books about ai and education

Artificial Intelligence and Education: A Reading List

A bibliography to help educators prepare students and themselves for a future shaped by AI—with all its opportunities and drawbacks.

How should education change to address, incorporate, or challenge today’s AI systems, especially powerful large language models? What role should educators and scholars play in shaping the future of generative AI? The release of ChatGPT in November 2022 triggered an explosion of news, opinion pieces, and social media posts addressing these questions. Yet many are not aware of the current and historical body of academic work that offers clarity, substance, and nuance to enrich the discourse.

Linking the terms “AI” and “education” invites a constellation of discussions. This selection of articles is hardly comprehensive, but it includes explanations of AI concepts and provides historical context for today’s systems. It describes a range of possible educational applications as well as adverse impacts, such as learning loss and increased inequity. Some articles touch on philosophical questions about AI in relation to learning, thinking, and human communication. Others will help educators prepare students for civic participation around concerns including information integrity, impacts on jobs, and energy consumption. Yet others outline educator and student rights in relation to AI and exhort educators to share their expertise in societal and industry discussions on the future of AI.

Nabeel Gillani, Rebecca Eynon, Catherine Chiabaut, and Kelsey Finkel, “ Unpacking the ‘Black Box’ of AI in Education ,” Educational Technology & Society 26, no. 1 (2023): 99–111.

Whether we’re aware of it or not, AI was already widespread in education before ChatGPT. Nabeel Gillani et al. describe AI applications such as learning analytics and adaptive learning systems, automated communications with students, early warning systems, and automated writing assessment. They seek to help educators develop literacy around the capacities and risks of these systems by providing an accessible introduction to machine learning and deep learning as well as rule-based AI. They present a cautious view, calling for scrutiny of bias in such systems and inequitable distribution of risks and benefits. They hope that engineers will collaborate deeply with educators on the development of such systems.

Jürgen Rudolph, Samson Tan, and Shannon Tan, “ ChatGPT: Bullshit Spewer or the End of Traditional Assessments in Higher Education? ” The Journal of Applied Learning and Teaching 6, no. 1 (January 24, 2023).

Jürgen Rudolph et al. give a practically oriented overview of ChatGPT’s implications for higher education. They explain the statistical nature of large language models as they tell the history of OpenAI and its attempts to mitigate bias and risk in the development of ChatGPT. They illustrate ways ChatGPT can be used with examples and screenshots. Their literature review shows the state of artificial intelligence in education (AIEd) as of January 2023. An extensive list of challenges and opportunities culminates in a set of recommendations that emphasizes explicit policy as well as expanding digital literacy education to include AI.

Emily M. Bender, Timnit Gebru, Angela McMillan-Major, and Shmargaret Shmitchell, “ On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 ,” FAccT ’21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (March 2021): 610–623.

Student and faculty understanding of the risks and impacts of large language models is central to AI literacy and civic participation around AI policy. This hugely influential paper details documented and likely adverse impacts of the current data-and-resource-intensive, non-transparent mode of development of these models. Bender et al. emphasize the ways in which these costs will likely be borne disproportionately by marginalized groups. They call for transparency around the energy use and cost of these models as well as transparency around the data used to train them. They warn that models perpetuate and even amplify human biases and that the seeming coherence of these systems’ outputs can be used for malicious purposes even though it doesn’t reflect real understanding.

The authors argue that inclusive participation in development can encourage alternate development paths that are less resource intensive. They further argue that beneficial applications for marginalized groups, such as improved automatic speech recognition systems, must be accompanied by plans to mitigate harm.

Erik Brynjolfsson, “ The Turing Trap: The Promise & Peril of Human-Like Artificial Intelligence ,” Daedalus 151, no. 2 (2022): 272–87.

Erik Brynjolfsson argues that when we think of artificial intelligence as aiming to substitute for human intelligence, we miss the opportunity to focus on how it can complement and extend human capabilities. Brynjolfsson calls for policy that shifts AI development incentives away from automation toward augmentation. Automation is more likely to result in the elimination of lower-level jobs and in growing inequality. He points educators toward augmentation as a framework for thinking about AI applications that assist learning and teaching. How can we create incentives for AI to support and extend what teachers do rather than substituting for teachers? And how can we encourage students to use AI to extend their thinking and learning rather than using AI to skip learning?

Kevin Scott, “ I Do Not Think It Means What You Think It Means: Artificial Intelligence, Cognitive Work & Scale ,” Daedalus 151, no. 2 (2022): 75–84.

Brynjolfsson’s focus on AI as “augmentation” converges with Microsoft computer scientist Kevin Scott’s focus on “cognitive assistance.” Steering discussion of AI away from visions of autonomous systems with their own goals, Scott argues that near-term AI will serve to help humans with cognitive work. Scott situates this assistance in relation to evolving historical definitions of work and the way in which tools for work embody generalized knowledge about specific domains. He’s intrigued by the way deep neural networks can represent domain knowledge in new ways, as seen in the unexpected coding capabilities offered by OpenAI’s GPT-3 language model, which have enabled people with less technical knowledge to code. His article can help educators frame discussions of how students should build knowledge and what knowledge is still relevant in contexts where AI assistance is nearly ubiquitous.

Laura D. Tyson and John Zysman, “ Automation, AI & Work ,” Daedalus 151, no. 2 (2022): 256–71.

How can educators prepare students for future work environments integrated with AI and advise students on how majors and career paths may be affected by AI automation? And how can educators prepare students to participate in discussions of government policy around AI and work? Laura Tyson and John Zysman emphasize the importance of policy in determining how economic gains due to AI are distributed and how well workers weather disruptions due to AI. They observe that recent trends in automation and gig work have exacerbated inequality and reduced the supply of “good” jobs for low- and middle-income workers. They predict that AI will intensify these effects, but they point to the way collective bargaining, social insurance, and protections for gig workers have mitigated such impacts in countries like Germany. They argue that such interventions can serve as models to help frame discussions of intelligent labor policies for “an inclusive AI era.”

Todd C. Helmus, Artificial Intelligence, Deepfakes, and Disinformation: A Primer (RAND Corporation, 2022).

Educators’ considerations of academic integrity and AI text can draw on parallel discussions of authenticity and labeling of AI content in other societal contexts. Artificial intelligence has made deepfake audio, video, and images as well as generated text much more difficult to detect as such. Here, Todd Helmus considers the consequences to political systems and individuals as he offers a review of the ways in which these can and have been used to promote disinformation. He considers ways to identify deepfakes and ways to authenticate provenance of videos and images. Helmus advocates for regulatory action, tools for journalistic scrutiny, and widespread efforts to promote media literacy. As well as informing discussions of authenticity in educational contexts, this report might help us shape curricula to teach students about the risks of deepfakes and unlabeled AI.

William Hasselberger, “ Can Machines Have Common Sense? ” The New Atlantis 65 (2021): 94–109.

Students, by definition, are engaged in developing their cognitive capacities; their understanding of their own intelligence is in flux and may be influenced by their interactions with AI systems and by AI hype. In his review of The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do by Erik J. Larson, William Hasselberger warns that in overestimating AI’s ability to mimic human intelligence we devalue the human and overlook human capacities that are integral to everyday life decision making, understanding, and reasoning. Hasselberger provides examples of both academic and everyday common-sense reasoning that continue to be out of reach for AI. He provides a historical overview of debates around the limits of artificial intelligence and its implications for our understanding of human intelligence, citing the likes of Alan Turing and Marvin Minsky as well as contemporary discussions of data-driven language models.

Gwo-Jen Hwang and Nian-Shing Chen, “ Exploring the Potential of Generative Artificial Intelligence in Education: Applications, Challenges, and Future Research Directions ,” Educational Technology & Society 26, no. 2 (2023).

Gwo-Jen Hwang and Nian-Shing Chen are enthusiastic about the potential benefits of incorporating generative AI into education. They outline a variety of roles a large language model like ChatGPT might play, from student to tutor to peer to domain expert to administrator. For example, educators might assign students to “teach” ChatGPT on a subject. Hwang and Chen provide sample ChatGPT session transcripts to illustrate their suggestions. They share prompting techniques to help educators better design AI-based teaching strategies. At the same time, they are concerned about student overreliance on generative AI. They urge educators to guide students to use it critically and to reflect on their interactions with AI. Hwang and Chen don’t touch on concerns about bias, inaccuracy, or fabrication, but they call for further research into the impact of integrating generative AI on learning outcomes.

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Lauren Goodlad and Samuel Baker, “ Now the Humanities Can Disrupt ‘AI’ ,” Public Books (February 20, 2023).

Lauren Goodlad and Samuel Baker situate both academic integrity concerns and the pressures on educators to “embrace” AI in the context of market forces. They ground their discussion of AI risks in a deep technical understanding of the limits of predictive models at mimicking human intelligence. Goodlad and Baker urge educators to communicate the purpose and value of teaching with writing to help students engage with the plurality of the world and communicate with others. Beyond the classroom, they argue, educators should question tech industry narratives and participate in public discussion on regulation and the future of AI. They see higher education as resilient: academic skepticism about former waves of hype around MOOCs, for example, suggests that educators will not likely be dazzled or terrified into submission to AI. Goodlad and Baker hope we will instead take up our place as experts who should help shape the future of the role of machines in human thought and communication.

Kathryn Conrad, “ Sneak Preview: A Blueprint for an AI Bill of Rights for Education ,” Critical AI 2.1 (July 17, 2023).

How can the field of education put the needs of students and scholars first as we shape our response to AI, the way we teach about it, and the way we might incorporate it into pedagogy? Kathryn Conrad’s manifesto builds on and extends the Biden administration’s Office of Science and Technology Policy 2022 “Blueprint for an AI Bill of Rights.” Conrad argues that educators should have input into institutional policies on AI and access to professional development around AI. Instructors should be able to decide whether and how to incorporate AI into pedagogy, basing their decisions on expert recommendations and peer-reviewed research. Conrad outlines student rights around AI systems, including the right to know when AI is being used to evaluate them and the right to request alternate human evaluation. They deserve detailed instructor guidance on policies around AI use without fear of reprisals. Conrad maintains that students should be able to appeal any charges of academic misconduct involving AI, and they should be offered alternatives to any AI-based assignments that might put their creative work at risk of exposure or use without compensation. Both students’ and educators’ legal rights must be respected in any educational application of automated generative systems.

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More From Forbes

5 Books On AI In Education And Why You Should Read Them

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I've read far too many books on ChatGPT and artificial intelligence.

Almost all of them are a waste of time when it comes to applying them to education.

But, there are five books educators on LinkedIn, X (formerly Twitter) and Facebook have recommended. And it's these five books I recommend to every educator exploring AI.

I've authored a best-seller for educators on artificial intelligence, " The AI Classroom: The Ultimate Guide to Artificial Intelligence in Education ," and I'm currently working on a practical guide for leaders on AI strategy. Being deeply immersed in the world of AI books for educators, I can confidently say that whether you are new to AI, experimenting with it, or already incorporating it into your practices, these are books worth your time:

AI For Educators By Matt Miller

AI for Educators is a readable guide that translates AI through a teacher lens.

It offers practical ideas you can use in class right away. It unlocks powerful ways to streamline teaching, save time and paints a picture of the future our students will face, providing questions you can help them grapple with.

Dana Leonardo, a technology integration educator from Gilbert, Arizona, praises the book for its clarity and practical advice: "Miller's book gets at the heart of what educators need to know about AI, including practical applications, benefits, and cautions. This text brilliantly explains how and why we need to use AI as a tool, while leveraging our most valuable asset—our humanity."

Best High-Yield Savings Accounts Of 2024

Best 5% interest savings accounts of 2024, brave new worlds by salman khan.

Salman Khan, the visionary behind Khan Academy, explores how AI and GPT technology will transform learning.

Khan offers a road map for teachers, parents and students to navigate this exciting new world. Beyond technology, Khan delves into the ethical and social implications of AI, providing insights on how administrators, guidance counselors and hiring managers can harness AI to build a more accessible education system.

Kevin Soli, a homeschooling parent from Papua New Guinea, highlights the book's value: "I homeschool my children so this book is very encouraging for me as a parent. ChatGPT is like your tech-buddy—not just to answer your prompts but to prompt you too, asking probing questions that challenge assumptions, clarify concepts and encourage deeper dialogue."

Practical AI Strategies By Leon Furze

Furze explores the opportunities and challenges of AI in education.

He offers insights into its workings and ethical considerations. The book guides readers through the construction and ethics of generative AI, navigates policy landscapes and provides practical strategies. It has detailed sections on text and image generation and preparations for multimodal technologies like video, audio and 3D generation.

Al Kingsley, chair of Hampton Academies Trust in the UK, emphasizes the book’s approach: “This is an excellent book. It’s highly accessible, evidence informed and structured to step you through AI basics, ethics and assessment.”

Teaching with AI By Jose Antonio Bowen And C. Edward Watson

Bowen and Watson present emerging and powerful research on the seismic changes AI is already creating in schools and the workplace, providing invaluable insights into what AI can accomplish in the classroom and beyond.

Dr. Heather M. Brown, an instructional designer from Virginia, shared, “The book resonates with me because it adopts a holistic view of AI's potential, challenging us to embrace this revolution as an opportunity to reimagine education.”

The AI Infused Classroom By Holly Clark

The key to successfully integrating any digital tool, according to Clark, is to focus on the deep learning and masterful pedagogy teachers can achieve amidst educational shifts.

The AI Infused Classroom emphasizes that AI will bring about changes, but it does not replace the need for well-trained and highly qualified teachers in the classroom. Students need educators’ guidance now more than ever to prepare for the world of AI. With the right mindset, questions and strategies, educators can use AI to create and broaden meaningful learning experiences for every student.

The AI Classroom and most of the books listed above tackle the issues of ethics and equity in AI education. But educators always welcome more guidance on this topic. That's why I’m looking forward to the upcoming book, "The Promises and Perils of AI in Education" by Ken Shelton and Dee Lanier. It’s not published yet, but it should be available soon.

One Reminder Before You Go

Reading is great, but applying what you read is better.

Reading books on AI in education feels productive. And it is! Until a certain point. Then, it turns into procrastination disguised as "research." How do you avoid falling into this trap?

Easy—start integrating AI into your educational practices every day.

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Artificial Intelligence In Education: Promises and Implications for Teaching and Learning Paperback – February 28, 2019

• Print length 242 pages
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• Publisher ‏ : ‎ Independently published (February 28, 2019)
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Artificial Intelligence in Education

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About the authors

Charles fadel.

Charles Fadel is a global education thought leader and author, futurist and inventor; founder and chairman of Center for Curriculum Redesign; chair education committee at BIAC/OECD; Member of OECD AI Experts group; co-author of “Education for the Age of AI” (2024), “Artificial Intelligence in Education” (2019); “Four-Dimensional Education” (framework in 23 languages) and “21st Century Skills”. He has worked with education systems and institutions in more than 30 countries, and spent 25 years in technology management (M/A-COM; Analog Devices; and as founder of NeurodyneAI). Formerly: founder and president Fondation Helvetica Educatio (Geneva, Switzerland); Global Education Lead at Cisco Systems, visiting scholar at MIT ESG and Wharton/Penn CLO, project director Harvard GSE; member President’s Council at Olin College of Engineering, angel investor with Beacon Angels. BSEE, MBA, seven patents awarded & one pending.

Wayne Holmes

Wayne Holmes (PhD, University of Oxford) is Professor of Critical Studies of Artificial Intelligence and Education at University College London (UK). His research takes a critical studies perspective to teaching and learning with and about Artificial Intelligence (AI&ED), and their ethical, human rights, and social justice implications. Wayne is leading the Council of Europe’s AI&ED expert group, for which he co-wrote ‘AI and Education. A Critical View through the Lens of Human Rights, Democracy, and the Rule of Law’, and which is developing legislation to protect the human rights of students and teachers engaging with AI-enabled systems. He is also Consultant for UNESCO, for which he co-wrote ‘AI and Education: Guidance for Policy-makers’ and ‘Guidance for Generative AI in Education and Research’; a Senior Researcher in AI&ED for the International Research Centre on Artificial Intelligence under the auspices of UNESCO; and an AI&ED expert for the United Nations. Wayne has also co-written ‘Artificial Intelligence in Education. Promise and Implications for Teaching and Learning’, ‘State of the Art and Practice in AI in Education’, and ‘The Ethics of AI in Education. Practices, Challenges and Debates’. He has given invited keynotes about AI&ED in countries around the world.

Maya Bialik

Since earning her Ed. M. in Mind, Brain, & Education from the Harvard Graduate School of Education in 2012, Maya Bialik has worked directly with educators and policymakers in jurisdictions around the world on many parts of the education system, from writing curriculum, to evaluating programs, running professional development, facilitating seminars and workshops, advising educational publishers, designing standards, conducting research, and publishing books and papers on both primary research and its synthesis into theoretical frameworks.

She has also worked on outside-the-box educational projects including interactive exhibitions, educational games, comics, and VR experiences. Her expertise ranges from social and emotional training, to science communication, math education, information literacy, learning sciences, improv, AI in education, neuroscience, diversity & inclusion, and redesigning curriculum for the 21st century. Her outside perspective helps her bring a fresh eye to organizations, helping them think critically about current patterns, and creatively about what's possible.

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An Introduction to Artificial Intelligence in Education

• © 2021
• Shengquan Yu 0 ,

Advanced Innovation Center for Future Education, Faculty of Education, Beijing Normal University, Beijing, China

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• Presents the most education-relevant AI technologies in a simple and straightforward way
• Utilizes massive data and comprehensive analysis from schools in China and abroad
• Facilitates readers’ understanding by exploring real-world cases

Part of the book series: Bridging Human and Machine: Future Education with Intelligence (BHMFEI)

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The Intertwined Histories of Artificial Intelligence and Education

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Table of contents (9 chapters)

Front matter, introduction.

Shengquan Yu, Yu Lu

An Overview of AI

Intelligent learning environments, intelligent learning processes, intelligent teacher assistant, intelligent educational evaluation, intelligent educational management and service, frontiers of ai in education, prospects and reflections: looking into the future, authors and affiliations, about the authors, bibliographic information.

Book Title : An Introduction to Artificial Intelligence in Education

Authors : Shengquan Yu, Yu Lu

Series Title : Bridging Human and Machine: Future Education with Intelligence

DOI : https://doi.org/10.1007/978-981-16-2770-5

Publisher : Springer Singapore

eBook Packages : Education , Education (R0)

Copyright Information : Springer Nature Singapore Pte Ltd. 2021

Hardcover ISBN : 978-981-16-2769-9 Published: 01 December 2021

Softcover ISBN : 978-981-16-2772-9 Published: 02 December 2022

eBook ISBN : 978-981-16-2770-5 Published: 29 November 2021

Series ISSN : 2662-5342

Series E-ISSN : 2662-5350

Edition Number : 1

Number of Pages : VIII, 198

Number of Illustrations : 20 b/w illustrations, 77 illustrations in colour

Topics : Educational Technology , Technology and Digital Education , Computers and Education

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Book description

Clear away the fog surrounding AI in education—and regain your peace of mind

Among teachers, there is a cloud of rumors, confusion, and fear surrounding the rise of artificial intelligence. AI and the Future of Education is a timely response to this general state of panic, showing you that AI is a tool to leverage, not a threat to teaching and learning. By understanding what AI is, what it does, and how it can be used to enhance education, you can let go of anxiety and uncertainty, and learn to embrace artificial intelligence.

It's true that, along with tremendous opportunities, AI presents some challenges for the field of education. In this book, Priten Shah, a Harvard M.Ed. with a robust background in educational innovation, helps you face these challenges head on, so you can gain the knowledge and skills you need to use AI effectively in your classroom. Thanks to this thorough consideration of ethical considerations and practical approaches, you can develop your own strategy for leveraging AI in administrative tasks, lesson design, professional development, and beyond.

• Understand what AI and machine learning are, and learn about new developments like ChatGPT
• Discover strategies for engaging students more fully using AI
• Automate administrative tasks, grading and feedback, and assessments
• Use AI in innovative ways to promote higher-order thinking skills
• Examine ethical considerations of AI, including the achievement gap, privacy concerns, and bias

For K-12 educators, as well as leaders and policymakers who want to understand the role of technology in education, AI and the Future of Education is a valuable resource that can change AI from an unknown entity to an indispensable tool.

Table of contents

• Additional Praise for AI and the Future of Education
• OPPORTUNITIES AND CHALLENGES: AI IN THE CLASSROOM
• SUSTAINABLE AI INTEGRATION STRATEGIES
• FUNDAMENTALS OF AI AND MACHINE LEARNING
• EXPLORING GENERATIVE AI
• EFFECTIVE PROMPT WRITING FOR TEACHERS
• PREPARING STUDENTS FOR THE AI‐DRIVEN WORKFORCE
• DEVELOPING AI LITERACY AND COMPUTATIONAL THINKING
• FOSTERING A GROWTH MINDSET AND LIFELONG LEARNING CULTURE
• CULTIVATING CREATIVITY AND INNOVATION SKILLS IN THE AI ERA
• LEARNING THEORIES IN THE AI ERA: CONSTRUCTIVIST, BEHAVIORIST, AND SOCIOCULTURAL APPROACHES
• ACTIVE LEARNING AND AI: TRANSFORMING THE CLASSROOM EXPERIENCE
• PROBLEM‐ AND PROJECT‐BASED LEARNING STRATEGIES WITH AI
• BLOOM'S TAXONOMY AND CRITICAL THINKING SKILLS IN THE AI‐ENHANCED CLASSROOM
• DIFFERENTIATED INSTRUCTION: AI‐GENERATED CUSTOMIZED ACTIVITIES
• FOSTERING COLLABORATION AND RELATIONSHIP‐BUILDING THROUGH AI INTEGRATION
• INQUIRY‐BASED LEARNING AND AI: ENCOURAGING STUDENT‐CENTERED EXPLORATION
• LESSON PLANNING AND CURRICULAR DESIGN
• CREATING LEARNING ASSETS
• FORMATIVE ACTIVITIES: GENERATED WORKSHEETS, GAMES, AND MORE
• SUMMATIVE ASSESSMENTS: QUIZZES, RUBRICS, AND PERFORMANCE TASKS
• IMPLICATIONS FOR SPECIAL EDUCATION, ELL, AND INCLUSIVE CLASSROOMS
• DISTANCE AND REMOTE EDUCATION
• STREAMLINING COMMUNICATION AND SCHEDULING
• AI‐ENHANCED FEEDBACK AND GRADING
• OPTIMIZING PAPERWORK AND RECORDKEEPING TASKS
• INTELLIGENT TUTORING SYSTEMS
• PERSONALIZED LEARNING PATHWAYS
• GAMIFICATION AND LEARNING EXPERIENCES
• DEBATES AND DISCUSSIONS
• EXECUTIVE FUNCTIONING AND SOCIAL‐EMOTIONAL LEARNING
• RESPONSIBLE AND ETHICAL USE OF AI
• DIGITAL CITIZENSHIP IN THE AI ERA
• REFINING AND ITERATING ON AI‐GENERATED CONTENT
• ADDRESSING AI‐RELATED MISINFORMATION AND BIAS
• REDUCING, NOT EXPANDING, THE ACHIEVEMENT GAP
• ADDRESSING THE DIGITAL DIVIDE AND ENSURING ACCESS
• PROTECTING STUDENT PRIVACY AND DATA SECURITY
• THE IMPORTANCE OF CONTINUED ADAPTATION AND GROWTH
• ESSENTIAL AI COMPETENCIES FOR EDUCATORS
• LEVERAGING AI FOR PERSONAL AND PROFESSIONAL DEVELOPMENT
• Chapter 11: Adapting and Growing with AI in Education
• Acknowledgments
• About the Author
• End User License Agreement

Product information

• Title: AI and the Future of Education
• Author(s): Priten Shah
• Release date: September 2023
• Publisher(s): Jossey-Bass
• ISBN: 9781394219247

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The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies …

DeFi and the Future of Finance

by Campbell R. Harvey, Ashwin Ramachandran, Joey Santoro, Fred Ehrsam, Vitalik Buterin

During the Global Financial Crisis in 2008, our financial infrastructure failed. Govern­ments bailed out the very …

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