to these challenges, making it even harder for regulators to fully address the breadth of these companies’ operations (Powell 1990) . The private-public partnerships that have emerged around energy, transportation, medical, and cyber technologies further complicate this picture, blurring the line between the public and private sectors and raising critical questions about the role of each in providing critical infrastructure, health care, and security. How can and should private tech companies operating in these different sectors be governed, and what types of influence do they exert over regulators? How feasible are different policy proposals aimed at technological innovation, and what potential unintended consequences might they have?

Conflict between countries has also spilled over significantly into the private sector in recent years, most notably in the case of tensions between the United States and China over which technologies developed in each country will be permitted by the other and which will be purchased by other customers, outside those two countries. Countries competing to develop the best technology is not a new phenomenon, but the current conflicts have major international ramifications and will influence the infrastructure that is installed and used around the world for years to come. Untangling the different factors that feed into these tussles as well as whom they benefit and whom they leave at a disadvantage is crucial for understanding how governments can most effectively foster technological innovation and invention domestically as well as the global consequences of those efforts. As much of the world is forced to choose between buying technology from the United States or from China, how should we understand the long-term impacts of those choices and the options available to people in countries without robust domestic tech industries? Does the global spread of technologies help fuel further innovation in countries with smaller tech markets, or does it reinforce the dominance of the states that are already most prominent in this sector? How can research universities maintain global collaborations and research communities in light of these national competitions, and what role does government research and development spending play in fostering innovation within its own borders and worldwide? How should intellectual property protections evolve to meet the demands of the technology industry, and how can those protections be enforced globally?

These conflicts between countries sometimes appear to challenge the feasibility of truly global technologies and networks that operate across all countries through standardized protocols and design features. Organizations like the International Organization for Standardization, the World Intellectual Property Organization, the United Nations Industrial Development Organization, and many others have tried to harmonize these policies and protocols across different countries for years, but have met with limited success when it comes to resolving the issues of greatest tension and disagreement among nations. For technology to operate in a global environment, there is a need for a much greater degree of coordination among countries and the development of common standards and norms, but governments continue to struggle to agree not just on those norms themselves but even the appropriate venue and processes for developing them. Without greater global cooperation, is it possible to maintain a global network like the internet or to promote the spread of new technologies around the world to address challenges of sustainability? What might help incentivize that cooperation moving forward, and what could new structures and process for governance of global technologies look like? Why has the tech industry’s self-regulation culture persisted? Do the same traditional drivers for public policy, such as politics of harmonization and path dependency in policy-making, still sufficiently explain policy outcomes in this space? As new technologies and their applications spread across the globe in uneven ways, how and when do they create forces of change from unexpected places?

These are some of the questions that we hope to address in the Technology and Global Change section through articles that tackle new dimensions of the global landscape of designing, developing, deploying, and assessing new technologies to address major challenges the world faces. Understanding these processes requires synthesizing knowledge from a range of different fields, including sociology, political science, economics, and history, as well as technical fields such as engineering, climate science, and computer science. A crucial part of understanding how technology has created global change and, in turn, how global changes have influenced the development of new technologies is understanding the technologies themselves in all their richness and complexity—how they work, the limits of what they can do, what they were designed to do, how they are actually used. Just as technologies themselves are becoming more complicated, so are their embeddings and relationships to the larger social, political, and legal contexts in which they exist. Scholars across all disciplines are encouraged to join us in untangling those complexities.

Josephine Wolff is an associate professor of cybersecurity policy at the Fletcher School of Law and Diplomacy at Tufts University. Her book You’ll See This Message When It Is Too Late: The Legal and Economic Aftermath of Cybersecurity Breaches was published by MIT Press in 2018.

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Home — Essay Samples — Information Science and Technology — Technology — Impact of Technology

Essays on Impact of Technology

Popular impact of technology essay topic and ideas.

• The Digital Divide: Technology's Role in Widening or Bridging the Gap
• Technology and Education: Transforming the Way We Learn and Teach
• The Future of Work: How Technology is Shaping Job Markets and Skills
• Privacy in the Digital Age: The Impact of Technology on Personal Data Security
• The Impact of Technology on Human Relationships
• E-Health: How Technology is Revolutionizing Healthcare
• The Environmental Footprint of Technological Advancements: Challenges and Solutions
• Social Media: Its Influence on Society and Individual Psychology
• The Role of Technology in Enhancing Art Appreciation
• Smart Cities: How Technology is Shaping Urban Development

The Internet's Impact on Human Society

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The Relationship Between Technology Use and Attention Span

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Technology Has Taken Over Society

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The Role of Technology in Improving Society

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• Disadvantages of Technology
• Negative Impact of Technology
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Feb 13, 2023

200-500 Word Example Essays about Technology

Got an essay assignment about technology check out these examples to inspire you.

Technology is a rapidly evolving field that has completely changed the way we live, work, and interact with one another. Technology has profoundly impacted our daily lives, from how we communicate with friends and family to how we access information and complete tasks. As a result, it's no surprise that technology is a popular topic for students writing essays.

But writing a technology essay can be challenging, especially for those needing more time or help with writer's block. This is where Jenni.ai comes in. Jenni.ai is an innovative AI tool explicitly designed for students who need help writing essays. With Jenni.ai, students can quickly and easily generate essays on various topics, including technology.

This blog post aims to provide readers with various example essays on technology, all generated by Jenni.ai. These essays will be a valuable resource for students looking for inspiration or guidance as they work on their essays. By reading through these example essays, students can better understand how technology can be approached and discussed in an essay.

Moreover, by signing up for a free trial with Jenni.ai, students can take advantage of this innovative tool and receive even more support as they work on their essays. Jenni.ai is designed to help students write essays faster and more efficiently, so they can focus on what truly matters – learning and growing as a student. Whether you're a student who is struggling with writer's block or simply looking for a convenient way to generate essays on a wide range of topics, Jenni.ai is the perfect solution.

The Impact of Technology on Society and Culture

Introduction:.

Technology has become an integral part of our daily lives and has dramatically impacted how we interact, communicate, and carry out various activities. Technological advancements have brought positive and negative changes to society and culture. In this article, we will explore the impact of technology on society and culture and how it has influenced different aspects of our lives.

Positive impact on communication:

Technology has dramatically improved communication and made it easier for people to connect from anywhere in the world. Social media platforms, instant messaging, and video conferencing have brought people closer, bridging geographical distances and cultural differences. This has made it easier for people to share information, exchange ideas, and collaborate on projects.

Positive impact on education:

Students and instructors now have access to a multitude of knowledge and resources because of the effect of technology on education . Students may now study at their speed and from any location thanks to online learning platforms, educational applications, and digital textbooks.

Negative impact on critical thinking and creativity:

Technological advancements have resulted in a reduction in critical thinking and creativity. With so much information at our fingertips, individuals have become more passive in their learning, relying on the internet for solutions rather than logic and inventiveness. As a result, independent thinking and problem-solving abilities have declined.

Positive impact on entertainment:

Technology has transformed how we access and consume entertainment. People may now access a wide range of entertainment alternatives from the comfort of their own homes thanks to streaming services, gaming platforms, and online content makers. The entertainment business has entered a new age of creativity and invention as a result of this.

Negative impact on attention span:

However, the continual bombardment of information and technological stimulation has also reduced attention span and the capacity to focus. People are easily distracted and need help focusing on a single activity for a long time. This has hampered productivity and the ability to accomplish duties.

The Ethics of Artificial Intelligence And Machine Learning

The development of artificial intelligence (AI) and machine learning (ML) technologies has been one of the most significant technological developments of the past several decades. These cutting-edge technologies have the potential to alter several sectors of society, including commerce, industry, healthcare, and entertainment. 

As with any new and quickly advancing technology, AI and ML ethics must be carefully studied. The usage of these technologies presents significant concerns around privacy, accountability, and command. As the use of AI and ML grows more ubiquitous, we must assess their possible influence on society and investigate the ethical issues that must be taken into account as these technologies continue to develop.

What are Artificial Intelligence and Machine Learning?

Artificial Intelligence is the simulation of human intelligence in machines designed to think and act like humans. Machine learning is a subfield of AI that enables computers to learn from data and improve their performance over time without being explicitly programmed.

The impact of AI and ML on Society

The use of AI and ML in various industries, such as healthcare, finance, and retail, has brought many benefits. For example, AI-powered medical diagnosis systems can identify diseases faster and more accurately than human doctors. However, there are also concerns about job displacement and the potential for AI to perpetuate societal biases.

The Ethical Considerations of AI and ML

A. Bias in AI algorithms

One of the critical ethical concerns about AI and ML is the potential for algorithms to perpetuate existing biases. This can occur if the data used to train these algorithms reflects the preferences of the people who created it. As a result, AI systems can perpetuate these biases and discriminate against certain groups of people.

B. Responsibility for AI-generated decisions

Another ethical concern is the responsibility for decisions made by AI systems. For example, who is responsible for the damage if a self-driving car causes an accident? The manufacturer of the vehicle, the software developer, or the AI algorithm itself?

C. The potential for misuse of AI and ML

AI and ML can also be used for malicious purposes, such as cyberattacks and misinformation. The need for more regulation and oversight in developing and using these technologies makes it difficult to prevent misuse.

The developments in AI and ML have given numerous benefits to humanity, but they also present significant ethical concerns that must be addressed. We must assess the repercussions of new technologies on society, implement methods to limit the associated dangers, and guarantee that they are utilized for the greater good. As AI and ML continue to play an ever-increasing role in our daily lives, we must engage in an open and frank discussion regarding their ethics.

The Future of Work And Automation

Rapid technological breakthroughs in recent years have brought about considerable changes in our way of life and work. Concerns regarding the influence of artificial intelligence and machine learning on the future of work and employment have increased alongside the development of these technologies. This article will examine the possible advantages and disadvantages of automation and its influence on the labor market, employees, and the economy.

The Advantages of Automation

Automation in the workplace offers various benefits, including higher efficiency and production, fewer mistakes, and enhanced precision. Automated processes may accomplish repetitive jobs quickly and precisely, allowing employees to concentrate on more complex and creative activities. Additionally, automation may save organizations money since it removes the need to pay for labor and minimizes the danger of workplace accidents.

The Potential Disadvantages of Automation

However, automation has significant disadvantages, including job loss and income stagnation. As robots and computers replace human labor in particular industries, there is a danger that many workers may lose their jobs, resulting in higher unemployment and more significant economic disparity. Moreover, if automation is not adequately regulated and managed, it might lead to stagnant wages and a deterioration in employees' standard of life.

The Future of Work and Automation

Despite these difficulties, automation will likely influence how labor is done. As a result, firms, employees, and governments must take early measures to solve possible issues and reap the rewards of automation. This might entail funding worker retraining programs, enhancing education and skill development, and implementing regulations that support equality and justice at work.

IV. The Need for Ethical Considerations

We must consider the ethical ramifications of automation and its effects on society as technology develops. The impact on employees and their rights, possible hazards to privacy and security, and the duty of corporations and governments to ensure that automation is utilized responsibly and ethically are all factors to be taken into account.

Conclusion:

To summarise, the future of employment and automation will most certainly be defined by a complex interaction of technological advances, economic trends, and cultural ideals. All stakeholders must work together to handle the problems and possibilities presented by automation and ensure that technology is employed to benefit society as a whole.

The Role of Technology in Education

Introduction.

Nearly every part of our lives has been transformed by technology, and education is no different. Today's students have greater access to knowledge, opportunities, and resources than ever before, and technology is becoming a more significant part of their educational experience. Technology is transforming how we think about education and creating new opportunities for learners of all ages, from online courses and virtual classrooms to instructional applications and augmented reality.

Technology's Benefits for Education

The capacity to tailor learning is one of technology's most significant benefits in education. Students may customize their education to meet their unique needs and interests since they can access online information and tools. 

For instance, people can enroll in online classes on topics they are interested in, get tailored feedback on their work, and engage in virtual discussions with peers and subject matter experts worldwide. As a result, pupils are better able to acquire and develop the abilities and information necessary for success.

Challenges and Concerns

Despite the numerous advantages of technology in education, there are also obstacles and considerations to consider. One issue is the growing reliance on technology and the possibility that pupils would become overly dependent on it. This might result in a lack of critical thinking and problem-solving abilities, as students may become passive learners who only follow instructions and rely on technology to complete their assignments.

Another obstacle is the digital divide between those who have access to technology and those who do not. This division can exacerbate the achievement gap between pupils and produce uneven educational and professional growth chances. To reduce these consequences, all students must have access to the technology and resources necessary for success.

In conclusion, technology is rapidly becoming an integral part of the classroom experience and has the potential to alter the way we learn radically. 

Technology can help students flourish and realize their full potential by giving them access to individualized instruction, tools, and opportunities. While the benefits of technology in the classroom are undeniable, it's crucial to be mindful of the risks and take precautions to guarantee that all kids have access to the tools they need to thrive.

The Influence of Technology On Personal Relationships And Communication 

Technological advancements have profoundly altered how individuals connect and exchange information. It has changed the world in many ways in only a few decades. Because of the rise of the internet and various social media sites, maintaining relationships with people from all walks of life is now simpler than ever. 

However, concerns about how these developments may affect interpersonal connections and dialogue are inevitable in an era of rapid technological growth. In this piece, we'll discuss how the prevalence of digital media has altered our interpersonal connections and the language we use to express ourselves.

Direct Effect on Direct Interaction:

The disruption of face-to-face communication is a particularly stark example of how technology has impacted human connections. The quality of interpersonal connections has suffered due to people's growing preference for digital over human communication. Technology has been demonstrated to reduce the usage of nonverbal signs such as facial expressions, tone of voice, and other indicators of emotional investment in the connection.

Positive Impact on Long-Distance Relationships:

Yet there are positives to be found as well. Long-distance relationships have also benefited from technological advancements. The development of technologies such as video conferencing, instant messaging, and social media has made it possible for individuals to keep in touch with distant loved ones. It has become simpler for individuals to stay in touch and feel connected despite geographical distance.

The Effects of Social Media on Personal Connections:

The widespread use of social media has had far-reaching consequences, especially on the quality of interpersonal interactions. Social media has positive and harmful effects on relationships since it allows people to keep in touch and share life's milestones.

Unfortunately, social media has made it all too easy to compare oneself to others, which may lead to emotions of jealousy and a general decline in confidence. Furthermore, social media might cause people to have inflated expectations of themselves and their relationships.

A Personal Perspective on the Intersection of Technology and Romance

Technological advancements have also altered physical touch and closeness. Virtual reality and other technologies have allowed people to feel physical contact and familiarity in a digital setting. This might be a promising breakthrough, but it has some potential downsides. 

Experts are concerned that people's growing dependence on technology for intimacy may lead to less time spent communicating face-to-face and less emphasis on physical contact, both of which are important for maintaining good relationships.

In conclusion, technological advancements have significantly affected the quality of interpersonal connections and the exchange of information. Even though technology has made it simpler to maintain personal relationships, it has chilled interpersonal interactions between people. 

Keeping tabs on how technology is changing our lives and making adjustments as necessary is essential as we move forward. Boundaries and prioritizing in-person conversation and physical touch in close relationships may help reduce the harm it causes.

The Security and Privacy Implications of Increased Technology Use and Data Collection

The fast development of technology over the past few decades has made its way into every aspect of our life. Technology has improved many facets of our life, from communication to commerce. However, significant privacy and security problems have emerged due to the broad adoption of technology. In this essay, we'll look at how the widespread use of technological solutions and the subsequent explosion in collected data affects our right to privacy and security.

Data Mining and Privacy Concerns

Risk of Cyber Attacks and Data Loss

The Widespread Use of Encryption and Other Safety Mechanisms

The Privacy and Security of the Future in a Globalized Information Age

Obtaining and Using Individual Information

The acquisition and use of private information is a significant cause for privacy alarm in the digital age. Data about their customers' online habits, interests, and personal information is a valuable commodity for many internet firms. Besides tailored advertising, this information may be used for other, less desirable things like identity theft or cyber assaults.

Moreover, many individuals need to be made aware of what data is being gathered from them or how it is being utilized because of the lack of transparency around gathering personal information. Privacy and data security have become increasingly contentious as a result.

Data breaches and other forms of cyber-attack pose a severe risk.

The risk of cyber assaults and data breaches is another big issue of worry. More people are using more devices, which means more opportunities for cybercriminals to steal private information like credit card numbers and other identifying data. This may cause monetary damages and harm one's reputation or identity.

Many high-profile data breaches have occurred in recent years, exposing the personal information of millions of individuals and raising serious concerns about the safety of this information. Companies and governments have responded to this problem by adopting new security methods like encryption and multi-factor authentication.

Many businesses now use encryption and other security measures to protect themselves from cybercriminals and data thieves. Encryption keeps sensitive information hidden by encoding it so that only those possessing the corresponding key can decipher it. This prevents private information like bank account numbers or social security numbers from falling into the wrong hands.

Firewalls, virus scanners, and two-factor authentication are all additional security precautions that may be used with encryption. While these safeguards do much to stave against cyber assaults, they are not entirely impregnable, and data breaches are still possible.

The Future of Privacy and Security in a Technologically Advanced World

There's little doubt that concerns about privacy and security will persist even as technology improves. There must be strict safeguards to secure people's private information as more and more of it is transferred and kept digitally. To achieve this goal, it may be necessary to implement novel technologies and heightened levels of protection and to revise the rules and regulations regulating the collection and storage of private information.

Individuals and businesses are understandably concerned about the security and privacy consequences of widespread technological use and data collecting. There are numerous obstacles to overcome in a society where technology plays an increasingly important role, from acquiring and using personal data to the risk of cyber-attacks and data breaches. Companies and governments must keep spending money on security measures and working to educate people about the significance of privacy and security if personal data is to remain safe.

In conclusion, technology has profoundly impacted virtually every aspect of our lives, including society and culture, ethics, work, education, personal relationships, and security and privacy. The rise of artificial intelligence and machine learning has presented new ethical considerations, while automation is transforming the future of work. 

In education, technology has revolutionized the way we learn and access information. At the same time, our dependence on technology has brought new challenges in terms of personal relationships, communication, security, and privacy.

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The Impact of Digital Technologies

Technologies can help make our world fairer, more peaceful, and more just. Digital advances can support and accelerate achievement of each of the 17 Sustainable Development Goals – from ending extreme poverty to reducing maternal and infant mortality, promoting sustainable farming and decent work, and achieving universal literacy. But technologies can also threaten privacy, erode security and fuel inequality. They have implications for human rights and human agency. Like generations before, we – governments, businesses and individuals – have a choice to make in how we harness and manage new technologies.

A DIGITAL FUTURE FOR ALL?

Digital technologies have advanced more rapidly than any innovation in our history – reaching around 50 per cent of the developing world’s population in only two decades and transforming societies. By enhancing connectivity, financial inclusion, access to trade and public services, technology can be a great equaliser.

In the health sector, for instance, AI-enabled frontier technologies are helping to save lives, diagnose diseases and extend life expectancy. In education, virtual learning environments and distance learning have opened up programmes to students who would otherwise be excluded. Public services are also becoming more accessible and accountable through blockchain-powered systems, and less bureaucratically burdensome as a result of AI assistance.Big data can also support more responsive and accurate policies and programmes.

However, those yet to be connected remain cut off from the benefits of this new era and remain further behind. Many of the people left behind are women, the elderly, persons with disabilities or from ethnic or linguistic minorities, indigenous groups and residents of poor or remote areas. The pace of connectivity is slowing, even reversing, among some constituencies. For example, globally, the proportion of women using the internet is 12 per cent lower than that of men. While this gap narrowed in most regions between 2013 and 2017, it widened in the least developed countries from 30 per cent to 33 per cent.

The use of algorithms can replicate and even amplify human and systemic bias where they function on the basis of data which is not adequately diverse. Lack of diversity in the technology sector can mean that this challenge is not adequately addressed.

THE FUTURE OF WORK

Throughout history, technological revolutions have changed the labour force: creating new forms and patterns of work, making others obsolete, and leading to wider societal changes. This current wave of change is likely to have profound impacts. For example, the International Labour Organization estimates that the shift to a greener economy could create 24 million new jobs globally by 2030 through the adoption of sustainable practices in the energy sector, the use of electric vehicles and increasing energy efficiency in existing and future buildings.

Meanwhile, reports by groups such as McKinsey suggest that 800 million people could lose their jobs to automation by 2030 , while polls reveal that the majority of all employees worry that they do not have the necessary training or skills to get a well-paid job.

There is broad agreement that managing these trends will require changes in our approach to education, for instance, by placing more emphasis on science, technology, engineering, and maths; by teaching soft skills, and resilience; and by ensuring that people can re-skill and up-skill throughout their lifetimes. Unpaid work, for example childcare and elderly care in the home, will need to be better supported, especially as with the shifting age profile of global populations, the demands on these tasks are likely to increase.

THE FUTURE OF DATA

Today, digital technologies such as data pooling and AI are used to track and diagnose issues in agriculture, health, and the environment, or to perform daily tasks such as navigating traffic or paying a bill. They can be used to defend and exercise human rights – but they can also be used to violate them, for example, by monitoring our movements, purchases, conversations and behaviours. Governments and businesses increasingly have the tools to mine and exploit data for financial and other purposes.

However, personal data would become an asset to a person, if there were a formula for better regulation of personal data ownership. Data-powered technology has the potential to empower individuals, improve human welfare, and promote universal rights, depending on the type of protections put in place.

THE FUTURE OF SOCIAL MEDIA

Social media connects almost half of the entire global population . It enables people to make their voices heard and to talk to people across the world in real time. However, it can also reinforce prejudices and sow discord, by giving hate speech and misinformation a platform, or by amplifying echo chambers.

In this way, social media algorithms can fuel the fragmentation of societies around the world. And yet they also have the potential to do the opposite.

THE FUTURE OF CYBERSPACE

How to manage these developments is the subject of much discussion – nationally and internationally – at a time when geopolitical tensions are on the rise. The UN Secretary-General has warned of a ‘great fracture’ between world powers, each with their own internet and AI strategy, as well as dominant currency, trade and financial rules and contradictory geopolitical and military views. Such a divide could establish a digital Berlin Wall. Increasingly, digital cooperation between states – and a universal cyberspace that reflects global standards for peace and security, human rights and sustainable development – is seen as crucial to ensuring a united world. A ‘global commitment for digital cooperation’ is a key recommendation by the Secretary-General’s High-level Panel on Digital Cooperation .

FOR MORE INFORMATION

The Sustainable Development Goals

The Age of Digital Interdependence: Report of the UN Secretary-General’s High-level Panel on Digital Cooperation

ILO | Global Commission on the Future of Work

Secretary General’s Address to the 74th Session of the UN General Assembly

Secretary General’s Strategy on New Technology

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How has technology changed - and changed us - in the past 20 years?

Remember this? Image:  REUTERS/Stephen Hird

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Stay up to date:, davos agenda.

• Since the dotcom bubble burst back in 2000, technology has radically transformed our societies and our daily lives.
• From smartphones to social media and healthcare, here's a brief history of the 21st century's technological revolution.

Just over 20 years ago, the dotcom bubble burst , causing the stocks of many tech firms to tumble. Some companies, like Amazon, quickly recovered their value – but many others were left in ruins. In the two decades since this crash, technology has advanced in many ways.

Many more people are online today than they were at the start of the millennium. Looking at broadband access, in 2000, just half of Americans had broadband access at home. Today, that number sits at more than 90% .

This broadband expansion was certainly not just an American phenomenon. Similar growth can be seen on a global scale; while less than 7% of the world was online in 2000, today over half the global population has access to the internet.

Similar trends can be seen in cellphone use. At the start of the 2000s, there were 740 million cell phone subscriptions worldwide. Two decades later, that number has surpassed 8 billion, meaning there are now more cellphones in the world than people

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At the same time, technology was also becoming more personal and portable. Apple sold its first iPod in 2001, and six years later it introduced the iPhone, which ushered in a new era of personal technology. These changes led to a world in which technology touches nearly everything we do.

Technology has changed major sectors over the past 20 years, including media, climate action and healthcare. The World Economic Forum’s Technology Pioneers , which just celebrated its 20th anniversary, gives us insight how emerging tech leaders have influenced and responded to these changes.

Media and media consumption

The past 20 years have greatly shaped how and where we consume media. In the early 2000s, many tech firms were still focused on expanding communication for work through advanced bandwidth for video streaming and other media consumption that is common today.

Others followed the path of expanding media options beyond traditional outlets. Early Tech Pioneers such as PlanetOut did this by providing an outlet and alternative media source for LGBTQIA communities as more people got online.

Following on from these first new media options, new communities and alternative media came the massive growth of social media. In 2004 , fewer than 1 million people were on Myspace; Facebook had not even launched. By 2018, Facebook had more 2.26 billion users with other sites also growing to hundreds of millions of users.

While these new online communities and communication channels have offered great spaces for alternative voices, their increased use has also brought issues of increased disinformation and polarization.

Today, many tech start-ups are focused on preserving these online media spaces while also mitigating the disinformation which can come with them. Recently, some Tech Pioneers have also approached this issue, including TruePic – which focuses on photo identification – and Two Hat , which is developing AI-powered content moderation for social media.

Climate change and green tech

Many scientists today are looking to technology to lead us towards a carbon-neutral world. Though renewed attention is being given to climate change today, these efforts to find a solution through technology is not new. In 2001, green tech offered a new investment opportunity for tech investors after the crash, leading to a boom of investing in renewable energy start-ups including Bloom Energy , a Technology Pioneer in 2010.

In the past two decades, tech start-ups have only expanded their climate focus. Many today are focuses on initiatives far beyond clean energy to slow the impact of climate change.

Different start-ups, including Carbon Engineering and Climeworks from this year’s Technology Pioneers, have started to roll out carbon capture technology. These technologies remove CO2 from the air directly, enabling scientists to alleviate some of the damage from fossil fuels which have already been burned.

Another expanding area for young tech firms today is food systems innovation. Many firms, like Aleph Farms and Air Protein, are creating innovative meat and dairy alternatives that are much greener than their traditional counterparts.

Biotech and healthcare

The early 2000s also saw the culmination of a biotech boom that had started in the mid-1990s. Many firms focused on advancing biotechnologies through enhanced tech research.

An early Technology Pioneer, Actelion Pharmaceuticals was one of these companies. Actelion’s tech researched the single layer of cells separating every blood vessel from the blood stream. Like many other biotech firms at the time, their focus was on precise disease and treatment research.

While many tech firms today still focus on disease and treatment research, many others have been focusing on healthcare delivery. Telehealth has been on the rise in recent years , with many young tech expanding virtual healthcare options. New technologies such as virtual visits, chatbots are being used to delivery healthcare to individuals, especially during Covid-19.

Many companies are also focusing their healthcare tech on patients, rather than doctors. For example Ada, a symptom checker app, used to be designed for doctor’s use but has now shifted its language and interface to prioritize giving patients information on their symptoms. Other companies, like 7 cups, are focused are offering mental healthcare support directly to their users without through their app instead of going through existing offices.

The past two decades have seen healthcare tech get much more personal and use tech for care delivery, not just advancing medical research.

The World Economic Forum was the first to draw the world’s attention to the Fourth Industrial Revolution, the current period of unprecedented change driven by rapid technological advances. Policies, norms and regulations have not been able to keep up with the pace of innovation, creating a growing need to fill this gap.

The Forum established the Centre for the Fourth Industrial Revolution Network in 2017 to ensure that new and emerging technologies will help—not harm—humanity in the future. Headquartered in San Francisco, the network launched centres in China, India and Japan in 2018 and is rapidly establishing locally-run Affiliate Centres in many countries around the world.

The global network is working closely with partners from government, business, academia and civil society to co-design and pilot agile frameworks for governing new and emerging technologies, including artificial intelligence (AI) , autonomous vehicles , blockchain , data policy , digital trade , drones , internet of things (IoT) , precision medicine and environmental innovations .

Learn more about the groundbreaking work that the Centre for the Fourth Industrial Revolution Network is doing to prepare us for the future.

Want to help us shape the Fourth Industrial Revolution? Contact us to find out how you can become a member or partner.

In the early 2000s, many companies were at the start of their recovery from the bursting dotcom bubble. Since then, we’ve seen a large expansion in the way tech innovators approach areas such as new media, climate change, healthcare delivery and more.

At the same time, we have also seen tech companies rise to the occasion of trying to combat issues which arose from the first group such as internet content moderation, expanding climate change solutions.

The Technology Pioneers' 2020 cohort marks the 20th anniversary of this community - and looking at the latest awardees can give us a snapshot of where the next two decades of tech may be heading.

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License and Republishing

World Economic Forum articles may be republished in accordance with the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License, and in accordance with our Terms of Use.

The views expressed in this article are those of the author alone and not the World Economic Forum.

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Essay Samples on Impact of Technology

Why parents should monitor children's internet access.

The rapid integration of technology into our lives has transformed the way children learn, socialize, and explore. With the virtual world becoming an integral part of childhood, the question of whether parents should monitor their children's internet access has gained prominence. This essay examines the...

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Should Parents Limit Screen Time: Analysis of the Argumentats

In an era defined by technology and digital connectivity, the question of whether parents should limit their children's screen time has become a subject of significant debate. As screens become a ubiquitous presence in daily life, concerns about their potential negative effects on children's physical,...

How Cell Phones Affect Our Lives

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Short About Negative Effects of Technology: A Closer Look

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The Positive and Negative Impact of Technology on Society

This essay weighs the advantages and disadvantages of technology in contemporary society, acknowledging the profound ways technology has reshaped our world, while advocating for a balanced and responsible approach to its use. Introduction As technology continues to evolve at an unprecedented rate, its effects on...

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Positive Effects of Technology: Enriching Lives and Shaping the Future

Introduction The evolution of technology has been one of the most transformative forces in human history. From the invention of the wheel to the development of the internet, technology has continually shaped our lives in countless ways. While discussions often focus on potential downsides of...

The Impact of Technology on Agriculture: A Transformative Force

Introduction The world of agriculture has seen a significant transformation in recent decades, largely due to advancements in technology. From the way farmers plant and nurture crops to the methods used to harvest and distribute products, technology has drastically altered the agricultural landscape. This essay...

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The Impact of Technology on Our Culture: A Transformative Influence

Introduction Technology has always been a significant driver of cultural change. From the invention of the printing press to the rise of the internet, technology has had profound and far-reaching impacts on our culture. It shapes how we communicate, work, learn, and engage with the...

• Culture and Communication

The Impact of Technology on Environment: A Complex Relationship

Introduction The relationship between technology and the environment is complex, encompassing both destructive and restorative dimensions. As society has developed increasingly sophisticated technologies, the environment has been altered in unprecedented ways. While technology has contributed to environmental degradation through pollution, resource depletion, and habitat loss,...

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The Impact of Technology on Art: A Modern Renaissance

Introduction The influence of technology on art is an evolving narrative that reflects the symbiotic relationship between human creativity and innovative tools. From the early use of simple tools to create cave paintings to the digital art technologies of today, the integration of technology in...

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The Way Technologies Transform Already Existing Art Forms

Compelling games are not the consequences of accidents, any more than are riveting novels, movies, or music. Creators for all these medias draw on well-established set of strategies and techniques to create a particular emotional experience. Musicians, for example, may create tension through reiteration and...

Analysis of Nicholas Carr's Article 'Is Google Making Us Stupid?'

Technology has a huge impact on everything. But the impact it has on literacy is even greater. According to Nicholas Carr in “Is Google Making Us Stupid?” summary essay Fredrick Nietzsche was becoming blind but wanted to continue writing so he bought a typewriter, the...

Discussion of Whether There Is a Positive Co-Existence Between Technology and Ecology

Our planet earth has seen some better days when we speak of technological revolution and advancements. This has harmed our ecology not once but several times. When our environment is harmed, we are the once who receive the impacts of that damage thereby prompting us...

Technology Makes Us Lonely: The Negatives of the Progress

There’s food on the table, with many people surrounding it ready to dig into a big family dinner, but wait everyone’s heads are down. What are they doing, are they praying, or are they really invested in a very lengthy book or Epic, like Beowulf?...

How Artificial Intelligence Will Change the Future of Work and Technology

We develop technology to replace our muscles. A lot of things has been replaced with the help of technology. 200 years ago 90% of the population involved in the agricultural sector by the invention and development in the machines industrial revolution has taken place most...

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Social Media and Technology Makes Us Lonely and Isolated

Technology has been the holy grail that has led to increased connectivity, new frontiers of business and economics and improved lives. On the other hand, it has also led to intense misery and contributed to the destruction of lives. Today, I will present facts and...

Debate on How Artificial Intelligence Will Change the Future

Introduction The hypothesis for this research paper is that artificial intelligence will change the future by impacting many aspects of people’s lives. Today, technology has become an essential part of every part of our lives. Automatic toasters make our breakfast, smartphones wake us up, and...

Technology Myth In "The Circle" By Dave Eggers

The Circle: The Technology Myth The novel begins on a glistening, sunlit day in June, Mae Holland cruises campus on her first-ever day at the Circle (Eggers, 1). The company is a creative and strongly favorite web organization, which has seized the globe by a...

What Makes Technology Good Or Bad

Technology has made incredible advancements in the past few years. It has made unimaginable things possible and it has changed the way humans live and connect. According to an article, published by Daily Mail, an average person spends 8 hours and 41 minutes on electronic...

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The Concept of Overcoming Technological Entrenchment in Society

The entrenchment of technology throughout society is a common and complex issue that is hindering and stunting the development and innovation of newer and arguably better technologies. Through retrospective viewing the paths of technological entrenchment are complex but evident, however, the foresight required at the...

British Petroleum Company and Its Use of Technology

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Extremely Negative Impact Of Technology Within Society

Technology plays a huge aspect in society nowadays, it’s inescapable. We’re constantly immersed in it, we constantly rely on it and we could not live without it. These points should be key signs that in the past few years’ technology is slowly beginning to have...

Parents Monitoring Teen's Internet Use: Is It Okay

Internet penetration across the world has shaped the communication sector. Currently, it is the most used medium of communication attributed with increased availability of Smartphones. In the U.S, 95% of teens have access to smartphones and at least nine out of ten access the internet...

Literary Analysis of the Article "Is Google Making Us Stupid"

“Have you heard: The average attention span [of Americans] is down from twelve seconds in the year 2000 to eight seconds now? That is less than the nine-second attention span of your average goldfish (Rachel Ainsworth).” In “Is Google Making us Stupid?,” Nicholas Carr states...

Technology Makes Life Easier: The Effects Of Technology

How Will Our Lives Be Changed By Technology Technologies can change our life in different kinds of ways. One of the ways are that we can use technology for communicating with each other. We can use social media or other apps to chat with other...

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The Impact Of Technology On Everyday Life: It Makes Life Easier

Technology has made a great impact as to how people involve with the world and as to how they spend their day-today lives. Few decades ago people did not know what exactly technology is and today technology has made people educated of what technology is...

How Technology Improves The Quality Of Life

Nowadays, technology is closely linked to the life of every human being because it facilitates and optimizes most of the activities that are performed daily. Besides, technology makes great contributions to society, making it safer and more functional. Without technology, the world would not be...

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Text-speak Is Harming Students

Did you know, the first text message was sent from a computer in December 1933. It said “Merry Christmas”. Text-speak wasn’t used in this text but it is used in many. Text speak is when someone uses shortened words like gr8 instead of great or...

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The Importance of Camera Technology in the Modern World

The camera, a technology incorporated into many aspects of our lives today, is one of the world's most influential and significant objects in modern culture and society. Reflecting on how the camera has evolved over time, it has surpassed its initial vision and expectations. It...

The Negative Effects of Cell Phones on the Health and Real Life Communications

Cell phone use is one of the greatest inventions of the 20th -century. Cell phones are something we can’t live without. The fact that this technology that we call the cell phones provides us with tons of functions, among which the most valuable one is...

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The Benefits of Using Cell Phones in Class as a Study Tool

In this current generation, cell phones have made an impact on our lives. Cell phones a generally used more with the younger generation, which usually leads to the use of phones during school. Phones can be used to help with educational purposes and studying. They...

How Emotions Received from Technology Can Trigger Flashbulb Memory

Memory never works alone, there are always some emotions involved which can be positive and negative at the same time. Emotions are strong feelings that come from someone’s circumstances, mood, or relationship with others or even oneself. Memory is in the hippocampus, the amygdala, and...

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What Drives a Person to be a Villain

Society today runs on technology, therefore technology is a medium that can be used by villains as a tool for their actions. In “Electric Funeral, ” Chuck Klosterman considers the idea of villainy, specifically in regard to the inevitability of technological progress. Klosterman argues that...

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M.T. Anderson's Book Feed: Letting Technologies Become an Irreplaceable Part of Our Lives

“Feed” a transmitter implanted into the heads of people. Feeds are a crucial part of life for Titus and his friends. Feed takes places in the near-future where media is always with you. Almost everyone has the tiny device implanted into their brain which corporations...

The Topic of Technology Replacing Humans in "Wall-E"

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How artificial intelligence is transforming the world

Subscribe to techstream, darrell m. west and darrell m. west senior fellow - center for technology innovation , douglas dillon chair in governmental studies john r. allen john r. allen.

April 24, 2018

Artificial intelligence (AI) is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decision making—and already it is transforming every walk of life. In this report, Darrell West and John Allen discuss AI’s application across a variety of sectors, address issues in its development, and offer recommendations for getting the most out of AI while still protecting important human values.

Table of Contents I. Qualities of artificial intelligence II. Applications in diverse sectors III. Policy, regulatory, and ethical issues IV. Recommendations V. Conclusion

• 49 min read

Most people are not very familiar with the concept of artificial intelligence (AI). As an illustration, when 1,500 senior business leaders in the United States in 2017 were asked about AI, only 17 percent said they were familiar with it. 1 A number of them were not sure what it was or how it would affect their particular companies. They understood there was considerable potential for altering business processes, but were not clear how AI could be deployed within their own organizations.

Despite its widespread lack of familiarity, AI is a technology that is transforming every walk of life. It is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decisionmaking. Our hope through this comprehensive overview is to explain AI to an audience of policymakers, opinion leaders, and interested observers, and demonstrate how AI already is altering the world and raising important questions for society, the economy, and governance.

In this paper, we discuss novel applications in finance, national security, health care, criminal justice, transportation, and smart cities, and address issues such as data access problems, algorithmic bias, AI ethics and transparency, and legal liability for AI decisions. We contrast the regulatory approaches of the U.S. and European Union, and close by making a number of recommendations for getting the most out of AI while still protecting important human values. 2

In order to maximize AI benefits, we recommend nine steps for going forward:

• Encourage greater data access for researchers without compromising users’ personal privacy,
• invest more government funding in unclassified AI research,
• promote new models of digital education and AI workforce development so employees have the skills needed in the 21 st -century economy,
• create a federal AI advisory committee to make policy recommendations,
• engage with state and local officials so they enact effective policies,
• regulate broad AI principles rather than specific algorithms,
• take bias complaints seriously so AI does not replicate historic injustice, unfairness, or discrimination in data or algorithms,
• maintain mechanisms for human oversight and control, and
• penalize malicious AI behavior and promote cybersecurity.

Qualities of artificial intelligence

Although there is no uniformly agreed upon definition, AI generally is thought to refer to “machines that respond to stimulation consistent with traditional responses from humans, given the human capacity for contemplation, judgment and intention.” 3  According to researchers Shubhendu and Vijay, these software systems “make decisions which normally require [a] human level of expertise” and help people anticipate problems or deal with issues as they come up. 4 As such, they operate in an intentional, intelligent, and adaptive manner.

Intentionality

Artificial intelligence algorithms are designed to make decisions, often using real-time data. They are unlike passive machines that are capable only of mechanical or predetermined responses. Using sensors, digital data, or remote inputs, they combine information from a variety of different sources, analyze the material instantly, and act on the insights derived from those data. With massive improvements in storage systems, processing speeds, and analytic techniques, they are capable of tremendous sophistication in analysis and decisionmaking.

Artificial intelligence is already altering the world and raising important questions for society, the economy, and governance.

Intelligence

AI generally is undertaken in conjunction with machine learning and data analytics. 5 Machine learning takes data and looks for underlying trends. If it spots something that is relevant for a practical problem, software designers can take that knowledge and use it to analyze specific issues. All that is required are data that are sufficiently robust that algorithms can discern useful patterns. Data can come in the form of digital information, satellite imagery, visual information, text, or unstructured data.

Adaptability

AI systems have the ability to learn and adapt as they make decisions. In the transportation area, for example, semi-autonomous vehicles have tools that let drivers and vehicles know about upcoming congestion, potholes, highway construction, or other possible traffic impediments. Vehicles can take advantage of the experience of other vehicles on the road, without human involvement, and the entire corpus of their achieved “experience” is immediately and fully transferable to other similarly configured vehicles. Their advanced algorithms, sensors, and cameras incorporate experience in current operations, and use dashboards and visual displays to present information in real time so human drivers are able to make sense of ongoing traffic and vehicular conditions. And in the case of fully autonomous vehicles, advanced systems can completely control the car or truck, and make all the navigational decisions.

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Applications in diverse sectors

AI is not a futuristic vision, but rather something that is here today and being integrated with and deployed into a variety of sectors. This includes fields such as finance, national security, health care, criminal justice, transportation, and smart cities. There are numerous examples where AI already is making an impact on the world and augmenting human capabilities in significant ways. 6

One of the reasons for the growing role of AI is the tremendous opportunities for economic development that it presents. A project undertaken by PriceWaterhouseCoopers estimated that “artificial intelligence technologies could increase global GDP by $15.7 trillion, a full 14%, by 2030.” 7 That includes advances of $7 trillion in China, $3.7 trillion in North America, $1.8 trillion in Northern Europe, $1.2 trillion for Africa and Oceania, $0.9 trillion in the rest of Asia outside of China, $0.7 trillion in Southern Europe, and $0.5 trillion in Latin America. China is making rapid strides because it has set a national goal of investing $150 billion in AI and becoming the global leader in this area by 2030.

Meanwhile, a McKinsey Global Institute study of China found that “AI-led automation can give the Chinese economy a productivity injection that would add 0.8 to 1.4 percentage points to GDP growth annually, depending on the speed of adoption.” 8 Although its authors found that China currently lags the United States and the United Kingdom in AI deployment, the sheer size of its AI market gives that country tremendous opportunities for pilot testing and future development.

Investments in financial AI in the United States tripled between 2013 and 2014 to a total of $12.2 billion. 9 According to observers in that sector, “Decisions about loans are now being made by software that can take into account a variety of finely parsed data about a borrower, rather than just a credit score and a background check.” 10 In addition, there are so-called robo-advisers that “create personalized investment portfolios, obviating the need for stockbrokers and financial advisers.” 11 These advances are designed to take the emotion out of investing and undertake decisions based on analytical considerations, and make these choices in a matter of minutes.

A prominent example of this is taking place in stock exchanges, where high-frequency trading by machines has replaced much of human decisionmaking. People submit buy and sell orders, and computers match them in the blink of an eye without human intervention. Machines can spot trading inefficiencies or market differentials on a very small scale and execute trades that make money according to investor instructions. 12 Powered in some places by advanced computing, these tools have much greater capacities for storing information because of their emphasis not on a zero or a one, but on “quantum bits” that can store multiple values in each location. 13 That dramatically increases storage capacity and decreases processing times.

Fraud detection represents another way AI is helpful in financial systems. It sometimes is difficult to discern fraudulent activities in large organizations, but AI can identify abnormalities, outliers, or deviant cases requiring additional investigation. That helps managers find problems early in the cycle, before they reach dangerous levels. 14

National security

AI plays a substantial role in national defense. Through its Project Maven, the American military is deploying AI “to sift through the massive troves of data and video captured by surveillance and then alert human analysts of patterns or when there is abnormal or suspicious activity.” 15 According to Deputy Secretary of Defense Patrick Shanahan, the goal of emerging technologies in this area is “to meet our warfighters’ needs and to increase [the] speed and agility [of] technology development and procurement.” 16

Artificial intelligence will accelerate the traditional process of warfare so rapidly that a new term has been coined: hyperwar.

The big data analytics associated with AI will profoundly affect intelligence analysis, as massive amounts of data are sifted in near real time—if not eventually in real time—thereby providing commanders and their staffs a level of intelligence analysis and productivity heretofore unseen. Command and control will similarly be affected as human commanders delegate certain routine, and in special circumstances, key decisions to AI platforms, reducing dramatically the time associated with the decision and subsequent action. In the end, warfare is a time competitive process, where the side able to decide the fastest and move most quickly to execution will generally prevail. Indeed, artificially intelligent intelligence systems, tied to AI-assisted command and control systems, can move decision support and decisionmaking to a speed vastly superior to the speeds of the traditional means of waging war. So fast will be this process, especially if coupled to automatic decisions to launch artificially intelligent autonomous weapons systems capable of lethal outcomes, that a new term has been coined specifically to embrace the speed at which war will be waged: hyperwar.

While the ethical and legal debate is raging over whether America will ever wage war with artificially intelligent autonomous lethal systems, the Chinese and Russians are not nearly so mired in this debate, and we should anticipate our need to defend against these systems operating at hyperwar speeds. The challenge in the West of where to position “humans in the loop” in a hyperwar scenario will ultimately dictate the West’s capacity to be competitive in this new form of conflict. 17

Just as AI will profoundly affect the speed of warfare, the proliferation of zero day or zero second cyber threats as well as polymorphic malware will challenge even the most sophisticated signature-based cyber protection. This forces significant improvement to existing cyber defenses. Increasingly, vulnerable systems are migrating, and will need to shift to a layered approach to cybersecurity with cloud-based, cognitive AI platforms. This approach moves the community toward a “thinking” defensive capability that can defend networks through constant training on known threats. This capability includes DNA-level analysis of heretofore unknown code, with the possibility of recognizing and stopping inbound malicious code by recognizing a string component of the file. This is how certain key U.S.-based systems stopped the debilitating “WannaCry” and “Petya” viruses.

Preparing for hyperwar and defending critical cyber networks must become a high priority because China, Russia, North Korea, and other countries are putting substantial resources into AI. In 2017, China’s State Council issued a plan for the country to “build a domestic industry worth almost $150 billion” by 2030. 18 As an example of the possibilities, the Chinese search firm Baidu has pioneered a facial recognition application that finds missing people. In addition, cities such as Shenzhen are providing up to $1 million to support AI labs. That country hopes AI will provide security, combat terrorism, and improve speech recognition programs. 19 The dual-use nature of many AI algorithms will mean AI research focused on one sector of society can be rapidly modified for use in the security sector as well. 20

Health care

AI tools are helping designers improve computational sophistication in health care. For example, Merantix is a German company that applies deep learning to medical issues. It has an application in medical imaging that “detects lymph nodes in the human body in Computer Tomography (CT) images.” 21 According to its developers, the key is labeling the nodes and identifying small lesions or growths that could be problematic. Humans can do this, but radiologists charge $100 per hour and may be able to carefully read only four images an hour. If there were 10,000 images, the cost of this process would be $250,000, which is prohibitively expensive if done by humans.

What deep learning can do in this situation is train computers on data sets to learn what a normal-looking versus an irregular-appearing lymph node is. After doing that through imaging exercises and honing the accuracy of the labeling, radiological imaging specialists can apply this knowledge to actual patients and determine the extent to which someone is at risk of cancerous lymph nodes. Since only a few are likely to test positive, it is a matter of identifying the unhealthy versus healthy node.

AI has been applied to congestive heart failure as well, an illness that afflicts 10 percent of senior citizens and costs $35 billion each year in the United States. AI tools are helpful because they “predict in advance potential challenges ahead and allocate resources to patient education, sensing, and proactive interventions that keep patients out of the hospital.” 22

Criminal justice

AI is being deployed in the criminal justice area. The city of Chicago has developed an AI-driven “Strategic Subject List” that analyzes people who have been arrested for their risk of becoming future perpetrators. It ranks 400,000 people on a scale of 0 to 500, using items such as age, criminal activity, victimization, drug arrest records, and gang affiliation. In looking at the data, analysts found that youth is a strong predictor of violence, being a shooting victim is associated with becoming a future perpetrator, gang affiliation has little predictive value, and drug arrests are not significantly associated with future criminal activity. 23

Judicial experts claim AI programs reduce human bias in law enforcement and leads to a fairer sentencing system. R Street Institute Associate Caleb Watney writes:

Empirically grounded questions of predictive risk analysis play to the strengths of machine learning, automated reasoning and other forms of AI. One machine-learning policy simulation concluded that such programs could be used to cut crime up to 24.8 percent with no change in jailing rates, or reduce jail populations by up to 42 percent with no increase in crime rates. 24

However, critics worry that AI algorithms represent “a secret system to punish citizens for crimes they haven’t yet committed. The risk scores have been used numerous times to guide large-scale roundups.” 25 The fear is that such tools target people of color unfairly and have not helped Chicago reduce the murder wave that has plagued it in recent years.

Despite these concerns, other countries are moving ahead with rapid deployment in this area. In China, for example, companies already have “considerable resources and access to voices, faces and other biometric data in vast quantities, which would help them develop their technologies.” 26 New technologies make it possible to match images and voices with other types of information, and to use AI on these combined data sets to improve law enforcement and national security. Through its “Sharp Eyes” program, Chinese law enforcement is matching video images, social media activity, online purchases, travel records, and personal identity into a “police cloud.” This integrated database enables authorities to keep track of criminals, potential law-breakers, and terrorists. 27 Put differently, China has become the world’s leading AI-powered surveillance state.

Transportation

Transportation represents an area where AI and machine learning are producing major innovations. Research by Cameron Kerry and Jack Karsten of the Brookings Institution has found that over $80 billion was invested in autonomous vehicle technology between August 2014 and June 2017. Those investments include applications both for autonomous driving and the core technologies vital to that sector. 28

Autonomous vehicles—cars, trucks, buses, and drone delivery systems—use advanced technological capabilities. Those features include automated vehicle guidance and braking, lane-changing systems, the use of cameras and sensors for collision avoidance, the use of AI to analyze information in real time, and the use of high-performance computing and deep learning systems to adapt to new circumstances through detailed maps. 29

Light detection and ranging systems (LIDARs) and AI are key to navigation and collision avoidance. LIDAR systems combine light and radar instruments. They are mounted on the top of vehicles that use imaging in a 360-degree environment from a radar and light beams to measure the speed and distance of surrounding objects. Along with sensors placed on the front, sides, and back of the vehicle, these instruments provide information that keeps fast-moving cars and trucks in their own lane, helps them avoid other vehicles, applies brakes and steering when needed, and does so instantly so as to avoid accidents.

Advanced software enables cars to learn from the experiences of other vehicles on the road and adjust their guidance systems as weather, driving, or road conditions change. This means that software is the key—not the physical car or truck itself.

Since these cameras and sensors compile a huge amount of information and need to process it instantly to avoid the car in the next lane, autonomous vehicles require high-performance computing, advanced algorithms, and deep learning systems to adapt to new scenarios. This means that software is the key, not the physical car or truck itself. 30 Advanced software enables cars to learn from the experiences of other vehicles on the road and adjust their guidance systems as weather, driving, or road conditions change. 31

Ride-sharing companies are very interested in autonomous vehicles. They see advantages in terms of customer service and labor productivity. All of the major ride-sharing companies are exploring driverless cars. The surge of car-sharing and taxi services—such as Uber and Lyft in the United States, Daimler’s Mytaxi and Hailo service in Great Britain, and Didi Chuxing in China—demonstrate the opportunities of this transportation option. Uber recently signed an agreement to purchase 24,000 autonomous cars from Volvo for its ride-sharing service. 32

However, the ride-sharing firm suffered a setback in March 2018 when one of its autonomous vehicles in Arizona hit and killed a pedestrian. Uber and several auto manufacturers immediately suspended testing and launched investigations into what went wrong and how the fatality could have occurred. 33 Both industry and consumers want reassurance that the technology is safe and able to deliver on its stated promises. Unless there are persuasive answers, this accident could slow AI advancements in the transportation sector.

Smart cities

Metropolitan governments are using AI to improve urban service delivery. For example, according to Kevin Desouza, Rashmi Krishnamurthy, and Gregory Dawson:

The Cincinnati Fire Department is using data analytics to optimize medical emergency responses. The new analytics system recommends to the dispatcher an appropriate response to a medical emergency call—whether a patient can be treated on-site or needs to be taken to the hospital—by taking into account several factors, such as the type of call, location, weather, and similar calls. 34

Since it fields 80,000 requests each year, Cincinnati officials are deploying this technology to prioritize responses and determine the best ways to handle emergencies. They see AI as a way to deal with large volumes of data and figure out efficient ways of responding to public requests. Rather than address service issues in an ad hoc manner, authorities are trying to be proactive in how they provide urban services.

Cincinnati is not alone. A number of metropolitan areas are adopting smart city applications that use AI to improve service delivery, environmental planning, resource management, energy utilization, and crime prevention, among other things. For its smart cities index, the magazine Fast Company ranked American locales and found Seattle, Boston, San Francisco, Washington, D.C., and New York City as the top adopters. Seattle, for example, has embraced sustainability and is using AI to manage energy usage and resource management. Boston has launched a “City Hall To Go” that makes sure underserved communities receive needed public services. It also has deployed “cameras and inductive loops to manage traffic and acoustic sensors to identify gun shots.” San Francisco has certified 203 buildings as meeting LEED sustainability standards. 35

Through these and other means, metropolitan areas are leading the country in the deployment of AI solutions. Indeed, according to a National League of Cities report, 66 percent of American cities are investing in smart city technology. Among the top applications noted in the report are “smart meters for utilities, intelligent traffic signals, e-governance applications, Wi-Fi kiosks, and radio frequency identification sensors in pavement.” 36

Policy, regulatory, and ethical issues

These examples from a variety of sectors demonstrate how AI is transforming many walks of human existence. The increasing penetration of AI and autonomous devices into many aspects of life is altering basic operations and decisionmaking within organizations, and improving efficiency and response times.

At the same time, though, these developments raise important policy, regulatory, and ethical issues. For example, how should we promote data access? How do we guard against biased or unfair data used in algorithms? What types of ethical principles are introduced through software programming, and how transparent should designers be about their choices? What about questions of legal liability in cases where algorithms cause harm? 37

The increasing penetration of AI into many aspects of life is altering decisionmaking within organizations and improving efficiency. At the same time, though, these developments raise important policy, regulatory, and ethical issues.

Data access problems

The key to getting the most out of AI is having a “data-friendly ecosystem with unified standards and cross-platform sharing.” AI depends on data that can be analyzed in real time and brought to bear on concrete problems. Having data that are “accessible for exploration” in the research community is a prerequisite for successful AI development. 38

According to a McKinsey Global Institute study, nations that promote open data sources and data sharing are the ones most likely to see AI advances. In this regard, the United States has a substantial advantage over China. Global ratings on data openness show that U.S. ranks eighth overall in the world, compared to 93 for China. 39

But right now, the United States does not have a coherent national data strategy. There are few protocols for promoting research access or platforms that make it possible to gain new insights from proprietary data. It is not always clear who owns data or how much belongs in the public sphere. These uncertainties limit the innovation economy and act as a drag on academic research. In the following section, we outline ways to improve data access for researchers.

Biases in data and algorithms

In some instances, certain AI systems are thought to have enabled discriminatory or biased practices. 40 For example, Airbnb has been accused of having homeowners on its platform who discriminate against racial minorities. A research project undertaken by the Harvard Business School found that “Airbnb users with distinctly African American names were roughly 16 percent less likely to be accepted as guests than those with distinctly white names.” 41

Racial issues also come up with facial recognition software. Most such systems operate by comparing a person’s face to a range of faces in a large database. As pointed out by Joy Buolamwini of the Algorithmic Justice League, “If your facial recognition data contains mostly Caucasian faces, that’s what your program will learn to recognize.” 42 Unless the databases have access to diverse data, these programs perform poorly when attempting to recognize African-American or Asian-American features.

Many historical data sets reflect traditional values, which may or may not represent the preferences wanted in a current system. As Buolamwini notes, such an approach risks repeating inequities of the past:

The rise of automation and the increased reliance on algorithms for high-stakes decisions such as whether someone get insurance or not, your likelihood to default on a loan or somebody’s risk of recidivism means this is something that needs to be addressed. Even admissions decisions are increasingly automated—what school our children go to and what opportunities they have. We don’t have to bring the structural inequalities of the past into the future we create. 43

AI ethics and transparency

Algorithms embed ethical considerations and value choices into program decisions. As such, these systems raise questions concerning the criteria used in automated decisionmaking. Some people want to have a better understanding of how algorithms function and what choices are being made. 44

In the United States, many urban schools use algorithms for enrollment decisions based on a variety of considerations, such as parent preferences, neighborhood qualities, income level, and demographic background. According to Brookings researcher Jon Valant, the New Orleans–based Bricolage Academy “gives priority to economically disadvantaged applicants for up to 33 percent of available seats. In practice, though, most cities have opted for categories that prioritize siblings of current students, children of school employees, and families that live in school’s broad geographic area.” 45 Enrollment choices can be expected to be very different when considerations of this sort come into play.

Depending on how AI systems are set up, they can facilitate the redlining of mortgage applications, help people discriminate against individuals they don’t like, or help screen or build rosters of individuals based on unfair criteria. The types of considerations that go into programming decisions matter a lot in terms of how the systems operate and how they affect customers. 46

For these reasons, the EU is implementing the General Data Protection Regulation (GDPR) in May 2018. The rules specify that people have “the right to opt out of personally tailored ads” and “can contest ‘legal or similarly significant’ decisions made by algorithms and appeal for human intervention” in the form of an explanation of how the algorithm generated a particular outcome. Each guideline is designed to ensure the protection of personal data and provide individuals with information on how the “black box” operates. 47

Legal liability

There are questions concerning the legal liability of AI systems. If there are harms or infractions (or fatalities in the case of driverless cars), the operators of the algorithm likely will fall under product liability rules. A body of case law has shown that the situation’s facts and circumstances determine liability and influence the kind of penalties that are imposed. Those can range from civil fines to imprisonment for major harms. 48 The Uber-related fatality in Arizona will be an important test case for legal liability. The state actively recruited Uber to test its autonomous vehicles and gave the company considerable latitude in terms of road testing. It remains to be seen if there will be lawsuits in this case and who is sued: the human backup driver, the state of Arizona, the Phoenix suburb where the accident took place, Uber, software developers, or the auto manufacturer. Given the multiple people and organizations involved in the road testing, there are many legal questions to be resolved.

In non-transportation areas, digital platforms often have limited liability for what happens on their sites. For example, in the case of Airbnb, the firm “requires that people agree to waive their right to sue, or to join in any class-action lawsuit or class-action arbitration, to use the service.” By demanding that its users sacrifice basic rights, the company limits consumer protections and therefore curtails the ability of people to fight discrimination arising from unfair algorithms. 49 But whether the principle of neutral networks holds up in many sectors is yet to be determined on a widespread basis.

Recommendations

In order to balance innovation with basic human values, we propose a number of recommendations for moving forward with AI. This includes improving data access, increasing government investment in AI, promoting AI workforce development, creating a federal advisory committee, engaging with state and local officials to ensure they enact effective policies, regulating broad objectives as opposed to specific algorithms, taking bias seriously as an AI issue, maintaining mechanisms for human control and oversight, and penalizing malicious behavior and promoting cybersecurity.

Improving data access

The United States should develop a data strategy that promotes innovation and consumer protection. Right now, there are no uniform standards in terms of data access, data sharing, or data protection. Almost all the data are proprietary in nature and not shared very broadly with the research community, and this limits innovation and system design. AI requires data to test and improve its learning capacity. 50 Without structured and unstructured data sets, it will be nearly impossible to gain the full benefits of artificial intelligence.

In general, the research community needs better access to government and business data, although with appropriate safeguards to make sure researchers do not misuse data in the way Cambridge Analytica did with Facebook information. There is a variety of ways researchers could gain data access. One is through voluntary agreements with companies holding proprietary data. Facebook, for example, recently announced a partnership with Stanford economist Raj Chetty to use its social media data to explore inequality. 51 As part of the arrangement, researchers were required to undergo background checks and could only access data from secured sites in order to protect user privacy and security.

In the U.S., there are no uniform standards in terms of data access, data sharing, or data protection. Almost all the data are proprietary in nature and not shared very broadly with the research community, and this limits innovation and system design.

Google long has made available search results in aggregated form for researchers and the general public. Through its “Trends” site, scholars can analyze topics such as interest in Trump, views about democracy, and perspectives on the overall economy. 52 That helps people track movements in public interest and identify topics that galvanize the general public.

Twitter makes much of its tweets available to researchers through application programming interfaces, commonly referred to as APIs. These tools help people outside the company build application software and make use of data from its social media platform. They can study patterns of social media communications and see how people are commenting on or reacting to current events.

In some sectors where there is a discernible public benefit, governments can facilitate collaboration by building infrastructure that shares data. For example, the National Cancer Institute has pioneered a data-sharing protocol where certified researchers can query health data it has using de-identified information drawn from clinical data, claims information, and drug therapies. That enables researchers to evaluate efficacy and effectiveness, and make recommendations regarding the best medical approaches, without compromising the privacy of individual patients.

There could be public-private data partnerships that combine government and business data sets to improve system performance. For example, cities could integrate information from ride-sharing services with its own material on social service locations, bus lines, mass transit, and highway congestion to improve transportation. That would help metropolitan areas deal with traffic tie-ups and assist in highway and mass transit planning.

Some combination of these approaches would improve data access for researchers, the government, and the business community, without impinging on personal privacy. As noted by Ian Buck, the vice president of NVIDIA, “Data is the fuel that drives the AI engine. The federal government has access to vast sources of information. Opening access to that data will help us get insights that will transform the U.S. economy.” 53 Through its Data.gov portal, the federal government already has put over 230,000 data sets into the public domain, and this has propelled innovation and aided improvements in AI and data analytic technologies. 54 The private sector also needs to facilitate research data access so that society can achieve the full benefits of artificial intelligence.

Increase government investment in AI

According to Greg Brockman, the co-founder of OpenAI, the U.S. federal government invests only $1.1 billion in non-classified AI technology. 55 That is far lower than the amount being spent by China or other leading nations in this area of research. That shortfall is noteworthy because the economic payoffs of AI are substantial. In order to boost economic development and social innovation, federal officials need to increase investment in artificial intelligence and data analytics. Higher investment is likely to pay for itself many times over in economic and social benefits. 56

Promote digital education and workforce development

As AI applications accelerate across many sectors, it is vital that we reimagine our educational institutions for a world where AI will be ubiquitous and students need a different kind of training than they currently receive. Right now, many students do not receive instruction in the kinds of skills that will be needed in an AI-dominated landscape. For example, there currently are shortages of data scientists, computer scientists, engineers, coders, and platform developers. These are skills that are in short supply; unless our educational system generates more people with these capabilities, it will limit AI development.

For these reasons, both state and federal governments have been investing in AI human capital. For example, in 2017, the National Science Foundation funded over 6,500 graduate students in computer-related fields and has launched several new initiatives designed to encourage data and computer science at all levels from pre-K to higher and continuing education. 57 The goal is to build a larger pipeline of AI and data analytic personnel so that the United States can reap the full advantages of the knowledge revolution.

But there also needs to be substantial changes in the process of learning itself. It is not just technical skills that are needed in an AI world but skills of critical reasoning, collaboration, design, visual display of information, and independent thinking, among others. AI will reconfigure how society and the economy operate, and there needs to be “big picture” thinking on what this will mean for ethics, governance, and societal impact. People will need the ability to think broadly about many questions and integrate knowledge from a number of different areas.

One example of new ways to prepare students for a digital future is IBM’s Teacher Advisor program, utilizing Watson’s free online tools to help teachers bring the latest knowledge into the classroom. They enable instructors to develop new lesson plans in STEM and non-STEM fields, find relevant instructional videos, and help students get the most out of the classroom. 58 As such, they are precursors of new educational environments that need to be created.

Create a federal AI advisory committee

Federal officials need to think about how they deal with artificial intelligence. As noted previously, there are many issues ranging from the need for improved data access to addressing issues of bias and discrimination. It is vital that these and other concerns be considered so we gain the full benefits of this emerging technology.

In order to move forward in this area, several members of Congress have introduced the “Future of Artificial Intelligence Act,” a bill designed to establish broad policy and legal principles for AI. It proposes the secretary of commerce create a federal advisory committee on the development and implementation of artificial intelligence. The legislation provides a mechanism for the federal government to get advice on ways to promote a “climate of investment and innovation to ensure the global competitiveness of the United States,” “optimize the development of artificial intelligence to address the potential growth, restructuring, or other changes in the United States workforce,” “support the unbiased development and application of artificial intelligence,” and “protect the privacy rights of individuals.” 59

Among the specific questions the committee is asked to address include the following: competitiveness, workforce impact, education, ethics training, data sharing, international cooperation, accountability, machine learning bias, rural impact, government efficiency, investment climate, job impact, bias, and consumer impact. The committee is directed to submit a report to Congress and the administration 540 days after enactment regarding any legislative or administrative action needed on AI.

This legislation is a step in the right direction, although the field is moving so rapidly that we would recommend shortening the reporting timeline from 540 days to 180 days. Waiting nearly two years for a committee report will certainly result in missed opportunities and a lack of action on important issues. Given rapid advances in the field, having a much quicker turnaround time on the committee analysis would be quite beneficial.

Engage with state and local officials

States and localities also are taking action on AI. For example, the New York City Council unanimously passed a bill that directed the mayor to form a taskforce that would “monitor the fairness and validity of algorithms used by municipal agencies.” 60 The city employs algorithms to “determine if a lower bail will be assigned to an indigent defendant, where firehouses are established, student placement for public schools, assessing teacher performance, identifying Medicaid fraud and determine where crime will happen next.” 61

According to the legislation’s developers, city officials want to know how these algorithms work and make sure there is sufficient AI transparency and accountability. In addition, there is concern regarding the fairness and biases of AI algorithms, so the taskforce has been directed to analyze these issues and make recommendations regarding future usage. It is scheduled to report back to the mayor on a range of AI policy, legal, and regulatory issues by late 2019.

Some observers already are worrying that the taskforce won’t go far enough in holding algorithms accountable. For example, Julia Powles of Cornell Tech and New York University argues that the bill originally required companies to make the AI source code available to the public for inspection, and that there be simulations of its decisionmaking using actual data. After criticism of those provisions, however, former Councilman James Vacca dropped the requirements in favor of a task force studying these issues. He and other city officials were concerned that publication of proprietary information on algorithms would slow innovation and make it difficult to find AI vendors who would work with the city. 62 It remains to be seen how this local task force will balance issues of innovation, privacy, and transparency.

Regulate broad objectives more than specific algorithms

The European Union has taken a restrictive stance on these issues of data collection and analysis. 63 It has rules limiting the ability of companies from collecting data on road conditions and mapping street views. Because many of these countries worry that people’s personal information in unencrypted Wi-Fi networks are swept up in overall data collection, the EU has fined technology firms, demanded copies of data, and placed limits on the material collected. 64 This has made it more difficult for technology companies operating there to develop the high-definition maps required for autonomous vehicles.

The GDPR being implemented in Europe place severe restrictions on the use of artificial intelligence and machine learning. According to published guidelines, “Regulations prohibit any automated decision that ‘significantly affects’ EU citizens. This includes techniques that evaluates a person’s ‘performance at work, economic situation, health, personal preferences, interests, reliability, behavior, location, or movements.’” 65 In addition, these new rules give citizens the right to review how digital services made specific algorithmic choices affecting people.

By taking a restrictive stance on issues of data collection and analysis, the European Union is putting its manufacturers and software designers at a significant disadvantage to the rest of the world.

If interpreted stringently, these rules will make it difficult for European software designers (and American designers who work with European counterparts) to incorporate artificial intelligence and high-definition mapping in autonomous vehicles. Central to navigation in these cars and trucks is tracking location and movements. Without high-definition maps containing geo-coded data and the deep learning that makes use of this information, fully autonomous driving will stagnate in Europe. Through this and other data protection actions, the European Union is putting its manufacturers and software designers at a significant disadvantage to the rest of the world.

It makes more sense to think about the broad objectives desired in AI and enact policies that advance them, as opposed to governments trying to crack open the “black boxes” and see exactly how specific algorithms operate. Regulating individual algorithms will limit innovation and make it difficult for companies to make use of artificial intelligence.

Take biases seriously

Bias and discrimination are serious issues for AI. There already have been a number of cases of unfair treatment linked to historic data, and steps need to be undertaken to make sure that does not become prevalent in artificial intelligence. Existing statutes governing discrimination in the physical economy need to be extended to digital platforms. That will help protect consumers and build confidence in these systems as a whole.

For these advances to be widely adopted, more transparency is needed in how AI systems operate. Andrew Burt of Immuta argues, “The key problem confronting predictive analytics is really transparency. We’re in a world where data science operations are taking on increasingly important tasks, and the only thing holding them back is going to be how well the data scientists who train the models can explain what it is their models are doing.” 66

Maintaining mechanisms for human oversight and control

Some individuals have argued that there needs to be avenues for humans to exercise oversight and control of AI systems. For example, Allen Institute for Artificial Intelligence CEO Oren Etzioni argues there should be rules for regulating these systems. First, he says, AI must be governed by all the laws that already have been developed for human behavior, including regulations concerning “cyberbullying, stock manipulation or terrorist threats,” as well as “entrap[ping] people into committing crimes.” Second, he believes that these systems should disclose they are automated systems and not human beings. Third, he states, “An A.I. system cannot retain or disclose confidential information without explicit approval from the source of that information.” 67 His rationale is that these tools store so much data that people have to be cognizant of the privacy risks posed by AI.

In the same vein, the IEEE Global Initiative has ethical guidelines for AI and autonomous systems. Its experts suggest that these models be programmed with consideration for widely accepted human norms and rules for behavior. AI algorithms need to take into effect the importance of these norms, how norm conflict can be resolved, and ways these systems can be transparent about norm resolution. Software designs should be programmed for “nondeception” and “honesty,” according to ethics experts. When failures occur, there must be mitigation mechanisms to deal with the consequences. In particular, AI must be sensitive to problems such as bias, discrimination, and fairness. 68

A group of machine learning experts claim it is possible to automate ethical decisionmaking. Using the trolley problem as a moral dilemma, they ask the following question: If an autonomous car goes out of control, should it be programmed to kill its own passengers or the pedestrians who are crossing the street? They devised a “voting-based system” that asked 1.3 million people to assess alternative scenarios, summarized the overall choices, and applied the overall perspective of these individuals to a range of vehicular possibilities. That allowed them to automate ethical decisionmaking in AI algorithms, taking public preferences into account. 69 This procedure, of course, does not reduce the tragedy involved in any kind of fatality, such as seen in the Uber case, but it provides a mechanism to help AI developers incorporate ethical considerations in their planning.

Penalize malicious behavior and promote cybersecurity

As with any emerging technology, it is important to discourage malicious treatment designed to trick software or use it for undesirable ends. 70 This is especially important given the dual-use aspects of AI, where the same tool can be used for beneficial or malicious purposes. The malevolent use of AI exposes individuals and organizations to unnecessary risks and undermines the virtues of the emerging technology. This includes behaviors such as hacking, manipulating algorithms, compromising privacy and confidentiality, or stealing identities. Efforts to hijack AI in order to solicit confidential information should be seriously penalized as a way to deter such actions. 71

In a rapidly changing world with many entities having advanced computing capabilities, there needs to be serious attention devoted to cybersecurity. Countries have to be careful to safeguard their own systems and keep other nations from damaging their security. 72 According to the U.S. Department of Homeland Security, a major American bank receives around 11 million calls a week at its service center. In order to protect its telephony from denial of service attacks, it uses a “machine learning-based policy engine [that] blocks more than 120,000 calls per month based on voice firewall policies including harassing callers, robocalls and potential fraudulent calls.” 73 This represents a way in which machine learning can help defend technology systems from malevolent attacks.

To summarize, the world is on the cusp of revolutionizing many sectors through artificial intelligence and data analytics. There already are significant deployments in finance, national security, health care, criminal justice, transportation, and smart cities that have altered decisionmaking, business models, risk mitigation, and system performance. These developments are generating substantial economic and social benefits.

The world is on the cusp of revolutionizing many sectors through artificial intelligence, but the way AI systems are developed need to be better understood due to the major implications these technologies will have for society as a whole.

Yet the manner in which AI systems unfold has major implications for society as a whole. It matters how policy issues are addressed, ethical conflicts are reconciled, legal realities are resolved, and how much transparency is required in AI and data analytic solutions. 74 Human choices about software development affect the way in which decisions are made and the manner in which they are integrated into organizational routines. Exactly how these processes are executed need to be better understood because they will have substantial impact on the general public soon, and for the foreseeable future. AI may well be a revolution in human affairs, and become the single most influential human innovation in history.

Note: We appreciate the research assistance of Grace Gilberg, Jack Karsten, Hillary Schaub, and Kristjan Tomasson on this project.

The Brookings Institution is a nonprofit organization devoted to independent research and policy solutions. Its mission is to conduct high-quality, independent research and, based on that research, to provide innovative, practical recommendations for policymakers and the public. The conclusions and recommendations of any Brookings publication are solely those of its author(s), and do not reflect the views of the Institution, its management, or its other scholars.

Support for this publication was generously provided by Amazon. Brookings recognizes that the value it provides is in its absolute commitment to quality, independence, and impact. Activities supported by its donors reflect this commitment. 

John R. Allen is a member of the Board of Advisors of Amida Technology and on the Board of Directors of Spark Cognition. Both companies work in fields discussed in this piece.

• Thomas Davenport, Jeff Loucks, and David Schatsky, “Bullish on the Business Value of Cognitive” (Deloitte, 2017), p. 3 (www2.deloitte.com/us/en/pages/deloitte-analytics/articles/cognitive-technology-adoption-survey.html).
• Luke Dormehl, Thinking Machines: The Quest for Artificial Intelligence—and Where It’s Taking Us Next (New York: Penguin–TarcherPerigee, 2017).
• Shubhendu and Vijay, “Applicability of Artificial Intelligence in Different Fields of Life.”
• Andrew McAfee and Erik Brynjolfsson, Machine Platform Crowd: Harnessing Our Digital Future (New York: Norton, 2017).
• Portions of this paper draw on Darrell M. West, The Future of Work: Robots, AI, and Automation , Brookings Institution Press, 2018.
• PriceWaterhouseCoopers, “Sizing the Prize: What’s the Real Value of AI for Your Business and How Can You Capitalise?” 2017.
• Dominic Barton, Jonathan Woetzel, Jeongmin Seong, and Qinzheng Tian, “Artificial Intelligence: Implications for China” (New York: McKinsey Global Institute, April 2017), p. 1.
• Nathaniel Popper, “Stocks and Bots,” New York Times Magazine , February 28, 2016.
• Michael Lewis, Flash Boys: A Wall Street Revolt (New York: Norton, 2015).
• Cade Metz, “In Quantum Computing Race, Yale Professors Battle Tech Giants,” New York Times , November 14, 2017, p. B3.
• Executive Office of the President, “Artificial Intelligence, Automation, and the Economy,” December 2016, pp. 27-28.
• Christian Davenport, “Future Wars May Depend as Much on Algorithms as on Ammunition, Report Says,” Washington Post , December 3, 2017.
• John R. Allen and Amir Husain, “On Hyperwar,” Naval Institute Proceedings , July 17, 2017, pp. 30-36.
• Paul Mozur, “China Sets Goal to Lead in Artificial Intelligence,” New York Times , July 21, 2017, p. B1.
• Paul Mozur and John Markoff, “Is China Outsmarting American Artificial Intelligence?” New York Times , May 28, 2017.
• Economist , “America v China: The Battle for Digital Supremacy,” March 15, 2018.
• Rasmus Rothe, “Applying Deep Learning to Real-World Problems,” Medium , May 23, 2017.
• Eric Horvitz, “Reflections on the Status and Future of Artificial Intelligence,” Testimony before the U.S. Senate Subcommittee on Space, Science, and Competitiveness, November 30, 2016, p. 5.
• Jeff Asher and Rob Arthur, “Inside the Algorithm That Tries to Predict Gun Violence in Chicago,” New York Times Upshot , June 13, 2017.
• Caleb Watney, “It’s Time for our Justice System to Embrace Artificial Intelligence,” TechTank (blog), Brookings Institution, July 20, 2017.
• Asher and Arthur, “Inside the Algorithm That Tries to Predict Gun Violence in Chicago.”
• Paul Mozur and Keith Bradsher, “China’s A.I. Advances Help Its Tech Industry, and State Security,” New York Times , December 3, 2017.
• Simon Denyer, “China’s Watchful Eye,” Washington Post , January 7, 2018.
• Cameron Kerry and Jack Karsten, “Gauging Investment in Self-Driving Cars,” Brookings Institution, October 16, 2017.
• Portions of this section are drawn from Darrell M. West, “Driverless Cars in China, Europe, Japan, Korea, and the United States,” Brookings Institution, September 2016.
• Yuming Ge, Xiaoman Liu, Libo Tang, and Darrell M. West, “Smart Transportation in China and the United States,” Center for Technology Innovation, Brookings Institution, December 2017.
• Peter Holley, “Uber Signs Deal to Buy 24,000 Autonomous Vehicles from Volvo,” Washington Post , November 20, 2017.
• Daisuke Wakabayashi, “Self-Driving Uber Car Kills Pedestrian in Arizona, Where Robots Roam,” New York Times , March 19, 2018.
• Kevin Desouza, Rashmi Krishnamurthy, and Gregory Dawson, “Learning from Public Sector Experimentation with Artificial Intelligence,” TechTank (blog), Brookings Institution, June 23, 2017.
• Boyd Cohen, “The 10 Smartest Cities in North America,” Fast Company , November 14, 2013.
• Teena Maddox, “66% of US Cities Are Investing in Smart City Technology,” TechRepublic , November 6, 2017.
• Osonde Osoba and William Welser IV, “The Risks of Artificial Intelligence to Security and the Future of Work” (Santa Monica, Calif.: RAND Corp., December 2017) (www.rand.org/pubs/perspectives/PE237.html).
• Ibid., p. 7.
• Dominic Barton, Jonathan Woetzel, Jeongmin Seong, and Qinzheng Tian, “Artificial Intelligence: Implications for China” (New York: McKinsey Global Institute, April 2017), p. 7.
• Executive Office of the President, “Preparing for the Future of Artificial Intelligence,” October 2016, pp. 30-31.
• Elaine Glusac, “As Airbnb Grows, So Do Claims of Discrimination,” New York Times , June 21, 2016.
• “Joy Buolamwini,” Bloomberg Businessweek , July 3, 2017, p. 80.
• Mark Purdy and Paul Daugherty, “Why Artificial Intelligence is the Future of Growth,” Accenture, 2016.
• Jon Valant, “Integrating Charter Schools and Choice-Based Education Systems,” Brown Center Chalkboard blog, Brookings Institution, June 23, 2017.
• Tucker, “‘A White Mask Worked Better.’”
• Cliff Kuang, “Can A.I. Be Taught to Explain Itself?” New York Times Magazine , November 21, 2017.
• Yale Law School Information Society Project, “Governing Machine Learning,” September 2017.
• Katie Benner, “Airbnb Vows to Fight Racism, But Its Users Can’t Sue to Prompt Fairness,” New York Times , June 19, 2016.
• Executive Office of the President, “Artificial Intelligence, Automation, and the Economy” and “Preparing for the Future of Artificial Intelligence.”
• Nancy Scolar, “Facebook’s Next Project: American Inequality,” Politico , February 19, 2018.
• Darrell M. West, “What Internet Search Data Reveals about Donald Trump’s First Year in Office,” Brookings Institution policy report, January 17, 2018.
• Ian Buck, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” February 14, 2018.
• Keith Nakasone, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” March 7, 2018.
• Greg Brockman, “The Dawn of Artificial Intelligence,” Testimony before U.S. Senate Subcommittee on Space, Science, and Competitiveness, November 30, 2016.
• Amir Khosrowshahi, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” February 14, 2018.
• James Kurose, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” March 7, 2018.
• Stephen Noonoo, “Teachers Can Now Use IBM’s Watson to Search for Free Lesson Plans,” EdSurge , September 13, 2017.
• Congress.gov, “H.R. 4625 FUTURE of Artificial Intelligence Act of 2017,” December 12, 2017.
• Elizabeth Zima, “Could New York City’s AI Transparency Bill Be a Model for the Country?” Government Technology , January 4, 2018.
• Julia Powles, “New York City’s Bold, Flawed Attempt to Make Algorithms Accountable,” New Yorker , December 20, 2017.
• Sheera Frenkel, “Tech Giants Brace for Europe’s New Data Privacy Rules,” New York Times , January 28, 2018.
• Claire Miller and Kevin O’Brien, “Germany’s Complicated Relationship with Google Street View,” New York Times , April 23, 2013.
• Cade Metz, “Artificial Intelligence is Setting Up the Internet for a Huge Clash with Europe,” Wired , July 11, 2016.
• Eric Siegel, “Predictive Analytics Interview Series: Andrew Burt,” Predictive Analytics Times , June 14, 2017.
• Oren Etzioni, “How to Regulate Artificial Intelligence,” New York Times , September 1, 2017.
• “Ethical Considerations in Artificial Intelligence and Autonomous Systems,” unpublished paper. IEEE Global Initiative, 2018.
• Ritesh Noothigattu, Snehalkumar Gaikwad, Edmond Awad, Sohan Dsouza, Iyad Rahwan, Pradeep Ravikumar, and Ariel Procaccia, “A Voting-Based System for Ethical Decision Making,” Computers and Society , September 20, 2017 (www.media.mit.edu/publications/a-voting-based-system-for-ethical-decision-making/).
• Miles Brundage, et al., “The Malicious Use of Artificial Intelligence,” University of Oxford unpublished paper, February 2018.
• John Markoff, “As Artificial Intelligence Evolves, So Does Its Criminal Potential,” New York Times, October 24, 2016, p. B3.
• Economist , “The Challenger: Technopolitics,” March 17, 2018.
• Douglas Maughan, “Testimony before the House Committee on Oversight and Government Reform Subcommittee on Information Technology,” March 7, 2018.
• Levi Tillemann and Colin McCormick, “Roadmapping a U.S.-German Agenda for Artificial Intelligence Policy,” New American Foundation, March 2017.

Artificial Intelligence

Governance Studies

Center for Technology Innovation

Artificial Intelligence and Emerging Technology Initiative

April 4, 2024

Nicol Turner Lee

March 28, 2024

Joseph B. Keller

Essay on Technology – A Boon or Bane for Students

500+ words essay on technology for students.

In this essay on technology, we are going to discuss what technology is, what are its uses, and also what technology can do? First of all, technology refers to the use of technical and scientific knowledge to create, monitor, and design machinery. Also, technology helps in making other goods that aid mankind.

Essay on Technology – A Boon or Bane?

Experts are debating on this topic for years. Also, the technology covered a long way to make human life easier but the negative aspect of it can’t be ignored. Over the years technological advancement has caused a severe rise in pollution . Also, pollution has become a major cause of many health issues. Besides, it has cut off people from society rather than connecting them. Above all, it has taken away many jobs from the workers class.

Familiarity between Technology and Science

As they are completely different fields but they are interdependent on each other. Also, it is due to science contribution we can create new innovation and build new technological tools. Apart from that, the research conducted in laboratories contributes a lot to the development of technologies. On the other hand, technology extends the agenda of science.

Vital Part of our Life

Regularly evolving technology has become an important part of our lives. Also, newer technologies are taking the market by storm and the people are getting used to them in no time. Above all, technological advancement has led to the growth and development of nations.

Negative Aspect of Technology

Although technology is a good thing, everything has two sides. Technology also has two sides one is good and the other is bad. Here are some negative aspects of technology that we are going to discuss.

Get the huge list of more than 500 Essay Topics and Ideas

With new technology the industrialization increases which give birth to many pollutions like air, water, soil, and noise. Also, they cause many health-related issues in animals, birds, and human beings.

Exhaustion of Natural Resources

New technology requires new resources for which the balance is disturbed. Eventually, this will lead to over-exploitation of natural resources which ultimately disturbs the balance of nature.

Unemployment

A single machine can replace many workers. Also, machines can do work at a constant pace for several hours or days without stopping. Due to this, many workers lost their job which ultimately increases unemployment .

Types of Technology

Generally, we judge technology on the same scale but in reality, technology is divided into various types. This includes information technology, industrial technology , architectural technology, creative technology and many more. Let’s discuss these technologies in brief.

Industrial Technology

This technology organizes engineering and manufacturing technology for the manufacturing of machines. Also, this makes the production process easier and convenient.

Creative Technology

This process includes art, advertising, and product design which are made with the help of software. Also, it comprises of 3D printers , virtual reality, computer graphics, and other wearable technologies.

Information Technology

This technology involves the use of telecommunication and computer to send, receive and store information. Internet is the best example of Information technology.

FAQs on Essay on Technology

Q.1 What is Information technology?

A –  It is a form of technology that uses telecommunication and computer systems for study. Also, they send, retrieve, and store data.

Q.2 Is technology harmful to humans?

 A – No, technology is not harmful to human beings until it is used properly. But, misuses of technology can be harmful and deadly.

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Essay on Technology and its impact Reading Questions and Answers

Ielts reading passage – essay on technology and its impact.

Essay on Technology and its impact

In simple words, Technology is the branch of study that deals with applied sciences and engineering. It is the application of scientific knowledge for a clear purpose Technology is the improvement and advancement of current processes to solve problems and make lives easier. It also denotes the progression made to solve problems like diseases or the state of famine.

Talking about the history of technology, it ranges from the time of developing a simple machine to lift stones till the time of having information technology explored. In 1894, Guglielmo Marconi developed the first radio whereas Harvard University created a digital computer around 1940. Twenty years before this time, on 6 august 1991, WWW (World Wide wave) became accessible to the public. This shows the drastic changes brought by the human brain in technical aspects.

Firstly, technology is a boon to the human brought by human brains in various forms.  Technology has been acting as a blessing for human society. From having access to the people living worldwide and knowing about the scenario beyond this planet, people got an opportunity to learn beyond the ordinary understanding. Technology has made communication easy and has supported a lot of enterprises and the economic world as well as the educational field. Optimization of medicinal waste and monitoring cognitive health has been possible. 

In addition to this, technology has been able to expand the area of promoting the ideas and beliefs. In other words, the world which was just vague in terms has been practically approachable because of technology. It has added the means of security and assisted the people physical disabilities too. Advancement in various fields has been possible because of technology. The imagination of a smart city has been a reality due to technology. Thus, technology has made advancement possible from stone age living to worldwide access with the help of the internet and media.

At the same time, the trend of misusing technology has prevailed causing a negative impact on human life. Talking about the negative impact of technology on human health, digital eye strain is the actual scenario now. The continuous use of the product of technology like smartphones causes musculoskeletal problems. Emotional stability and physical health have a raised question mark now because of technology. Further, there is negativity impact stamped on the kids resulting in behavioral problems, lack of socialization, violence, and obesity.

Besides human health, lack of privacy, and the reach to personal space through the act of tracing has worsened humanity and society. An increase in the number of crimes and additional stress on employees has made life suffocative. Technology has been an addiction which creates a loss of concentration as well. Youths drop their social skills and avoid communication skills. Insomnia has been a major problem. Overall, the root cause of cyber crimes and supervised criminals is a technology and its gifts to the world of gadgets.

Thus, technology is like a medicine. If taken more than the prescribed dose, it degrades us more than the advancement. The advancement comes with the limitation of use and access to the required fields. From having a child look at the videos on youtube while having a video conference by the caretaker, the world has been inviting the negativity more than the benefits. Thus, supervision is necessary to make proper and necessary use of technology and secure its safe tag policies rather than the lately discovered criminal purpose.

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Impact of Technology on Society

Impact of Technology on Society: In the past few decades, technology has proliferated. The use of technology has also increased drastically. It affects the lives of people and changes the way they learn, think, and communicate. It plays a major role in society, and now it is very tough to imagine life without technology. Both technology and society are co-related, co-dependent, co-influence with each other. Technology has an impact on society, including the potential for society to progress or decline, in both good and bad manner. Our society is shaped by technology, which has both beneficial and harmful consequences.

Table of Content

Impact of Technology

What is society, what is technology.

Human societies and technology have grown inextricably linked since technical systems like mobile phones, computers, TV, etc. are produced by humans and reflect the very basis of a population’s needs and lifestyle. Although technology improves the lifestyle of human beings, it is also a major concern for future generations. Nowadays, people are excessively using technology which reduces their physical activities and directly affects their health. Also, due to the excessive use of technology, there are so many cybercrimes happen every day in which someone steals the identity or personal information of the victim, such as a Unique ID number, PAN number, Debit Card, etc. and uses it to conduct a crime or perpetrate fraud without our permission. Some other cyber crimes are:

• Hacking: An effort to manipulate a computer system or a network within a computer is known as hacking. It is unauthorized control of computer systems to commit a crime.
• Credit/Debit Card theft: Credit card fraud refers to any type of fraud involving a payment card, such as a credit or debit card. The objective could be to obtain products or services or to transfer the funds to a criminal-controlled account.
• Malware installation: Any program or file that is dangerous to a computer user is known as malware. Viruses, worms, Trojan horses, and spyware are all examples of malware.
• E-mail threat: The use of email to deceive another person for personal benefit or to harm another person.
• Phishing: Depending on the offender, phishing attempts can target a wide spectrum of people. It’s possible that these are generic phishing emails aimed at anyone with a PayPal account. These are frequently identified as phishing attempts.
• Spams: An undesired, uninvited digital message that is sent in large quantities is known as spam. You can get spam via email, phone calls, text messages etc.
• ATM cards theft: ATM fraud refers to a crime in which the criminal make the payments for the criminal activities via some other person’s ATM card using the PIN.

Society is defined as the group of among human beings sharing social relationships. Or in other words, a society is a group of people that lives together in a community that includes some form of government, along with some rules and economy.

Technology is defined as the body of knowledge that deals with the innovation, invention, and application of technical means, as well as their interrelationship with life, society, and the environment. Or in other words, technology means the use of scientific knowledge to achieve some specific goal or create applications that are used in industry or in everyday life. So, if we are using some scientific knowledge to achieve some goal means we are using technology. 

We utilize and rely on technology in our daily lives, and our technical requirements and demands continue to grow. Technology is used by humans to explore, connect, study, and do work. The manner in which we use technology decides whether its effects are beneficial or detrimental for society.

Positive Impacts of Technology on Society

Technology has a more positive impact on humans or society as compared to negative. It makes our life easier and reward us by providing resources or tool that make our life much easier. Following are some positive changes that technology brings to our life:

• Improved Communication: Communication is the most important part of society, we build or transfer our thoughts with each other with the help of communication. Earlier people used pigeons or birds to transfer their messages to their loved ones. After that technology slowly grows and the medium of transferring information is changed to mobile phones, email, etc. Nowadays, we send messages to loved ones or known people via email, social media platforms, etc. It is the fastest, efficient, and effective medium. People can talk or share information with their loved ones easily even if they are very far away from them.
• Improved Education and learning process: Technology enhances the education and learning process. Nowadays, people can easily enhance their knowledge using the internet. Most of the data is present on the internet is free of cost, and you can access this data anytime and anywhere.
• Mechanized Agriculture: Technology changes the working mechanism of farmers. Lots of machines and technical instruments were introduced in the agricultural area which makes farming very easy, effective, automated, etc.
• Easy to access information: We can easily access information via the internet anytime and anywhere. Most of the information is present on the internet are free of cost, so you can use them to enhance your knowledge, skills, etc.

Negative Impacts of Technology on Society

As we know that everything present on this planet has both advantages and disadvantages. The same goes for technology it also has negative impacts on society and some other negative impacts are:

• Increase in unemployment: Nowadays, large and small business uses machinery and technical equipment because of their low costing and high efficiency due to which the rate of unemployment is increasing continuously.
• Increase in pollution: Not only humans but technology also affecting our environment. Due to vehicles and machinery, the rate of pollution is increasing continuously which causes global warming, etc.
• Increase in health and mental concerns: Nowadays, technology effecting the physical as well as mental health of human beings. It makes people lazy, emotionally weak, sleeping problems, reduce physical activity, also people are spending less time with their family and friends.
• Increase in cybercrimes: Due to the excessive use of the internet, the rate of cybercrimes are also increased. Some people (attackers) harm innocent people (victims) or children for money or fun.

Societal Issues and Cultural Changes

Social issues.

Following are some social issues that we face while using the internet:

• Identity Theft: To use the identity of some other person by getting his financial/ personal information in a fraud manner in order to commit a crime.
• Gaming Addiction: An individual’s capacity to perform in multiple life domains is severely affected as a result of the excessive use of internet games over a long period of time.
• Health and Fitness: Using a lot of the internet lay an impact on health and fitness, it may impact your eyesight, backbone, etc.
• Cyberbullying: The use of technology to bully, abuse, criticize, or target another person is known as cyberbullying.
• Terrorism and Crime: Theft of our cyber-infrastructure, as well as digital information such as software, hardware, data, or information, is considered cyberterrorism.
• Communication Breakdown: A communication breakdown occurs when information is not exchanged, resulting in a loss of interaction.
• Defamation of Character: The act of transmitting a piece of false information in order to do serious harm to another person’s goodwill is known as defamation of character.

Cultural  Changes

Our culture has been radically transformed by technology. From our ideals to our modes of communication, we’ve come a long way. Many people now find it difficult to conduct a face-to-face chat. People use their phones, tablets, or computers to spend time with their buddies. Also, individuals now evaluate others based on how technologically, whether or not they own the latest mobile phones or cars. Nowadays, listening to music on headphones is preferred over listening to another person. Most individuals nowadays prefer the internet because that is all they have ever known. Cell phones with touch screens are all the rage these days. Technology just serves to separate people from actuality. People nowadays lack the ability to interact in real-life situations such as individual connections, problem-solving, and showing adult actions. All this is influencing our culture. Technology influences culture every time we may get anything from an internet seller rather than going to a local business. Every moment someone always sits down to watch our night on-demand enjoyment, we are shaping culture through technology.

Frequently Asked Questions

How to authenticate biometric.

The technical difficulties of automated individual recognition based on biological and behavioral features are fundamental in the conversion of analog (facial image, fingerprint, voice pattern…) to digital (patterns, minutiae) data that can then be produced and matched with the effective algorithm.

What is the role of technology in modern society?

Technology helps in lending support in the automating various tasks, which include setting up reminders, communicating efficiently, payment of bills at click of a button and also shopping for simplest things.

What should we do if we find identity theft?

Put  a fraud warning on your credit reports so that we help us to identify identity theft. Put a hold on your credit. Use credit card monitor service and increase the level of security on your accounts.

What is cybercrime?

An illegal activity that makes use of a computer or targets a computer is known as cybercrime. Example: hacking, phishing, spamming, child pornography etc. Cyber thieves carry out illicit actions by use of Computer technology.

What is cybersecurity?

The technique of protecting servers, mobile devices, laptops, networks, data, etc. from malicious invasions is known as cybersecurity. Being secure online is what cyber safety entails. Threats to our safety and security abound in the online world.

What steps should be taken to safeguard online identity?

The following steps should be taken to safeguard online identity: 1. When providing personal information on the internet, be cautious. Just because a website requests information from you doesn’t mean you have to provide it to them. Inquire as to who wants the data and why they want it. 2. Do not open the link or attachment if it comes from someone you do not know. 3. When shopping or banking online, use a secure network. 4. Install sophisticated security software on your electrical device.

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Tech at the edge: Trends reshaping the future of IT and business

It is easy to become numb to the onslaught of new technologies hitting the market, each with its own promise of changing (more often “revolutionizing”) the business world. But our analysis of some of the more meaningful tech trends lays out a convincing case that something significant is happening. 1 Michael Chui, Roger Roberts, and Lareina Yee, “ McKinsey Technology Trends Outlook 2022 ,” McKinsey, August 24, 2022.

These tech trends are generally accelerating the primary characteristics that have defined the digital era: granularity, speed, and scale. But it’s the magnitude of these changes—in computing power, bandwidth, and analytical sophistication—that is opening the door to new innovations, businesses, and business models.

The emergence of cloud and 5G , for example, exponentially increases compute power and network speeds that can enable greater innovation. Developments in the metaverse of augmented and virtual reality open the doors to virtual R&D via digital twins , for example, and immersive learning. Advances in AI, machine learning, and software 2.0 (machine-written code) bring a range of new services and products, from autonomous vehicles to connected homes, well within reach.

Much ink has been spilled on identifying tech trends, but less attention has been paid to the implications of those changes. To help understand how management will need to adapt in the face of these technology trends in the next three to five years, we spoke to business leaders and leading thinkers on the topic. We weren’t looking for prognostications; we wanted to explore realistic scenarios, their implications, and what senior executives might do to get ready.

The discussions pinpointed some broad, interrelated shifts, such as how technology’s radically increasing power is exerting a centrifugal force on the organization, pushing innovation to expert networks at the edges of the company; how the pace and proliferation of these innovations calls for radical new approaches to continuous learning built around skills deployed at points of need; how these democratizing forces mean that IT can no longer act as a centralized controller of technology deployment and operations but instead needs to become a master enabler and influencer; and how these new technologies are creating more data about, and touchpoints with, customers, which is reshaping the boundaries of trust and requiring a much broader understanding of a company’s security responsibilities.

1. Innovation at the edge

Key tech trends.

We estimate that 70 percent of companies will employ hybrid or multicloud management technologies, tools, and processes . 2 “ The top trends in tech ,” McKinsey, June 15, 2021. At the same time, 5G will deliver network speeds that are about ten times faster than current speeds on 4G LTE networks, 3 Irina Ivanova, “What consumers need to know about this week’s AT&T–Verizon 5G rollout,” CBS News, January 20, 2022. with expectations of speeds that are up to 100 times faster with 40 times faster latency. 4 “5G speed: 5G vs. 4G performance compared,” Tom’s Guide, June 1, 2021. By 2024, more than 50 percent of user touches will be augmented by AI-driven speech, written word, or computer-vision algorithms , 5 “ The top trends in tech ,” June 15, 2021. while global data creation is projected to grow to more than 180 zettabytes by 2025, up from 64.2 zettabytes in 2020. 6 “Amount of data created, consumed, and stored 2010–2025,” Statista Research Department, May 23, 2022. The low-code development platform market‘s compound annual growth rate (CAGR) is projected at about 30 percent through 2030. 7 “Global $187 billion low-code development platform market to 2030,” GlobeNewswire, November 10, 2020.

Shift: Innovation develops around personal networks of experts at the porous edge of the organization and is supported by capabilities that scale the benefits across the business.

These technologies promise access to virtually unlimited compute power and massive data sets, as well as a huge leap in bandwidth at low cost, making it cheaper and easier to test, launch, and scale innovations quickly. The resulting acceleration in innovation will mean that companies can expect more disruptions from more sources. Centralized strategic and innovation functions cannot hope to keep pace on their own. Companies will need to be much more involved in networks outside their organizations to spot, invest in, and even acquire promising opportunities.

Corporate venture-capital (VC) funds with centralized teams have looked to find and fund innovation, but their track record has been spotty, often because the teams lack the requisite skills and are simply too far removed from the constantly evolving needs of individual business units. Instead, companies will need to figure out how to tap their front lines, particularly business domain experts and technologists, to enable them to act, in effect, as the business’s VC arm. That’s because the people who are writing code and building solutions are often well plugged into strong external networks in their fields and have the expertise to evaluate new developments. One pharma company, for example, taps its own expert researchers in various fields, such as gene expression, who know well the people outside the company who are leaders in the field.

While companies will need to create incentives and opportunities for engineers to build up and engage with their networks, the key focus must be on empowering teams so they can spend their allocated budget as they see fit—for example, experimenting and failing without penalty (within boundaries) and deciding on technologies to meet their goals (within prescribed guidelines).

The IT organization of the future can play an important role in building up a scaling capability to make that innovation work for the business, something that has traditionally been a challenge. Individual developers or small teams working fast don’t tend to naturally think about how to scale an application. That issue is likely to be exacerbated as nontechnical users working in pockets across organizations use low-code/no-code (LC/NC) applications to design and build programs with point-and-click or pull-down-menu interfaces.

One pharma company has taken this idea to heart by giving local business units the flexibility to run with a nonstandard idea when it has proven to be better than what the company is already doing. In return for that flexibility, the business unit must commit to helping the rest of the organization use the new idea, and IT builds it into the company’s standards.

In considering how this scaling capability might work, companies could, for example, assign advanced developers to “productize” applications by refactoring code so they can scale. IT leadership can provide tools and platforms, reusable-code libraries that are easily accessible, and flexible, standards-based architecture so that innovations can be scaled across the business more easily.

Questions for leadership

• What incentives will best encourage engineers and domain experts to develop, maintain, and tap into their networks?
• What processes are in place for tracking and managing VC activity at the edge?
• What capabilities do you need to identify innovation opportunities and “industrialize” the best ones so they can be shared across the organization?

For more on how to empower workers at the edge, see “ Tech companies innovate at the edge. Legacy companies can too ,” in Harvard Business Review.

Would you like to learn more about McKinsey Digital ?

2. a perpetual-learning culture.

Advances in AI, machine learning, robotics, and other technologies have increased the pace of change tenfold . By 2025, we estimate that 50 billion devices will be connected to the Industrial Internet of Things (IIoT), while 70 percent of manufacturers are expected to be using digital twins regularly (by 2022). 8 “ The top trends in tech ,” June 15, 2021. Some 70 percent of new applications will use LC/NC technologies by 2025, up from less than 25 percent in 2020. 9 “Gartner says cloud will be the centerpiece of new digital experiences,” Gartner, November 10, 2021. The global metaverse revenue opportunity could approach $800 billion in 2024, up from about $500 billion in 2020. 10 Bloomberg Intelligence, “Metaverse may be $800 billion market, next tech platform,” Bloomberg, December 1, 2021. This proliferation of technological innovations means we can expect to experience more progress in the next decade than in the past 100 years combined, according to entrepreneur and futurist Peter Diamandis. 11 Peter Diamandis and Steven Kotler, The Future Is Faster than You Think: How Converging Technologies Are Transforming Business, Industries, and Our Lives , New York: Simon & Schuster, 2020.

Shift: Tech literacy becomes core to every role, requiring learning to be continuous and built at the level of individual skills that are deployed at the point of need.

With the pace and proliferation of technologies pushing innovation to the edge of the organization, businesses need to be ready to incorporate the most promising options from across the front lines. This will create huge opportunities, but only for those companies that develop true tech intelligence through a perpetual-learning culture. The cornerstone of this effort includes training all levels of personnel, from “citizen developers” working with easy-to-use LC/NC tools or in entirely new environments such as the metaverse, to full-stack developers and engineers, who will need to continually evolve their skills to keep up with changing technologies. We’re already seeing situations where poorly trained employees use LC/NC to churn out suboptimal products.

While there will always be a need for more formalized paths for foundational learning, we anticipate an acceleration in the shift from teaching curricula periodically to continuous learning that can deliver varying technical skills across the entire organization. In practice, that will mean orienting employee development around delivering skills. This requires breaking down a capability into its smallest sets of composite skills. One large tech company, for example, created 146,000 skills data points for the 1,200 technical skills it was assessing.

The key point is that these skills “snippets”—such as a block of code or a video of a specific negotiating tactic—need to be integrated into the workflow so that they’re delivered when needed. This might be called a “LearnOps” approach, where learning is built into the operations. This integration mentality is established at Netflix, where data scientists partner directly with product managers, engineering teams, and other business units to design, execute, and learn from experiments. 12 Netflix Technology Blog , “Experimentation is a major focus of data science across Netflix,” blog entry by Martin Tingley et al., January 11, 2022.

As important as being able to deploy learning is building a learning culture by making continuous learning expected and easy to do. The way top engineers learn can be instructive. This is a community that is highly aware of the need to keep their skills up to date. They have ingrained habits of sharing code, and they gravitate to projects where they can learn. One advantage of using open source, for example, is the built-in community that constantly updates and reviews code. In the same spirit, we’re seeing companies budget extra time to allow people to try new tools or technologies when they’re building a product. Other companies are budgeting for “learning buffers” to allow for setbacks in product development that teams can learn from. 13 “ The big boost: How incumbents successfully scale their new businesses ,” McKinsey, August 27, 2020.

Netflix, which makes broad, open, and deliberate information sharing a core value, built the Netflix experimentation platform as an internal product that acts as a repository of solutions for future teams to reuse. It has a product manager and innovation road map, with the goal of making experimentation a simple and integrated part of the product life cycle. 14 Netflix Technology Blog , “Netflix: A culture of learning,” blog entry by Martin Tingley et al., January 25, 2022.

To support this kind of continuous learning and experimentation, companies will need to accept mistakes. The art will be in limiting the impact of potentially costly mistakes, such as the loss or misuse of customer data. IT will need to architect protocols, incentives, and systems to encourage good behaviors and reduce bad ones. Many companies are beginning to adopt practices such as automated testing to keep mistakes from happening in the first place ; creating spaces where mistakes won’t affect other applications or systems, such as isolation zones in cloud environments ; and building in resiliency protocols.

• Do you have a list of the most important skills your business needs?
• What is the minimum level of learning needed for advanced users of analytics and manipulators of data?
• How do you track what people are learning and whether that learning is effective and translating into better performance?

3. IT as a service

It is estimated that the global cloud microservices platform market will generate $4.2 billion in revenue by 2028, up from $952 million in 2020. 15 Cloud microservice platform market report , Research Dive, November 2021. GitHub has more than 200 million code repositories and expects 100 million software developers by 2025. 16 Paul Krill, “GitHub expects more than 100 million software developers by 2025,” InfoWorld, December 3, 2020. Nearly 90 percent of developers already use APIs. 17 Christina Voskoglou, “APIs have taken over software development,” Nordic APIs, October 27, 2020. Software 2.0 creates new ways of writing software and reduces complexity. Software sourced by companies from cloud-service platforms, open repositories, and software as a service (SaaS) is growing at a CAGR of 27.5 percent from 2021 to 2028. 18 Software as a service (SaaS) market, 2021–2028 , Fortune Business Insights, January 2022.

Shift: IT becomes the enabler of product innovation by serving small, interoperable blocks of code.

When innovation is pushed to the edge and a perpetual-learning culture permeates an organization, the role of IT shifts dramatically. IT can’t support this dynamic environment by sticking to its traditional role as a controlling entity managing technology at the center. The premium will now be on IT’s ability to enable innovation, requiring a shift in its traditional role as protector of big tech assets to a purveyor of small blocks of code. The gold standard of IT effectiveness will be its ability to help people stitch together snippets of code into a useful product.

We are already seeing what that might look like. Employees at G&J Pepsi-Cola Bottlers with little to no experience at software development created an app that examines images of a store shelf to identify the number and type of bottles on it, then automatically restocks it based on historic trends. 19 Adam Burden, “Low code/no code could reshape business innovation,” VentureBeat, February 5, 2022. One pharmaceutical company grew its low-code platform base from eight users to 1,400 in just one year . Business users outside of IT are now building applications with thousands of monthly sessions. 20 Shivam Srivastava, Kartik Trehan, Dilip Wagle, and Jane Wang, “ Developer Velocity: How software excellence fuels business performance ,” McKinsey, April 20, 2020. Companies that empower “citizen developers” score 33 percent higher on innovation compared with bottom-quartile companies that don’t provide that level of support, according to a McKinsey survey. 21 Shivam Srivastava, Kartik Trehan, Dilip Wagle, and Jane Wang, “ Developer Velocity: How software excellence fuels business performance ,” McKinsey, April 20, 2020.

These developments point toward much more of a “buffet” approach to technology, where IT builds useful blocks of reusable code, sometimes assembles them into specific products, and makes them available through a user-friendly cataloging system for the business to use to create the products it needs. IT provides guiderails, such as API standards and directives on the environments in which the code might be most useful; protects the most sensitive information, such as customer data and financial records; and tracks their adoption. This tracking capability will become particularly crucial as bots, AI, algorithms, and APIs proliferate. Transparency isn’t sufficient. IT will need to make sense of all the activity through advanced tech performance and management capabilities and the development of new roles, such as data diagnosticians and bot managers.

This IT-as-a-service approach puts the product at the center of the operating model, requiring a commitment to organizing IT around product management . Some companies have been moving in this direction. But reaching the scale needed to support fast-paced and more diffuse innovation will require a deeper commitment to product owners, working with leaders in the business side of the house, to run teams with real P&L responsibility. Many organizations, from traditional enterprises to digital natives, have found that putting in place product leaders who set overall product and portfolio strategy, drive execution, and empower product owners to drive innovation aligned with business outcomes and P&L metrics can increase the return on the funding that flows to technology delivery and quicken the pace of innovation.

• Do you have a vision for how the role of the IT organization will change to enable democratization of technology?
• How will you elevate the role of the technology product manager, and do you have a road map for developing that role?
• What systems will you need to put in place to manage and track the use, reuse, and performance of code?

McKinsey Technology Trends Outlook 2022

4. expanded trust boundaries.

It was estimated that almost 100 percent of biometrics-capable devices (such as smartphones) will be using biometrics for transactions by 2022. 22 “Usage of biometric technology in transactions with mobile devices worldwide 2016–2022”, Statista Research Department, June 13, 2022. The effectiveness of these technologies has advanced dramatically, with the best facial-identification algorithms having improved 50 times since 2014. 23 William Crumpler, “How accurate are facial recognition systems—and why does it matter?” Center for Strategies and International Studies (CSIS), April 14, 2020. These developments are contributing to profound unease in the relationship between technology and consumers of technology. The Pearson Institute and the Associated Press-NORC Center for Public Affairs Research shows that “about two-thirds of Americans are very or extremely concerned about hacking that involves their personal information, financial institutions, government agencies, or certain utilities.” 24 Chuck Brooks, “More alarming cybersecurity stats for 2021!” Forbes , October 24, 2021.

Shift: Trust expands to cover a broader array of stakeholder concerns and become an enterprise-wide responsibility.

These enormous shifts in technology power and capacity will create many more touchpoints with customers and an exponential wave of new data about customers. Even as IT’s role within the organization becomes more that of an enabler, the expanding digital landscape means that IT must broaden its trust capabilities around security, privacy, and cyber . To date, consumers have largely embraced the convenience that technology provides, from ordering a product online to adjusting the temperature in their homes remotely to monitoring their health through personal devices. In exchange for these conveniences, consumers have traditionally been willing to provide some personal information. But a steady undercurrent of privacy and trust concerns around these ever-more-sophisticated conveniences is raising the stakes on the broad topic of trust. Consumers are becoming more aware of their identity rights, making decisions based on values, and demanding the ethical use of data and responsible AI .

The most obvious concern is around cybersecurity , an ongoing issue that is already on the board-level agenda. But tech-driven trust issues are much broader and are driven by three characteristics. One is the sheer quantity of personal data, such as biometrics, that companies and governments collect, creating concerns about privacy and data misuse. The second is that personal security issues are becoming more pervasive in the physical world. Wired homes, connected cars, and the Internet of Medical Things, for example, are all vectors for attack that can affect people’s well-being. Third is the issue that advanced analytics seem too complex to be understood and controlled, leading to deep unease about people’s relationship with technology. This issue is driving the development of “ explainable AI ” and the movement to debias AI.

Adding to the complexity is the frequent need to manage and secure trust across an entire ecosystem of technologies. Take the wired home, for example. The proliferation of devices—think virtual assistants, security, communications, power management, and entertainment systems—means that a large group of providers will need to agree on standards for managing, in effect, an interconnected security net in the home.

These developments require a complex extension of the boundaries of trust. The significant advantages that many incumbents enjoy—existing relationships with customers and proprietary data—are at risk unless businesses rethink how they manage and nurture that trust. Companies need to consider putting identity and trust management at the core of their customer experience and business processes. That can happen effectively only when companies assign a dedicated leader with real power and board-level prioritization with enterprise-wide responsibility across the entire trust and security landscape. Given the tech underpinnings of this trust environment, IT will need to play a key role in monitoring and remediating, such as assessing the impact of new legislation on AI algorithms, tracking incidents, identifying the number and nature of high-risk data-processing activities and automated decisions, and—perhaps most important—monitoring consumer trust levels and the issues that affect them.

• Who is responsible for the enterprise-wide trust and risk landscape?
• How have you integrated your efforts around customer trust with overall cybersecurity processes?
• What privacy, trust, and security processes are in place to manage the entire life cycle of your data?

It is inevitable that the pace of technological change will continue to accelerate. The successful technology leader of the future will not simply need to adopt new technologies but to build capabilities to absorb continuous change and make it a source of competitive advantage.

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Impacts of digital technologies on education and factors influencing schools' digital capacity and transformation: A literature review

Stella timotheou.

1 CYENS Center of Excellence & Cyprus University of Technology (Cyprus Interaction Lab), Cyprus, CYENS Center of Excellence & Cyprus University of Technology, Nicosia-Limassol, Cyprus

Ourania Miliou

Yiannis dimitriadis.

2 Universidad de Valladolid (UVA), Spain, Valladolid, Spain

Sara Villagrá Sobrino

Nikoleta giannoutsou, romina cachia.

3 JRC - Joint Research Centre of the European Commission, Seville, Spain

Alejandra Martínez Monés

Andri ioannou, associated data.

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

Digital technologies have brought changes to the nature and scope of education and led education systems worldwide to adopt strategies and policies for ICT integration. The latter brought about issues regarding the quality of teaching and learning with ICTs, especially concerning the understanding, adaptation, and design of the education systems in accordance with current technological trends. These issues were emphasized during the recent COVID-19 pandemic that accelerated the use of digital technologies in education, generating questions regarding digitalization in schools. Specifically, many schools demonstrated a lack of experience and low digital capacity, which resulted in widening gaps, inequalities, and learning losses. Such results have engendered the need for schools to learn and build upon the experience to enhance their digital capacity and preparedness, increase their digitalization levels, and achieve a successful digital transformation. Given that the integration of digital technologies is a complex and continuous process that impacts different actors within the school ecosystem, there is a need to show how these impacts are interconnected and identify the factors that can encourage an effective and efficient change in the school environments. For this purpose, we conducted a non-systematic literature review. The results of the literature review were organized thematically based on the evidence presented about the impact of digital technology on education and the factors that affect the schools’ digital capacity and digital transformation. The findings suggest that ICT integration in schools impacts more than just students’ performance; it affects several other school-related aspects and stakeholders, too. Furthermore, various factors affect the impact of digital technologies on education. These factors are interconnected and play a vital role in the digital transformation process. The study results shed light on how ICTs can positively contribute to the digital transformation of schools and which factors should be considered for schools to achieve effective and efficient change.

Introduction

Digital technologies have brought changes to the nature and scope of education. Versatile and disruptive technological innovations, such as smart devices, the Internet of Things (IoT), artificial intelligence (AI), augmented reality (AR) and virtual reality (VR), blockchain, and software applications have opened up new opportunities for advancing teaching and learning (Gaol & Prasolova-Førland, 2021 ; OECD, 2021 ). Hence, in recent years, education systems worldwide have increased their investment in the integration of information and communication technology (ICT) (Fernández-Gutiérrez et al., 2020 ; Lawrence & Tar, 2018 ) and prioritized their educational agendas to adapt strategies or policies around ICT integration (European Commission, 2019 ). The latter brought about issues regarding the quality of teaching and learning with ICTs (Bates, 2015 ), especially concerning the understanding, adaptation, and design of education systems in accordance with current technological trends (Balyer & Öz, 2018 ). Studies have shown that despite the investment made in the integration of technology in schools, the results have not been promising, and the intended outcomes have not yet been achieved (Delgado et al., 2015 ; Lawrence & Tar, 2018 ). These issues were exacerbated during the COVID-19 pandemic, which forced teaching across education levels to move online (Daniel, 2020 ). Online teaching accelerated the use of digital technologies generating questions regarding the process, the nature, the extent, and the effectiveness of digitalization in schools (Cachia et al., 2021 ; König et al., 2020 ). Specifically, many schools demonstrated a lack of experience and low digital capacity, which resulted in widening gaps, inequalities, and learning losses (Blaskó et al., 2021 ; Di Pietro et al, 2020 ). Such results have engendered the need for schools to learn and build upon the experience in order to enhance their digital capacity (European Commission, 2020 ) and increase their digitalization levels (Costa et al., 2021 ). Digitalization offers possibilities for fundamental improvement in schools (OECD, 2021 ; Rott & Marouane, 2018 ) and touches many aspects of a school’s development (Delcker & Ifenthaler, 2021 ) . However, it is a complex process that requires large-scale transformative changes beyond the technical aspects of technology and infrastructure (Pettersson, 2021 ). Namely, digitalization refers to “ a series of deep and coordinated culture, workforce, and technology shifts and operating models ” (Brooks & McCormack, 2020 , p. 3) that brings cultural, organizational, and operational change through the integration of digital technologies (JISC, 2020 ). A successful digital transformation requires that schools increase their digital capacity levels, establishing the necessary “ culture, policies, infrastructure as well as digital competence of students and staff to support the effective integration of technology in teaching and learning practices ” (Costa et al, 2021 , p.163).

Given that the integration of digital technologies is a complex and continuous process that impacts different actors within the school ecosystem (Eng, 2005 ), there is a need to show how the different elements of the impact are interconnected and to identify the factors that can encourage an effective and efficient change in the school environment. To address the issues outlined above, we formulated the following research questions:

a) What is the impact of digital technologies on education?

b) Which factors might affect a school’s digital capacity and transformation?

In the present investigation, we conducted a non-systematic literature review of publications pertaining to the impact of digital technologies on education and the factors that affect a school’s digital capacity and transformation. The results of the literature review were organized thematically based on the evidence presented about the impact of digital technology on education and the factors which affect the schools’ digital capacity and digital transformation.

Methodology

The non-systematic literature review presented herein covers the main theories and research published over the past 17 years on the topic. It is based on meta-analyses and review papers found in scholarly, peer-reviewed content databases and other key studies and reports related to the concepts studied (e.g., digitalization, digital capacity) from professional and international bodies (e.g., the OECD). We searched the Scopus database, which indexes various online journals in the education sector with an international scope, to collect peer-reviewed academic papers. Furthermore, we used an all-inclusive Google Scholar search to include relevant key terms or to include studies found in the reference list of the peer-reviewed papers, and other key studies and reports related to the concepts studied by professional and international bodies. Lastly, we gathered sources from the Publications Office of the European Union ( https://op.europa.eu/en/home ); namely, documents that refer to policies related to digital transformation in education.

Regarding search terms, we first searched resources on the impact of digital technologies on education by performing the following search queries: “impact” OR “effects” AND “digital technologies” AND “education”, “impact” OR “effects” AND “ICT” AND “education”. We further refined our results by adding the terms “meta-analysis” and “review” or by adjusting the search options based on the features of each database to avoid collecting individual studies that would provide limited contributions to a particular domain. We relied on meta-analyses and review studies as these consider the findings of multiple studies to offer a more comprehensive view of the research in a given area (Schuele & Justice, 2006 ). Specifically, meta-analysis studies provided quantitative evidence based on statistically verifiable results regarding the impact of educational interventions that integrate digital technologies in school classrooms (Higgins et al., 2012 ; Tolani-Brown et al., 2011 ).

However, quantitative data does not offer explanations for the challenges or difficulties experienced during ICT integration in learning and teaching (Tolani-Brown et al., 2011 ). To fill this gap, we analyzed literature reviews and gathered in-depth qualitative evidence of the benefits and implications of technology integration in schools. In the analysis presented herein, we also included policy documents and reports from professional and international bodies and governmental reports, which offered useful explanations of the key concepts of this study and provided recent evidence on digital capacity and transformation in education along with policy recommendations. The inclusion and exclusion criteria that were considered in this study are presented in Table ​ Table1 1 .

Inclusion and exclusion criteria for the selection of resources on the impact of digital technologies on education

To ensure a reliable extraction of information from each study and assist the research synthesis we selected the study characteristics of interest (impact) and constructed coding forms. First, an overview of the synthesis was provided by the principal investigator who described the processes of coding, data entry, and data management. The coders followed the same set of instructions but worked independently. To ensure a common understanding of the process between coders, a sample of ten studies was tested. The results were compared, and the discrepancies were identified and resolved. Additionally, to ensure an efficient coding process, all coders participated in group meetings to discuss additions, deletions, and modifications (Stock, 1994 ). Due to the methodological diversity of the studied documents we began to synthesize the literature review findings based on similar study designs. Specifically, most of the meta-analysis studies were grouped in one category due to the quantitative nature of the measured impact. These studies tended to refer to student achievement (Hattie et al., 2014 ). Then, we organized the themes of the qualitative studies in several impact categories. Lastly, we synthesized both review and meta-analysis data across the categories. In order to establish a collective understanding of the concept of impact, we referred to a previous impact study by Balanskat ( 2009 ) which investigated the impact of technology in primary schools. In this context, the impact had a more specific ICT-related meaning and was described as “ a significant influence or effect of ICT on the measured or perceived quality of (parts of) education ” (Balanskat, 2009 , p. 9). In the study presented herein, the main impacts are in relation to learning and learners, teaching, and teachers, as well as other key stakeholders who are directly or indirectly connected to the school unit.

The study’s results identified multiple dimensions of the impact of digital technologies on students’ knowledge, skills, and attitudes; on equality, inclusion, and social integration; on teachers’ professional and teaching practices; and on other school-related aspects and stakeholders. The data analysis indicated various factors that might affect the schools’ digital capacity and transformation, such as digital competencies, the teachers’ personal characteristics and professional development, as well as the school’s leadership and management, administration, infrastructure, etc. The impacts and factors found in the literature review are presented below.

Impacts of digital technologies on students’ knowledge, skills, attitudes, and emotions

The impact of ICT use on students’ knowledge, skills, and attitudes has been investigated early in the literature. Eng ( 2005 ) found a small positive effect between ICT use and students' learning. Specifically, the author reported that access to computer-assisted instruction (CAI) programs in simulation or tutorial modes—used to supplement rather than substitute instruction – could enhance student learning. The author reported studies showing that teachers acknowledged the benefits of ICT on pupils with special educational needs; however, the impact of ICT on students' attainment was unclear. Balanskat et al. ( 2006 ) found a statistically significant positive association between ICT use and higher student achievement in primary and secondary education. The authors also reported improvements in the performance of low-achieving pupils. The use of ICT resulted in further positive gains for students, namely increased attention, engagement, motivation, communication and process skills, teamwork, and gains related to their behaviour towards learning. Evidence from qualitative studies showed that teachers, students, and parents recognized the positive impact of ICT on students' learning regardless of their competence level (strong/weak students). Punie et al. ( 2006 ) documented studies that showed positive results of ICT-based learning for supporting low-achieving pupils and young people with complex lives outside the education system. Liao et al. ( 2007 ) reported moderate positive effects of computer application instruction (CAI, computer simulations, and web-based learning) over traditional instruction on primary school student's achievement. Similarly, Tamim et al. ( 2011 ) reported small to moderate positive effects between the use of computer technology (CAI, ICT, simulations, computer-based instruction, digital and hypermedia) and student achievement in formal face-to-face classrooms compared to classrooms that did not use technology. Jewitt et al., ( 2011 ) found that the use of learning platforms (LPs) (virtual learning environments, management information systems, communication technologies, and information- and resource-sharing technologies) in schools allowed primary and secondary students to access a wider variety of quality learning resources, engage in independent and personalized learning, and conduct self- and peer-review; LPs also provide opportunities for teacher assessment and feedback. Similar findings were reported by Fu ( 2013 ), who documented a list of benefits and opportunities of ICT use. According to the author, the use of ICTs helps students access digital information and course content effectively and efficiently, supports student-centered and self-directed learning, as well as the development of a creative learning environment where more opportunities for critical thinking skills are offered, and promotes collaborative learning in a distance-learning environment. Higgins et al. ( 2012 ) found consistent but small positive associations between the use of technology and learning outcomes of school-age learners (5–18-year-olds) in studies linking the provision and use of technology with attainment. Additionally, Chauhan ( 2017 ) reported a medium positive effect of technology on the learning effectiveness of primary school students compared to students who followed traditional learning instruction.

The rise of mobile technologies and hardware devices instigated investigations into their impact on teaching and learning. Sung et al. ( 2016 ) reported a moderate effect on students' performance from the use of mobile devices in the classroom compared to the use of desktop computers or the non-use of mobile devices. Schmid et al. ( 2014 ) reported medium–low to low positive effects of technology integration (e.g., CAI, ICTs) in the classroom on students' achievement and attitude compared to not using technology or using technology to varying degrees. Tamim et al. ( 2015 ) found a low statistically significant effect of the use of tablets and other smart devices in educational contexts on students' achievement outcomes. The authors suggested that tablets offered additional advantages to students; namely, they reported improvements in students’ notetaking, organizational and communication skills, and creativity. Zheng et al. ( 2016 ) reported a small positive effect of one-to-one laptop programs on students’ academic achievement across subject areas. Additional reported benefits included student-centered, individualized, and project-based learning enhanced learner engagement and enthusiasm. Additionally, the authors found that students using one-to-one laptop programs tended to use technology more frequently than in non-laptop classrooms, and as a result, they developed a range of skills (e.g., information skills, media skills, technology skills, organizational skills). Haßler et al. ( 2016 ) found that most interventions that included the use of tablets across the curriculum reported positive learning outcomes. However, from 23 studies, five reported no differences, and two reported a negative effect on students' learning outcomes. Similar results were indicated by Kalati and Kim ( 2022 ) who investigated the effect of touchscreen technologies on young students’ learning. Specifically, from 53 studies, 34 advocated positive effects of touchscreen devices on children’s learning, 17 obtained mixed findings and two studies reported negative effects.

More recently, approaches that refer to the impact of gamification with the use of digital technologies on teaching and learning were also explored. A review by Pan et al. ( 2022 ) that examined the role of learning games in fostering mathematics education in K-12 settings, reported that gameplay improved students’ performance. Integration of digital games in teaching was also found as a promising pedagogical practice in STEM education that could lead to increased learning gains (Martinez et al., 2022 ; Wang et al., 2022 ). However, although Talan et al. ( 2020 ) reported a medium effect of the use of educational games (both digital and non-digital) on academic achievement, the effect of non-digital games was higher.

Over the last two years, the effects of more advanced technologies on teaching and learning were also investigated. Garzón and Acevedo ( 2019 ) found that AR applications had a medium effect on students' learning outcomes compared to traditional lectures. Similarly, Garzón et al. ( 2020 ) showed that AR had a medium impact on students' learning gains. VR applications integrated into various subjects were also found to have a moderate effect on students’ learning compared to control conditions (traditional classes, e.g., lectures, textbooks, and multimedia use, e.g., images, videos, animation, CAI) (Chen et al., 2022b ). Villena-Taranilla et al. ( 2022 ) noted the moderate effect of VR technologies on students’ learning when these were applied in STEM disciplines. In the same meta-analysis, Villena-Taranilla et al. ( 2022 ) highlighted the role of immersive VR, since its effect on students’ learning was greater (at a high level) across educational levels (K-6) compared to semi-immersive and non-immersive integrations. In another meta-analysis study, the effect size of the immersive VR was small and significantly differentiated across educational levels (Coban et al., 2022 ). The impact of AI on education was investigated by Su and Yang ( 2022 ) and Su et al. ( 2022 ), who showed that this technology significantly improved students’ understanding of AI computer science and machine learning concepts.

It is worth noting that the vast majority of studies referred to learning gains in specific subjects. Specifically, several studies examined the impact of digital technologies on students’ literacy skills and reported positive effects on language learning (Balanskat et al., 2006 ; Grgurović et al., 2013 ; Friedel et al., 2013 ; Zheng et al., 2016 ; Chen et al., 2022b ; Savva et al., 2022 ). Also, several studies documented positive effects on specific language learning areas, namely foreign language learning (Kao, 2014 ), writing (Higgins et al., 2012 ; Wen & Walters, 2022 ; Zheng et al., 2016 ), as well as reading and comprehension (Cheung & Slavin, 2011 ; Liao et al., 2007 ; Schwabe et al., 2022 ). ICTs were also found to have a positive impact on students' performance in STEM (science, technology, engineering, and mathematics) disciplines (Arztmann et al., 2022 ; Bado, 2022 ; Villena-Taranilla et al., 2022 ; Wang et al., 2022 ). Specifically, a number of studies reported positive impacts on students’ achievement in mathematics (Balanskat et al., 2006 ; Hillmayr et al., 2020 ; Li & Ma, 2010 ; Pan et al., 2022 ; Ran et al., 2022 ; Verschaffel et al., 2019 ; Zheng et al., 2016 ). Furthermore, studies documented positive effects of ICTs on science learning (Balanskat et al., 2006 ; Liao et al., 2007 ; Zheng et al., 2016 ; Hillmayr et al., 2020 ; Kalemkuş & Kalemkuş, 2022 ; Lei et al., 2022a ). Çelik ( 2022 ) also noted that computer simulations can help students understand learning concepts related to science. Furthermore, some studies documented that the use of ICTs had a positive impact on students’ achievement in other subjects, such as geography, history, music, and arts (Chauhan, 2017 ; Condie & Munro, 2007 ), and design and technology (Balanskat et al., 2006 ).

More specific positive learning gains were reported in a number of skills, e.g., problem-solving skills and pattern exploration skills (Higgins et al., 2012 ), metacognitive learning outcomes (Verschaffel et al., 2019 ), literacy skills, computational thinking skills, emotion control skills, and collaborative inquiry skills (Lu et al., 2022 ; Su & Yang, 2022 ; Su et al., 2022 ). Additionally, several investigations have reported benefits from the use of ICT on students’ creativity (Fielding & Murcia, 2022 ; Liu et al., 2022 ; Quah & Ng, 2022 ). Lastly, digital technologies were also found to be beneficial for enhancing students’ lifelong learning skills (Haleem et al., 2022 ).

Apart from gaining knowledge and skills, studies also reported improvement in motivation and interest in mathematics (Higgins et. al., 2019 ; Fadda et al., 2022 ) and increased positive achievement emotions towards several subjects during interventions using educational games (Lei et al., 2022a ). Chen et al. ( 2022a ) also reported a small but positive effect of digital health approaches in bullying and cyberbullying interventions with K-12 students, demonstrating that technology-based approaches can help reduce bullying and related consequences by providing emotional support, empowerment, and change of attitude. In their meta-review study, Su et al. ( 2022 ) also documented that AI technologies effectively strengthened students’ attitudes towards learning. In another meta-analysis, Arztmann et al. ( 2022 ) reported positive effects of digital games on motivation and behaviour towards STEM subjects.

Impacts of digital technologies on equality, inclusion and social integration

Although most of the reviewed studies focused on the impact of ICTs on students’ knowledge, skills, and attitudes, reports were also made on other aspects in the school context, such as equality, inclusion, and social integration. Condie and Munro ( 2007 ) documented research interventions investigating how ICT can support pupils with additional or special educational needs. While those interventions were relatively small scale and mostly based on qualitative data, their findings indicated that the use of ICTs enabled the development of communication, participation, and self-esteem. A recent meta-analysis (Baragash et al., 2022 ) with 119 participants with different disabilities, reported a significant overall effect size of AR on their functional skills acquisition. Koh’s meta-analysis ( 2022 ) also revealed that students with intellectual and developmental disabilities improved their competence and performance when they used digital games in the lessons.

Istenic Starcic and Bagon ( 2014 ) found that the role of ICT in inclusion and the design of pedagogical and technological interventions was not sufficiently explored in educational interventions with people with special needs; however, some benefits of ICT use were found in students’ social integration. The issue of gender and technology use was mentioned in a small number of studies. Zheng et al. ( 2016 ) reported a statistically significant positive interaction between one-to-one laptop programs and gender. Specifically, the results showed that girls and boys alike benefitted from the laptop program, but the effect on girls’ achievement was smaller than that on boys’. Along the same lines, Arztmann et al. ( 2022 ) reported no difference in the impact of game-based learning between boys and girls, arguing that boys and girls equally benefited from game-based interventions in STEM domains. However, results from a systematic review by Cussó-Calabuig et al. ( 2018 ) found limited and low-quality evidence on the effects of intensive use of computers on gender differences in computer anxiety, self-efficacy, and self-confidence. Based on their view, intensive use of computers can reduce gender differences in some areas and not in others, depending on contextual and implementation factors.

Impacts of digital technologies on teachers’ professional and teaching practices

Various research studies have explored the impact of ICT on teachers’ instructional practices and student assessment. Friedel et al. ( 2013 ) found that the use of mobile devices by students enabled teachers to successfully deliver content (e.g., mobile serious games), provide scaffolding, and facilitate synchronous collaborative learning. The integration of digital games in teaching and learning activities also gave teachers the opportunity to study and apply various pedagogical practices (Bado, 2022 ). Specifically, Bado ( 2022 ) found that teachers who implemented instructional activities in three stages (pre-game, game, and post-game) maximized students’ learning outcomes and engagement. For instance, during the pre-game stage, teachers focused on lectures and gameplay training, at the game stage teachers provided scaffolding on content, addressed technical issues, and managed the classroom activities. During the post-game stage, teachers organized activities for debriefing to ensure that the gameplay had indeed enhanced students’ learning outcomes.

Furthermore, ICT can increase efficiency in lesson planning and preparation by offering possibilities for a more collaborative approach among teachers. The sharing of curriculum plans and the analysis of students’ data led to clearer target settings and improvements in reporting to parents (Balanskat et al., 2006 ).

Additionally, the use and application of digital technologies in teaching and learning were found to enhance teachers’ digital competence. Balanskat et al. ( 2006 ) documented studies that revealed that the use of digital technologies in education had a positive effect on teachers’ basic ICT skills. The greatest impact was found on teachers with enough experience in integrating ICTs in their teaching and/or who had recently participated in development courses for the pedagogical use of technologies in teaching. Punie et al. ( 2006 ) reported that the provision of fully equipped multimedia portable computers and the development of online teacher communities had positive impacts on teachers’ confidence and competence in the use of ICTs.

Moreover, online assessment via ICTs benefits instruction. In particular, online assessments support the digitalization of students’ work and related logistics, allow teachers to gather immediate feedback and readjust to new objectives, and support the improvement of the technical quality of tests by providing more accurate results. Additionally, the capabilities of ICTs (e.g., interactive media, simulations) create new potential methods of testing specific skills, such as problem-solving and problem-processing skills, meta-cognitive skills, creativity and communication skills, and the ability to work productively in groups (Punie et al., 2006 ).

Impacts of digital technologies on other school-related aspects and stakeholders

There is evidence that the effective use of ICTs and the data transmission offered by broadband connections help improve administration (Balanskat et al., 2006 ). Specifically, ICTs have been found to provide better management systems to schools that have data gathering procedures in place. Condie and Munro ( 2007 ) reported impacts from the use of ICTs in schools in the following areas: attendance monitoring, assessment records, reporting to parents, financial management, creation of repositories for learning resources, and sharing of information amongst staff. Such data can be used strategically for self-evaluation and monitoring purposes which in turn can result in school improvements. Additionally, they reported that online access to other people with similar roles helped to reduce headteachers’ isolation by offering them opportunities to share insights into the use of ICT in learning and teaching and how it could be used to support school improvement. Furthermore, ICTs provided more efficient and successful examination management procedures, namely less time-consuming reporting processes compared to paper-based examinations and smooth communications between schools and examination authorities through electronic data exchange (Punie et al., 2006 ).

Zheng et al. ( 2016 ) reported that the use of ICTs improved home-school relationships. Additionally, Escueta et al. ( 2017 ) reported several ICT programs that had improved the flow of information from the school to parents. Particularly, they documented that the use of ICTs (learning management systems, emails, dedicated websites, mobile phones) allowed for personalized and customized information exchange between schools and parents, such as attendance records, upcoming class assignments, school events, and students’ grades, which generated positive results on students’ learning outcomes and attainment. Such information exchange between schools and families prompted parents to encourage their children to put more effort into their schoolwork.

The above findings suggest that the impact of ICT integration in schools goes beyond students’ performance in school subjects. Specifically, it affects a number of school-related aspects, such as equality and social integration, professional and teaching practices, and diverse stakeholders. In Table ​ Table2, 2 , we summarize the different impacts of digital technologies on school stakeholders based on the literature review, while in Table ​ Table3 3 we organized the tools/platforms and practices/policies addressed in the meta-analyses, literature reviews, EU reports, and international bodies included in the manuscript.

The impact of digital technologies on schools’ stakeholders based on the literature review

Tools/platforms and practices/policies addressed in the meta-analyses, literature reviews, EU reports, and international bodies included in the manuscript

Additionally, based on the results of the literature review, there are many types of digital technologies with different affordances (see, for example, studies on VR vs Immersive VR), which evolve over time (e.g. starting from CAIs in 2005 to Augmented and Virtual reality 2020). Furthermore, these technologies are linked to different pedagogies and policy initiatives, which are critical factors in the study of impact. Table ​ Table3 3 summarizes the different tools and practices that have been used to examine the impact of digital technologies on education since 2005 based on the review results.

Factors that affect the integration of digital technologies

Although the analysis of the literature review demonstrated different impacts of the use of digital technology on education, several authors highlighted the importance of various factors, besides the technology itself, that affect this impact. For example, Liao et al. ( 2007 ) suggested that future studies should carefully investigate which factors contribute to positive outcomes by clarifying the exact relationship between computer applications and learning. Additionally, Haßler et al., ( 2016 ) suggested that the neutral findings regarding the impact of tablets on students learning outcomes in some of the studies included in their review should encourage educators, school leaders, and school officials to further investigate the potential of such devices in teaching and learning. Several other researchers suggested that a number of variables play a significant role in the impact of ICTs on students’ learning that could be attributed to the school context, teaching practices and professional development, the curriculum, and learners’ characteristics (Underwood, 2009 ; Tamim et al., 2011 ; Higgins et al., 2012 ; Archer et al., 2014 ; Sung et al., 2016 ; Haßler et al., 2016 ; Chauhan, 2017 ; Lee et al., 2020 ; Tang et al., 2022 ).

Digital competencies

One of the most common challenges reported in studies that utilized digital tools in the classroom was the lack of students’ skills on how to use them. Fu ( 2013 ) found that students’ lack of technical skills is a barrier to the effective use of ICT in the classroom. Tamim et al. ( 2015 ) reported that students faced challenges when using tablets and smart mobile devices, associated with the technical issues or expertise needed for their use and the distracting nature of the devices and highlighted the need for teachers’ professional development. Higgins et al. ( 2012 ) reported that skills training about the use of digital technologies is essential for learners to fully exploit the benefits of instruction.

Delgado et al. ( 2015 ), meanwhile, reported studies that showed a strong positive association between teachers’ computer skills and students’ use of computers. Teachers’ lack of ICT skills and familiarization with technologies can become a constraint to the effective use of technology in the classroom (Balanskat et al., 2006 ; Delgado et al., 2015 ).

It is worth noting that the way teachers are introduced to ICTs affects the impact of digital technologies on education. Previous studies have shown that teachers may avoid using digital technologies due to limited digital skills (Balanskat, 2006 ), or they prefer applying “safe” technologies, namely technologies that their own teachers used and with which they are familiar (Condie & Munro, 2007 ). In this regard, the provision of digital skills training and exposure to new digital tools might encourage teachers to apply various technologies in their lessons (Condie & Munro, 2007 ). Apart from digital competence, technical support in the school setting has also been shown to affect teachers’ use of technology in their classrooms (Delgado et al., 2015 ). Ferrari et al. ( 2011 ) found that while teachers’ use of ICT is high, 75% stated that they needed more institutional support and a shift in the mindset of educational actors to achieve more innovative teaching practices. The provision of support can reduce time and effort as well as cognitive constraints, which could cause limited ICT integration in the school lessons by teachers (Escueta et al., 2017 ).

Teachers’ personal characteristics, training approaches, and professional development

Teachers’ personal characteristics and professional development affect the impact of digital technologies on education. Specifically, Cheok and Wong ( 2015 ) found that teachers’ personal characteristics (e.g., anxiety, self-efficacy) are associated with their satisfaction and engagement with technology. Bingimlas ( 2009 ) reported that lack of confidence, resistance to change, and negative attitudes in using new technologies in teaching are significant determinants of teachers’ levels of engagement in ICT. The same author reported that the provision of technical support, motivation support (e.g., awards, sufficient time for planning), and training on how technologies can benefit teaching and learning can eliminate the above barriers to ICT integration. Archer et al. ( 2014 ) found that comfort levels in using technology are an important predictor of technology integration and argued that it is essential to provide teachers with appropriate training and ongoing support until they are comfortable with using ICTs in the classroom. Hillmayr et al. ( 2020 ) documented that training teachers on ICT had an important effecton students’ learning.

According to Balanskat et al. ( 2006 ), the impact of ICTs on students’ learning is highly dependent on the teachers’ capacity to efficiently exploit their application for pedagogical purposes. Results obtained from the Teaching and Learning International Survey (TALIS) (OECD, 2021 ) revealed that although schools are open to innovative practices and have the capacity to adopt them, only 39% of teachers in the European Union reported that they are well or very well prepared to use digital technologies for teaching. Li and Ma ( 2010 ) and Hardman ( 2019 ) showed that the positive effect of technology on students’ achievement depends on the pedagogical practices used by teachers. Schmid et al. ( 2014 ) reported that learning was best supported when students were engaged in active, meaningful activities with the use of technological tools that provided cognitive support. Tamim et al. ( 2015 ) compared two different pedagogical uses of tablets and found a significant moderate effect when the devices were used in a student-centered context and approach rather than within teacher-led environments. Similarly, Garzón and Acevedo ( 2019 ) and Garzón et al. ( 2020 ) reported that the positive results from the integration of AR applications could be attributed to the existence of different variables which could influence AR interventions (e.g., pedagogical approach, learning environment, and duration of the intervention). Additionally, Garzón et al. ( 2020 ) suggested that the pedagogical resources that teachers used to complement their lectures and the pedagogical approaches they applied were crucial to the effective integration of AR on students’ learning gains. Garzón and Acevedo ( 2019 ) also emphasized that the success of a technology-enhanced intervention is based on both the technology per se and its characteristics and on the pedagogical strategies teachers choose to implement. For instance, their results indicated that the collaborative learning approach had the highest impact on students’ learning gains among other approaches (e.g., inquiry-based learning, situated learning, or project-based learning). Ran et al. ( 2022 ) also found that the use of technology to design collaborative and communicative environments showed the largest moderator effects among the other approaches.

Hattie ( 2008 ) reported that the effective use of computers is associated with training teachers in using computers as a teaching and learning tool. Zheng et al. ( 2016 ) noted that in addition to the strategies teachers adopt in teaching, ongoing professional development is also vital in ensuring the success of technology implementation programs. Sung et al. ( 2016 ) found that research on the use of mobile devices to support learning tends to report that the insufficient preparation of teachers is a major obstacle in implementing effective mobile learning programs in schools. Friedel et al. ( 2013 ) found that providing training and support to teachers increased the positive impact of the interventions on students’ learning gains. Trucano ( 2005 ) argued that positive impacts occur when digital technologies are used to enhance teachers’ existing pedagogical philosophies. Higgins et al. ( 2012 ) found that the types of technologies used and how they are used could also affect students’ learning. The authors suggested that training and professional development of teachers that focuses on the effective pedagogical use of technology to support teaching and learning is an important component of successful instructional approaches (Higgins et al., 2012 ). Archer et al. ( 2014 ) found that studies that reported ICT interventions during which teachers received training and support had moderate positive effects on students’ learning outcomes, which were significantly higher than studies where little or no detail about training and support was mentioned. Fu ( 2013 ) reported that the lack of teachers’ knowledge and skills on the technical and instructional aspects of ICT use in the classroom, in-service training, pedagogy support, technical and financial support, as well as the lack of teachers’ motivation and encouragement to integrate ICT on their teaching were significant barriers to the integration of ICT in education.

School leadership and management

Management and leadership are important cornerstones in the digital transformation process (Pihir et al., 2018 ). Zheng et al. ( 2016 ) documented leadership among the factors positively affecting the successful implementation of technology integration in schools. Strong leadership, strategic planning, and systematic integration of digital technologies are prerequisites for the digital transformation of education systems (Ređep, 2021 ). Management and leadership play a significant role in formulating policies that are translated into practice and ensure that developments in ICT become embedded into the life of the school and in the experiences of staff and pupils (Condie & Munro, 2007 ). Policy support and leadership must include the provision of an overall vision for the use of digital technologies in education, guidance for students and parents, logistical support, as well as teacher training (Conrads et al., 2017 ). Unless there is a commitment throughout the school, with accountability for progress at key points, it is unlikely for ICT integration to be sustained or become part of the culture (Condie & Munro, 2007 ). To achieve this, principals need to adopt and promote a whole-institution strategy and build a strong mutual support system that enables the school’s technological maturity (European Commission, 2019 ). In this context, school culture plays an essential role in shaping the mindsets and beliefs of school actors towards successful technology integration. Condie and Munro ( 2007 ) emphasized the importance of the principal’s enthusiasm and work as a source of inspiration for the school staff and the students to cultivate a culture of innovation and establish sustainable digital change. Specifically, school leaders need to create conditions in which the school staff is empowered to experiment and take risks with technology (Elkordy & Lovinelli, 2020 ).

In order for leaders to achieve the above, it is important to develop capacities for learning and leading, advocating professional learning, and creating support systems and structures (European Commission, 2019 ). Digital technology integration in education systems can be challenging and leadership needs guidance to achieve it. Such guidance can be introduced through the adoption of new methods and techniques in strategic planning for the integration of digital technologies (Ređep, 2021 ). Even though the role of leaders is vital, the relevant training offered to them has so far been inadequate. Specifically, only a third of the education systems in Europe have put in place national strategies that explicitly refer to the training of school principals (European Commission, 2019 , p. 16).

Connectivity, infrastructure, and government and other support

The effective integration of digital technologies across levels of education presupposes the development of infrastructure, the provision of digital content, and the selection of proper resources (Voogt et al., 2013 ). Particularly, a high-quality broadband connection in the school increases the quality and quantity of educational activities. There is evidence that ICT increases and formalizes cooperative planning between teachers and cooperation with managers, which in turn has a positive impact on teaching practices (Balanskat et al., 2006 ). Additionally, ICT resources, including software and hardware, increase the likelihood of teachers integrating technology into the curriculum to enhance their teaching practices (Delgado et al., 2015 ). For example, Zheng et al. ( 2016 ) found that the use of one-on-one laptop programs resulted in positive changes in teaching and learning, which would not have been accomplished without the infrastructure and technical support provided to teachers. Delgado et al. ( 2015 ) reported that limited access to technology (insufficient computers, peripherals, and software) and lack of technical support are important barriers to ICT integration. Access to infrastructure refers not only to the availability of technology in a school but also to the provision of a proper amount and the right types of technology in locations where teachers and students can use them. Effective technical support is a central element of the whole-school strategy for ICT (Underwood, 2009 ). Bingimlas ( 2009 ) reported that lack of technical support in the classroom and whole-school resources (e.g., failing to connect to the Internet, printers not printing, malfunctioning computers, and working on old computers) are significant barriers that discourage the use of ICT by teachers. Moreover, poor quality and inadequate hardware maintenance, and unsuitable educational software may discourage teachers from using ICTs (Balanskat et al., 2006 ; Bingimlas, 2009 ).

Government support can also impact the integration of ICTs in teaching. Specifically, Balanskat et al. ( 2006 ) reported that government interventions and training programs increased teachers’ enthusiasm and positive attitudes towards ICT and led to the routine use of embedded ICT.

Lastly, another important factor affecting digital transformation is the development and quality assurance of digital learning resources. Such resources can be support textbooks and related materials or resources that focus on specific subjects or parts of the curriculum. Policies on the provision of digital learning resources are essential for schools and can be achieved through various actions. For example, some countries are financing web portals that become repositories, enabling teachers to share resources or create their own. Additionally, they may offer e-learning opportunities or other services linked to digital education. In other cases, specific agencies of projects have also been set up to develop digital resources (Eurydice, 2019 ).

Administration and digital data management

The digital transformation of schools involves organizational improvements at the level of internal workflows, communication between the different stakeholders, and potential for collaboration. Vuorikari et al. ( 2020 ) presented evidence that digital technologies supported the automation of administrative practices in schools and reduced the administration’s workload. There is evidence that digital data affects the production of knowledge about schools and has the power to transform how schooling takes place. Specifically, Sellar ( 2015 ) reported that data infrastructure in education is developing due to the demand for “ information about student outcomes, teacher quality, school performance, and adult skills, associated with policy efforts to increase human capital and productivity practices ” (p. 771). In this regard, practices, such as datafication which refers to the “ translation of information about all kinds of things and processes into quantified formats” have become essential for decision-making based on accountability reports about the school’s quality. The data could be turned into deep insights about education or training incorporating ICTs. For example, measuring students’ online engagement with the learning material and drawing meaningful conclusions can allow teachers to improve their educational interventions (Vuorikari et al., 2020 ).

Students’ socioeconomic background and family support

Research show that the active engagement of parents in the school and their support for the school’s work can make a difference to their children’s attitudes towards learning and, as a result, their achievement (Hattie, 2008 ). In recent years, digital technologies have been used for more effective communication between school and family (Escueta et al., 2017 ). The European Commission ( 2020 ) presented data from a Eurostat survey regarding the use of computers by students during the pandemic. The data showed that younger pupils needed additional support and guidance from parents and the challenges were greater for families in which parents had lower levels of education and little to no digital skills.

In this regard, the socio-economic background of the learners and their socio-cultural environment also affect educational achievements (Punie et al., 2006 ). Trucano documented that the use of computers at home positively influenced students’ confidence and resulted in more frequent use at school, compared to students who had no home access (Trucano, 2005 ). In this sense, the socio-economic background affects the access to computers at home (OECD, 2015 ) which in turn influences the experience of ICT, an important factor for school achievement (Punie et al., 2006 ; Underwood, 2009 ). Furthermore, parents from different socio-economic backgrounds may have different abilities and availability to support their children in their learning process (Di Pietro et al., 2020 ).

Schools’ socioeconomic context and emergency situations

The socio-economic context of the school is closely related to a school’s digital transformation. For example, schools in disadvantaged, rural, or deprived areas are likely to lack the digital capacity and infrastructure required to adapt to the use of digital technologies during emergency periods, such as the COVID-19 pandemic (Di Pietro et al., 2020 ). Data collected from school principals confirmed that in several countries, there is a rural/urban divide in connectivity (OECD, 2015 ).

Emergency periods also affect the digitalization of schools. The COVID-19 pandemic led to the closure of schools and forced them to seek appropriate and connective ways to keep working on the curriculum (Di Pietro et al., 2020 ). The sudden large-scale shift to distance and online teaching and learning also presented challenges around quality and equity in education, such as the risk of increased inequalities in learning, digital, and social, as well as teachers facing difficulties coping with this demanding situation (European Commission, 2020 ).

Looking at the findings of the above studies, we can conclude that the impact of digital technologies on education is influenced by various actors and touches many aspects of the school ecosystem. Figure  1 summarizes the factors affecting the digital technologies’ impact on school stakeholders based on the findings from the literature review.

Factors that affect the impact of ICTs on education

The findings revealed that the use of digital technologies in education affects a variety of actors within a school’s ecosystem. First, we observed that as technologies evolve, so does the interest of the research community to apply them to school settings. Figure  2 summarizes the trends identified in current research around the impact of digital technologies on schools’ digital capacity and transformation as found in the present study. Starting as early as 2005, when computers, simulations, and interactive boards were the most commonly applied tools in school interventions (e.g., Eng, 2005 ; Liao et al., 2007 ; Moran et al., 2008 ; Tamim et al., 2011 ), moving towards the use of learning platforms (Jewitt et al., 2011 ), then to the use of mobile devices and digital games (e.g., Tamim et al., 2015 ; Sung et al., 2016 ; Talan et al., 2020 ), as well as e-books (e.g., Savva et al., 2022 ), to the more recent advanced technologies, such as AR and VR applications (e.g., Garzón & Acevedo, 2019 ; Garzón et al., 2020 ; Kalemkuş & Kalemkuş, 2022 ), or robotics and AI (e.g., Su & Yang, 2022 ; Su et al., 2022 ). As this evolution shows, digital technologies are a concept in flux with different affordances and characteristics. Additionally, from an instructional perspective, there has been a growing interest in different modes and models of content delivery such as online, blended, and hybrid modes (e.g., Cheok & Wong, 2015 ; Kazu & Yalçin, 2022 ; Ulum, 2022 ). This is an indication that the value of technologies to support teaching and learning as well as other school-related practices is increasingly recognized by the research and school community. The impact results from the literature review indicate that ICT integration on students’ learning outcomes has effects that are small (Coban et al., 2022 ; Eng, 2005 ; Higgins et al., 2012 ; Schmid et al., 2014 ; Tamim et al., 2015 ; Zheng et al., 2016 ) to moderate (Garzón & Acevedo, 2019 ; Garzón et al., 2020 ; Liao et al., 2007 ; Sung et al., 2016 ; Talan et al., 2020 ; Wen & Walters, 2022 ). That said, a number of recent studies have reported high effect sizes (e.g., Kazu & Yalçin, 2022 ).

Current work and trends in the study of the impact of digital technologies on schools’ digital capacity

Based on these findings, several authors have suggested that the impact of technology on education depends on several variables and not on the technology per se (Tamim et al., 2011 ; Higgins et al., 2012 ; Archer et al., 2014 ; Sung et al., 2016 ; Haßler et al., 2016 ; Chauhan, 2017 ; Lee et al., 2020 ; Lei et al., 2022a ). While the impact of ICTs on student achievement has been thoroughly investigated by researchers, other aspects related to school life that are also affected by ICTs, such as equality, inclusion, and social integration have received less attention. Further analysis of the literature review has revealed a greater investment in ICT interventions to support learning and teaching in the core subjects of literacy and STEM disciplines, especially mathematics, and science. These were the most common subjects studied in the reviewed papers often drawing on national testing results, while studies that investigated other subject areas, such as social studies, were limited (Chauhan, 2017 ; Condie & Munro, 2007 ). As such, research is still lacking impact studies that focus on the effects of ICTs on a range of curriculum subjects.

The qualitative research provided additional information about the impact of digital technologies on education, documenting positive effects and giving more details about implications, recommendations, and future research directions. Specifically, the findings regarding the role of ICTs in supporting learning highlight the importance of teachers’ instructional practice and the learning context in the use of technologies and consequently their impact on instruction (Çelik, 2022 ; Schmid et al., 2014 ; Tamim et al., 2015 ). The review also provided useful insights regarding the various factors that affect the impact of digital technologies on education. These factors are interconnected and play a vital role in the transformation process. Specifically, these factors include a) digital competencies; b) teachers’ personal characteristics and professional development; c) school leadership and management; d) connectivity, infrastructure, and government support; e) administration and data management practices; f) students’ socio-economic background and family support and g) the socioeconomic context of the school and emergency situations. It is worth noting that we observed factors that affect the integration of ICTs in education but may also be affected by it. For example, the frequent use of ICTs and the use of laptops by students for instructional purposes positively affect the development of digital competencies (Zheng et al., 2016 ) and at the same time, the digital competencies affect the use of ICTs (Fu, 2013 ; Higgins et al., 2012 ). As a result, the impact of digital technologies should be explored more as an enabler of desirable and new practices and not merely as a catalyst that improves the output of the education process i.e. namely student attainment.

Conclusions

Digital technologies offer immense potential for fundamental improvement in schools. However, investment in ICT infrastructure and professional development to improve school education are yet to provide fruitful results. Digital transformation is a complex process that requires large-scale transformative changes that presuppose digital capacity and preparedness. To achieve such changes, all actors within the school’s ecosystem need to share a common vision regarding the integration of ICTs in education and work towards achieving this goal. Our literature review, which synthesized quantitative and qualitative data from a list of meta-analyses and review studies, provided useful insights into the impact of ICTs on different school stakeholders and showed that the impact of digital technologies touches upon many different aspects of school life, which are often overlooked when the focus is on student achievement as the final output of education. Furthermore, the concept of digital technologies is a concept in flux as technologies are not only different among them calling for different uses in the educational practice but they also change through time. Additionally, we opened a forum for discussion regarding the factors that affect a school’s digital capacity and transformation. We hope that our study will inform policy, practice, and research and result in a paradigm shift towards more holistic approaches in impact and assessment studies.

Study limitations and future directions

We presented a review of the study of digital technologies' impact on education and factors influencing schools’ digital capacity and transformation. The study results were based on a non-systematic literature review grounded on the acquisition of documentation in specific databases. Future studies should investigate more databases to corroborate and enhance our results. Moreover, search queries could be enhanced with key terms that could provide additional insights about the integration of ICTs in education, such as “policies and strategies for ICT integration in education”. Also, the study drew information from meta-analyses and literature reviews to acquire evidence about the effects of ICT integration in schools. Such evidence was mostly based on the general conclusions of the studies. It is worth mentioning that, we located individual studies which showed different, such as negative or neutral results. Thus, further insights are needed about the impact of ICTs on education and the factors influencing the impact. Furthermore, the nature of the studies included in meta-analyses and reviews is different as they are based on different research methodologies and data gathering processes. For instance, in a meta-analysis, the impact among the studies investigated is measured in a particular way, depending on policy or research targets (e.g., results from national examinations, pre-/post-tests). Meanwhile, in literature reviews, qualitative studies offer additional insights and detail based on self-reports and research opinions on several different aspects and stakeholders who could affect and be affected by ICT integration. As a result, it was challenging to draw causal relationships between so many interrelating variables.

Despite the challenges mentioned above, this study envisaged examining school units as ecosystems that consist of several actors by bringing together several variables from different research epistemologies to provide an understanding of the integration of ICTs. However, the use of other tools and methodologies and models for evaluation of the impact of digital technologies on education could give more detailed data and more accurate results. For instance, self-reflection tools, like SELFIE—developed on the DigCompOrg framework- (Kampylis et al., 2015 ; Bocconi & Lightfoot, 2021 ) can help capture a school’s digital capacity and better assess the impact of ICTs on education. Furthermore, the development of a theory of change could be a good approach for documenting the impact of digital technologies on education. Specifically, theories of change are models used for the evaluation of interventions and their impact; they are developed to describe how interventions will work and give the desired outcomes (Mayne, 2015 ). Theory of change as a methodological approach has also been used by researchers to develop models for evaluation in the field of education (e.g., Aromatario et al., 2019 ; Chapman & Sammons, 2013 ; De Silva et al., 2014 ).

We also propose that future studies aim at similar investigations by applying more holistic approaches for impact assessment that can provide in-depth data about the impact of digital technologies on education. For instance, future studies could focus on different research questions about the technologies that are used during the interventions or the way the implementation takes place (e.g., What methodologies are used for documenting impact? How are experimental studies implemented? How can teachers be taken into account and trained on the technology and its functions? What are the elements of an appropriate and successful implementation? How is the whole intervention designed? On which learning theories is the technology implementation based?).

Future research could also focus on assessing the impact of digital technologies on various other subjects since there is a scarcity of research related to particular subjects, such as geography, history, arts, music, and design and technology. More research should also be done about the impact of ICTs on skills, emotions, and attitudes, and on equality, inclusion, social interaction, and special needs education. There is also a need for more research about the impact of ICTs on administration, management, digitalization, and home-school relationships. Additionally, although new forms of teaching and learning with the use of ICTs (e.g., blended, hybrid, and online learning) have initiated several investigations in mainstream classrooms, only a few studies have measured their impact on students’ learning. Additionally, our review did not document any study about the impact of flipped classrooms on K-12 education. Regarding teaching and learning approaches, it is worth noting that studies referred to STEM or STEAM did not investigate the impact of STEM/STEAM as an interdisciplinary approach to learning but only investigated the impact of ICTs on learning in each domain as a separate subject (science, technology, engineering, arts, mathematics). Hence, we propose future research to also investigate the impact of the STEM/STEAM approach on education. The impact of emerging technologies on education, such as AR, VR, robotics, and AI has also been investigated recently, but more work needs to be done.

Finally, we propose that future studies could focus on the way in which specific factors, e.g., infrastructure and government support, school leadership and management, students’ and teachers’ digital competencies, approaches teachers utilize in the teaching and learning (e.g., blended, online and hybrid learning, flipped classrooms, STEM/STEAM approach, project-based learning, inquiry-based learning), affect the impact of digital technologies on education. We hope that future studies will give detailed insights into the concept of schools’ digital transformation through further investigation of impacts and factors which influence digital capacity and transformation based on the results and the recommendations of the present study.

Acknowledgements

This project has received funding under Grant Agreement No Ref Ares (2021) 339036 7483039 as well as funding from the European Union’s Horizon 2020 Research and Innovation Program under Grant Agreement No 739578 and the Government of the Republic of Cyprus through the Deputy Ministry of Research, Innovation and Digital Policy. The UVa co-authors would like also to acknowledge funding from the European Regional Development Fund and the National Research Agency of the Spanish Ministry of Science and Innovation, under project grant PID2020-112584RB-C32.

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