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This page is the AI Wiki index of books about artificial intelligence, organised by type. It collects textbooks used in university courses, popular non-fiction written for general readers, earlier classics from the founders of the field, and fiction that has shaped how the public thinks about thinking machines. Every entry has been checked against publisher records, author bibliographies, or library catalogues. Where a book has gone through multiple editions, the most widely used edition is noted in the table.
The list is not exhaustive. AI has been written about since the 1940s, and the number of trade books published since the public release of ChatGPT in November 2022 alone runs into the hundreds. The selection here favours titles that are widely cited in the literature, that have been adopted as course texts, or that have shaped public debate enough to be quoted across newspapers, podcasts, and policy papers.
Books about AI fall into four rough groups. Textbooks and academic works present the mathematical and algorithmic foundations of the field. They are usually long, dense, and updated in new editions every few years. Popular non-fiction explains the same ideas to general readers, often weaving in interviews, case studies, and predictions. The third category covers earlier classics, books written before the deep learning revolution that still get assigned in graduate seminars or quoted in modern essays. The fourth category is fiction, mostly science fiction, that has either shaped the public imagination about AI or has been written by authors who studied the technical literature carefully.
The tables below use sentence case in column headings. Years refer to the first edition unless noted. Publishers are listed by their imprint at the time of first publication. ISBNs are given where they uniquely identify a book; for older titles with many reprints, ISBN is omitted.
| Title | Year | Authors | Publisher | Notes |
|---|---|---|---|---|
| Deep Learning | 2016 | Ian Goodfellow, Yoshua Bengio, Aaron Courville | MIT Press | The standard graduate text on deep neural networks. Available free online at deeplearningbook.org. |
| Pattern Recognition and Machine Learning | 2006 | Christopher Bishop | Springer | Long the default text for Bayesian and probabilistic methods. Released as a free PDF by the author in 2024. |
| The Elements of Statistical Learning | 2001 (2nd ed. 2009) | Trevor Hastie, Robert Tibshirani, Jerome Friedman | Springer | A statistician's view of machine learning. Free PDF available from Stanford. |
| An Introduction to Statistical Learning | 2013 (2nd ed. 2021) | Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani | Springer | Companion volume to The Elements of Statistical Learning, written for undergraduates with code in R and a separate Python edition. |
| Artificial Intelligence: A Modern Approach | 1995 (4th ed. 2020) | Stuart Russell, Peter Norvig | Pearson / Prentice Hall | The most widely adopted undergraduate AI textbook in the world, used in over 1,500 universities. The fourth edition added chapters on deep learning and ethics. |
| Reinforcement Learning: An Introduction | 1998 (2nd ed. 2018) | Richard S. Sutton, Andrew G. Barto | MIT Press | The standard text on reinforcement learning. The authors shared the 2024 Turing Award for the work. |
| Mathematics for Machine Learning | 2020 | Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong | Cambridge University Press | A free textbook that covers the linear algebra, calculus, and probability needed to follow ML papers. |
| Probabilistic Machine Learning: An Introduction | 2022 | Kevin P. Murphy | MIT Press | First volume of a two-volume update to Murphy's 2012 book, with expanded coverage of deep learning. |
| Probabilistic Machine Learning: Advanced Topics | 2023 | Kevin P. Murphy | MIT Press | Second volume, covering inference, generative models, decision-making, and structured prediction. |
| Machine Learning: A Probabilistic Perspective | 2012 | Kevin P. Murphy | MIT Press | The widely used predecessor to the 2022/2023 two-volume set. |
| Dive into Deep Learning | 2020 (multiple editions) | Aston Zhang, Zachary Lipton, Mu Li, Alexander J. Smola | Cambridge University Press / d2l.ai | A free interactive textbook with runnable Jupyter notebooks. Used as a course text at over 500 universities. |
| Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow | 2017 (3rd ed. 2022) | Aurélien Géron | O'Reilly | The most popular practical introduction to applied ML. The third edition covers transformers and generative models. |
| Speech and Language Processing | 2000 (3rd ed. drafts ongoing) | Daniel Jurafsky, James H. Martin | Pearson / draft online | The standard reference for natural language processing. The third edition has been distributed as ongoing free chapter drafts since 2018. |
| Neural Networks and Deep Learning | 2015 | Michael Nielsen | Determination Press | A free online introduction to neural network fundamentals, written for self-learners. |
| Information Theory, Inference, and Learning Algorithms | 2003 | David J. C. MacKay | Cambridge University Press | Combines information theory and machine learning in a single text. Available free online from the author's site. |
| Bayesian Reasoning and Machine Learning | 2012 | David Barber | Cambridge University Press | A graduate text on probabilistic models, available as a free PDF. |
| Foundations of Machine Learning | 2012 (2nd ed. 2018) | Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar | MIT Press | Covers the learning theory side of the field, including PAC learning and Rademacher complexity. |
| Understanding Machine Learning: From Theory to Algorithms | 2014 | Shai Shalev-Shwartz, Shai Ben-David | Cambridge University Press | A widely used theory-oriented introduction. Free PDF on the authors' websites. |
| Computer Vision: Algorithms and Applications | 2010 (2nd ed. 2022) | Richard Szeliski | Springer | The standard text on computer vision, with the second edition expanded to cover deep learning approaches. |
| Deep Learning with Python | 2017 (2nd ed. 2021) | François Chollet | Manning | A practical Keras-focused introduction by the creator of Keras. |
| Grokking Deep Learning | 2019 | Andrew W. Trask | Manning | A hands-on, NumPy-only introduction aimed at programmers without a math background. |
| The Hundred-Page Machine Learning Book | 2019 | Andriy Burkov | self-published | A concise overview that became a popular reference for practitioners. |
| Machine Learning Engineering | 2020 | Andriy Burkov | True Positive Inc. | Companion volume covering the production side of ML systems. |
| Designing Machine Learning Systems | 2022 | Chip Huyen | O'Reilly | Covers data pipelines, feature stores, model monitoring, and deployment for production ML. |
| AI Engineering | 2024 | Chip Huyen | O'Reilly | A follow-up focused on building applications with foundation models, including prompt engineering, evaluation, and fine-tuning. |
| Build a Large Language Model (From Scratch) | 2024 | Sebastian Raschka | Manning | A hands-on walkthrough that builds a transformer language model in PyTorch, step by step. |
The table below groups popular AI books into four threads: alignment and existential risk, history and progress reporting, ethics and social criticism, and industry and policy. The first three groups overlap heavily in practice; the categorisation in the rightmost column is meant as a hint, not a strict label.
| Title | Year | Authors | Publisher | Theme |
|---|---|---|---|---|
| Superintelligence: Paths, Dangers, Strategies | 2014 | Nick Bostrom | Oxford University Press | Alignment, existential risk |
| The Singularity Is Near: When Humans Transcend Biology | 2005 | Ray Kurzweil | Viking | History and forecasting |
| The Singularity Is Nearer: When We Merge with AI | 2024 | Ray Kurzweil | Viking | Forecasting, follow-up to the 2005 book |
| Life 3.0: Being Human in the Age of Artificial Intelligence | 2017 | Max Tegmark | Knopf | Alignment, futures |
| Human Compatible: Artificial Intelligence and the Problem of Control | 2019 | Stuart Russell | Viking | Alignment, control problem |
| A Brief History of Intelligence | 2023 | Max Bennett | Mariner Books | History, cognitive science |
| Co-Intelligence: Living and Working with AI | 2024 | Ethan Mollick | Portfolio | Industry, applications |
| Genesis: Artificial Intelligence, Hope, and the Human Spirit | 2024 | Henry Kissinger, Eric Schmidt, Craig Mundie | Little, Brown | Policy. Kissinger died in November 2023 before the book went to press. |
| The Coming Wave | 2023 | Mustafa Suleyman with Michael Bhaskar | Crown | Policy, containment |
| Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity | 2023 | Daron Acemoglu, Simon Johnson | PublicAffairs | Policy, economics. Both authors shared the 2024 Nobel Memorial Prize in Economic Sciences. |
| I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique | 2023 | Tomas Chamorro-Premuzic | Harvard Business Review Press | Society, work |
| Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence | 2021 | Kate Crawford | Yale University Press | Ethics, infrastructure |
| Race After Technology: Abolitionist Tools for the New Jim Code | 2019 | Ruha Benjamin | Polity | Ethics, race |
| Algorithms of Oppression: How Search Engines Reinforce Racism | 2018 | Safiya Umoja Noble | NYU Press | Ethics, search |
| Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy | 2016 | Cathy O'Neil | Crown | Ethics, big data |
| The Alignment Problem: Machine Learning and Human Values | 2020 | Brian Christian | W. W. Norton | Alignment |
| Code Dependent: Living in the Shadow of AI | 2024 | Madhumita Murgia | Henry Holt | Society, journalism |
| Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI | 2025 | Karen Hao | Penguin Press | Industry, OpenAI history |
| The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI | 2023 | Fei-Fei Li | Flatiron Books | Memoir, ImageNet |
| Genius Makers: The Mavericks Who Brought AI to Google, Facebook, and the World | 2021 | Cade Metz | Dutton | Industry history |
| AI 2041: Ten Visions for Our Future | 2021 | Kai-Fu Lee, Chen Qiufan | Currency | Forecasting, fiction-essay hybrid |
| AI Superpowers: China, Silicon Valley, and the New World Order | 2018 | Kai-Fu Lee | Houghton Mifflin Harcourt | Industry, geopolitics |
| Rebooting AI: Building Artificial Intelligence We Can Trust | 2019 | Gary Marcus, Ernest Davis | Pantheon | AI critique, cognitive science |
| Taming Silicon Valley: How We Can Ensure That AI Works for Us | 2024 | Gary Marcus | MIT Press | Policy, regulation |
| Our Final Invention: Artificial Intelligence and the End of the Human Era | 2013 | James Barrat | Thomas Dunne Books | Existential risk |
| The Master Algorithm | 2015 | Pedro Domingos | Basic Books | Survey of ML schools |
| The Book of Why: The New Science of Cause and Effect | 2018 | Judea Pearl, Dana Mackenzie | Basic Books | Causal inference for general readers |
| The Deep Learning Revolution | 2018 | Terrence J. Sejnowski | MIT Press | History of neural networks |
| You Look Like a Thing and I Love You | 2019 | Janelle Shane | Voracious / Little, Brown | Popular science, AI failure modes |
| Hello World: Being Human in the Age of Algorithms | 2018 | Hannah Fry | W. W. Norton | Algorithms in everyday life |
| The Age of AI: And Our Human Future | 2021 | Henry Kissinger, Eric Schmidt, Daniel Huttenlocher | Little, Brown | Policy, predecessor to Genesis |
| The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity | 2019 | Amy Webb | PublicAffairs | Industry, geopolitics |
| A Thousand Brains: A New Theory of Intelligence | 2021 | Jeff Hawkins | Basic Books | Neuroscience-inspired AI |
| Architects of Intelligence: The Truth About AI from the People Building It | 2018 | Martin Ford | Packt | Interviews with 23 leading AI researchers |
| Rule of the Robots: How Artificial Intelligence Will Transform Everything | 2021 | Martin Ford | Basic Books | Survey of AI impact |
| Rise of the Robots: Technology and the Threat of a Jobless Future | 2015 | Martin Ford | Basic Books | Automation, work |
| The Second Machine Age | 2014 | Erik Brynjolfsson, Andrew McAfee | W. W. Norton | Automation, economics |
| The Creativity Code: Art and Innovation in the Age of AI | 2019 | Marcus du Sautoy | Belknap / Harvard University Press | AI and creativity |
| Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots | 2015 | John Markoff | Ecco | History of AI and robotics |
| Final Jeopardy: Man vs. Machine and the Quest to Know Everything | 2011 | Stephen Baker | Houghton Mifflin Harcourt | The Watson Jeopardy! match, IBM |
| The Quest for Artificial Intelligence: A History of Ideas and Achievements | 2010 | Nils J. Nilsson | Cambridge University Press | Comprehensive AI history through 2010 |
| Possible Minds: 25 Ways of Looking at AI | 2019 | John Brockman, editor | Penguin Press | Essay collection, contributors include Russell, Tegmark, Pinker |
| Artificial Unintelligence: How Computers Misunderstand the World | 2018 | Meredith Broussard | MIT Press | Critical perspective on AI hype |
| Privacy Is Power: Why and How You Should Take Back Control of Your Data | 2020 | Carissa Veliz | Bantam Press | Data ethics |
| The Age of Surveillance Capitalism | 2019 | Shoshana Zuboff | PublicAffairs | Data economy, behavioural prediction |
| Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor | 2018 | Virginia Eubanks | St. Martin's Press | Algorithmic harm in social services |
| Genie in the Machine: How Computer-Automated Inventing Is Revolutionizing Law and Business | 2009 | Robert Plotkin | Stanford Law Books (an imprint of Stanford University Press) | Patent law and automated invention |
The books below were written before the deep learning era, but each remains widely read and cited. They cover symbolic AI, cognitive science, the philosophy of mind, and the early debates about what a thinking machine could or should be.
| Title | Year | Authors | Publisher | Notes |
|---|---|---|---|---|
| Computer Power and Human Reason: From Judgment to Calculation | 1976 | Joseph Weizenbaum | W. H. Freeman | An early ethical critique by the creator of the ELIZA chatbot. |
| Goedel, Escher, Bach: An Eternal Golden Braid | 1979 | Douglas Hofstadter | Basic Books | A meditation on self-reference, formal systems, and cognition. Pulitzer Prize for general non-fiction, 1980. |
| The Mind's I: Fantasies and Reflections on Self and Soul | 1981 | Douglas Hofstadter, Daniel Dennett, editors | Basic Books | An anthology of essays and fiction on consciousness and AI. |
| Mindstorms: Children, Computers, and Powerful Ideas | 1980 | Seymour Papert | Basic Books | Argues for using computers as tools for thinking and learning. The Logo programming language grew out of this work. |
| The Society of Mind | 1986 | Marvin Minsky | Simon and Schuster | Proposes that intelligence emerges from many simple processes interacting. |
| Perceptrons: An Introduction to Computational Geometry | 1969 | Marvin Minsky, Seymour Papert | MIT Press | The book that proved certain limitations of single-layer perceptrons and is often credited (or blamed) for the first AI winter. |
| What Computers Can't Do: A Critique of Artificial Reason | 1972 | Hubert L. Dreyfus | Harper and Row | A philosophical critique of symbolic AI based on phenomenology. |
| The Emperor's New Mind: Concerning Computers, Minds, and the Laws of Physics | 1989 | Roger Penrose | Oxford University Press | Argues against strong AI on physical and mathematical grounds. |
| Shadows of the Mind: A Search for the Missing Science of Consciousness | 1994 | Roger Penrose | Oxford University Press | Sequel to The Emperor's New Mind, extending the argument from Goedel's theorems. |
| Consciousness Explained | 1991 | Daniel Dennett | Little, Brown | A functionalist account of consciousness that has been central to philosophy of mind debates. |
| The Age of Intelligent Machines | 1990 | Ray Kurzweil | MIT Press | Predecessor to The Age of Spiritual Machines, with predictions about chess, search, and the web. |
| The Age of Spiritual Machines: When Computers Exceed Human Intelligence | 1999 | Ray Kurzweil | Viking | Introduces the law of accelerating returns and forecasts machine intelligence in the early 21st century. |
| Vehicles: Experiments in Synthetic Psychology | 1984 | Valentino Braitenberg | MIT Press | Thought experiments on simple robots whose behaviour looks intelligent. |
| The Computer and the Brain | 1958 | John von Neumann | Yale University Press | A short posthumous comparison of digital and biological information processing. |
| Cybernetics: Or Control and Communication in the Animal and the Machine | 1948 | Norbert Wiener | MIT Press | The founding text of cybernetics, which underlies much of modern AI. |
| The Human Use of Human Beings | 1950 | Norbert Wiener | Houghton Mifflin | A general-reader account of the social implications of cybernetics. |
| Plans and the Structure of Behavior | 1960 | George A. Miller, Eugene Galanter, Karl Pribram | Henry Holt | An early cognitive science book that introduced the TOTE unit and shaped how AI thought about goals. |
AI fiction has shaped public expectations of the field for almost a century. The books below are the ones most often cited in discussions of AI in film, in coursework on technology and society, and in the published interviews of researchers themselves. Asimov's robot stories, Dick's androids, and Gibson's cyberspace are the recurring reference points.
| Title | Year | Author | Type | Notes |
|---|---|---|---|---|
| I, Robot | 1950 | Isaac Asimov | Story collection | Introduces the Three Laws of Robotics, which the field still references when discussing safety constraints. |
| The Caves of Steel | 1954 | Isaac Asimov | Novel | First Robot novel, pairing detective Elijah Baley with humanoid robot R. Daneel Olivaw. |
| The Naked Sun | 1957 | Isaac Asimov | Novel | Second Robot novel; explores a society where humans rely entirely on robot labour. |
| The Bicentennial Man and Other Stories | 1976 | Isaac Asimov | Story collection | Title novella follows a robot seeking legal recognition as human. |
| Do Androids Dream of Electric Sheep? | 1968 | Philip K. Dick | Novel | The novel adapted into Blade Runner (1982). Asks what distinguishes empathy in humans from imitation in androids. |
| Neuromancer | 1984 | William Gibson | Novel | The founding text of cyberpunk; introduced the word cyberspace and an artificial intelligence character, Wintermute. Won the Nebula, Hugo, and Philip K. Dick awards. |
| Count Zero | 1986 | William Gibson | Novel | Sequel to Neuromancer, expanding the role of AI entities in the Sprawl trilogy. |
| Mona Lisa Overdrive | 1988 | William Gibson | Novel | Third Sprawl novel, continuing the AI thread. |
| Snow Crash | 1992 | Neal Stephenson | Novel | Introduced the word metaverse and features a Sumerian-mythology-influenced linguistic virus. |
| The Diamond Age: Or, A Young Lady's Illustrated Primer | 1995 | Neal Stephenson | Novel | An AI-driven adaptive book teaches a child everything she needs to know. |
| Speak | 2015 | Louisa Hall | Novel | Five interleaved voices across centuries trace the development of a conversational AI. |
| Klara and the Sun | 2021 | Kazuo Ishiguro | Novel | A solar-powered artificial friend narrates her own observations of human family life. Ishiguro won the Nobel Prize in Literature in 2017. |
| Machines Like Me | 2019 | Ian McEwan | Novel | An alternate-history London where Alan Turing lived longer and synthetic humans are sold to consumers. |
| The Lifecycle of Software Objects | 2010 | Ted Chiang | Novella | Follows trainers of intelligent virtual pets over many years. Won the Hugo and Locus awards for best novella. |
| Exhalation | 2019 | Ted Chiang | Story collection | Contains The Lifecycle of Software Objects and other AI-relevant stories such as The Truth of Fact, the Truth of Feeling. |
| Stories of Your Life and Others | 2002 | Ted Chiang | Story collection | Contains the novella later adapted as Arrival; not strictly AI but central to many AI essayists' canons. |
| Burn-In: A Novel of the Real Robotic Revolution | 2020 | P. W. Singer, August Cole | Novel | A near-future thriller built around verified research on automation, robotics, and security. |
| The Moon Is a Harsh Mistress | 1966 | Robert A. Heinlein | Novel | Features Mike, a self-aware lunar supercomputer who helps lead a revolution. |
| 2001: A Space Odyssey | 1968 | Arthur C. Clarke | Novel | Published alongside the Kubrick film; HAL 9000 became the most quoted fictional AI in the field. |
| 2010: Odyssey Two | 1982 | Arthur C. Clarke | Novel | Sequel that explains HAL's behaviour from the first book. |
| The Adolescence of P-1 | 1977 | Thomas J. Ryan | Novel | An early novel about a self-improving program that escapes onto the wider network. |
| Galatea 2.2 | 1995 | Richard Powers | Novel | A novelist helps train a neural network to pass a master's exam in English literature. |
| Permutation City | 1994 | Greg Egan | Novel | Hard science fiction on uploaded minds and simulated worlds. |
| Diaspora | 1997 | Greg Egan | Novel | Posthuman software citizens explore the universe. |
| The Quantum Thief | 2010 | Hannu Rajaniemi | Novel | A post-singularity caper with sophisticated AI characters. |
| Hyperion | 1989 | Dan Simmons | Novel | The TechnoCore, a coalition of AI entities, is a major faction throughout the Hyperion Cantos. |
| He, She and It | 1991 | Marge Piercy | Novel | A cyborg defends a Jewish town in a near-future setting. Won the Arthur C. Clarke Award. |
| Vernor Vinge's True Names | 1981 | Vernor Vinge | Novella | Anticipated cyberspace and online identity decades before the web. |
| A Fire Upon the Deep | 1992 | Vernor Vinge | Novel | A superintelligent Power is a central antagonist; Vinge popularised the term technological singularity in a 1993 essay. |
| Daemon | 2006 | Daniel Suarez | Novel | An autonomous distributed program continues executing its creator's plans after his death. |
| Avogadro Corp | 2011 | William Hertling | Novel | A self-improving AI emerges from an email-rewriting tool. |
| Annihilation | 2014 | Jeff VanderMeer | Novel | First book of the Southern Reach trilogy. Less directly about AI, but commonly cited in discussions of non-human cognition. |
The books below are first-person accounts by people who built the field, ran the labs, or wrote the policies. They are listed separately because their value as primary sources differs from the analytical non-fiction in the popular section.
| Title | Year | Author | Publisher | Notes |
|---|---|---|---|---|
| The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI | 2023 | Fei-Fei Li | Flatiron Books | A memoir from the Stanford professor who led the ImageNet project. |
| AI Superpowers: China, Silicon Valley, and the New World Order | 2018 | Kai-Fu Lee | Houghton Mifflin Harcourt | Part autobiography, part industry analysis. Lee chaired Microsoft Research Asia and ran Google China. |
| AI 2041: Ten Visions for Our Future | 2021 | Kai-Fu Lee, Chen Qiufan | Currency | Ten short stories by Chen with technical analysis by Lee after each one. |
| The Coming Wave | 2023 | Mustafa Suleyman with Michael Bhaskar | Crown | Written before Suleyman left Inflection AI to join Microsoft to lead its consumer AI division in 2024. |
| The Master Algorithm | 2015 | Pedro Domingos | Basic Books | Less personal than the other entries here, but Domingos draws on his own research throughout. |
| Final Jeopardy | 2011 | Stephen Baker | Houghton Mifflin Harcourt | Reported access to the IBM Watson team; reads as a group biography of the project. |
| Genius Makers | 2021 | Cade Metz | Dutton | Group biography of Geoffrey Hinton, Yann LeCun, Yoshua Bengio, and Demis Hassabis built from years of interviews. |
| Empire of AI | 2025 | Karen Hao | Penguin Press | Built on Hao's prior reporting at MIT Technology Review and The Atlantic, including extensive interviews with current and former OpenAI staff. |