These are the 12 best books to get up to speed on the hot new world of generative AI, according to experts

Author: Reid Hoffman, LinkedIn cofounder, investor at venture firm Greylock Partners, and former board member of OpenAI. 

Publish Date: March 15, 2023

Why it's good: As a former board member of OpenAI — one of the startups leading the generative AI charge — Hoffman has seen up close how the large language models behind generative AI tools like ChatGPT work. His book, available as a free pdf, was written with GPT-4, the newer, more powerful version of ChatGPT. 

The book is the first to be written by GPT-4, Hoffman said in a LinkedIn post announcing his work earlier this month.

"With GPT-4, I traveled through light bulb jokes, epic poems, original sci fi plots, arguments about human nature, musings on how AI might strengthen democracy, society and industries," he wrote. "The goal, like in any good trip, was to learn as much about my traveling partner as the place I was exploring."

Learn more about Impromptu: Amplifying Our Humanity Through AI

Author: Pedro Domingos, professor emeritus of computer science and engineering at the University of Washington

Publish Date: September 22, 2015

Why it's good: Domingos, whose research focuses on machine learning and data mining, takes on an ambitious task with The Master Algorithm, which was recommended by Bill Gates at the Code Conference in 2016.

Domingos starts by giving readers a look into the five major schools of thought in machine learning. He also takes readers behind the scenes of the learning models that power tech giants like Google and Amazon. Ultimately, he elucidates what the invention of a "master algorithm" — a learning algorithm that is capable of discovering any knowledge from data — will mean for both business and society at large. 

Matt Turck, an investor who focuses on generative AI at the venture firm FirstMark Capital, believes The Master Algorithm is still relevant now, and a great introduction to the field. "It's a book that was sort of ahead of its time in terms of thinking through the issues," he said, adding that it's also "just one of those rare books that is approachable, compelling to read, and technically correct."

Learn more about The Master Algorithm

Authors: Henry Kissinger, Eric Schmidt, and Daniel Huttenlocher. Kissinger, former Secretary of State in the Nixon & Ford administrations; Schmidt, former CEO of Google; Huttenlocher, an acclaimed computer vision research who is currently a dean at MIT's Schwarzman College of Computing. 

Publish Date: November 2, 2021

Why it's good: The book's trio of authors brings their expertise in statecraft, business, and academia to explore how AI is set to reshape society. 

"AI's promise of epoch-making transformations—in society, economics, politics, and foreign policy—portends effects beyond the scope of any single author's or field's traditional focuses," the authors contend in an online preview of the book. 

In the time since The Age of A.I. was published, a revolution in generative AI has brought us much closer to the promise of artificial general intelligence — the representation of human cognitive abilities in software— making the book's discussion of how society will change as machines increasingly perform human tasks all the more relevant.  

Learn more about The Age of AI: And Our Human Future

Authors: Ajay Agrawal, Joshua Gans, and Avi Goldfarb, all professors at University of Toronto's Rotman School of Management. 

Publish Date: November 15, 2022

Why it's good: This trio of economists previously authored the bestseller, Prediction Machines, in which they honed in on the benefits of using AI to make better and more efficient predictions. In Power and Prediction, they go one step further to explore how AI — and its capacity for predictions — poses threats and opportunities across a range of industries.  

That exploration is important now amid questions about which jobs generative AI will replace and which ones it will facilitate. 

James Currier, general partner at venture firm NFX, who recommended Power and Prediction said, "it relates to how Generative AI will impact business and the economy, with strong mental frameworks about how it will roll out." 

Learn more about Power and Prediction: The Disruptive Economics of Artificial Intelligence

Authors: Gary Marcus and Ernest Davis, both professors at New York University. Marcus, is a professor emeritus of psychology and neural science, while Davis is a professor of computer science. 

Publish Date: September 10, 2019

Why it's good: Rebooting AI offers an explanation of the developments around AI and what it will really take to move AI systems from narrow intelligence to genuine general intelligence. The authors argue that much of the development around AI has occurred in closed systems with fixed rules. The real world, however, is open-ended and much more complex, they say.  

FirstMark's Turck, who also recommended Rebooting AI, said its interesting because it offers a more skeptical take on deep learning.

Turck said that the explosion in deep learning over the past several years laid the foreground for the current revolution in generative AI. Over these years, he said the overarching belief has been that if you build systems with "more and more and more data" then you'll get "better and better and better results." Turck said that Rebooting AI pushes back against that "brute force approach," offering a slightly different path to AGI.

Learn more about Rebooting AI: Building Artificial Intelligence We Can Trust

Author: Stuart Russell, professor of computer science at UC-Berkeley who studies AI, algorithms, and machine learning. 

Publish Date: October 8, 2019

Why it's good: Russell explores questions of how humans and artificial intelligence can co-exist in a world where machines are becoming increasingly intelligent by the day.

Russell argues that this is possible by rethinking our approach to AI systems. One of his suggestions is to design machines that will be uncertain about the human preferences, rendering them humble and committed to pursuing human objectives over their own. 

Human Compatible was selected by the Stanford University Human-Centered Artificial Intelligence community for its "AI Books Recs" list published in August 2022.

Elon Musk also tweeted that the book was "worth reading" when it was published. 

—Elon Musk (@elonmusk) October 8, 2019

Learn more about Human Compatible: Artificial Intelligence and the Problem of Control

Author: Melanie Mitchell, professor at the Santa Fe Institute who researches visual recognition and artificial intelligence systems. 

Publish Date: October 15, 2019

Why it's good: In this work, Mitchell grapples with some of the biggest questions surrounding the explosive field of artificial intelligence. Those questions, as she writes on her website, include: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us?

Mitchell's book was also selected for the Stanford HAI 2022 "AI Books Recs" list. 

"Computer scientist Mitchell shows readers what they can actually do versus what our imaginations think they can do, offering a useful overview of the technology, its achievements, and its problems," wrote Shana Lynch, the head of content for Stanford's HAI. 

Learn more about Artificial Intelligence: A Guide for Thinking Humans

Author: Peter Lee, Carey Goldberg, and Isaac Kohane. Lee, Corporate VP for Research and Incubations at Microsoft; Goldberg, medical and science journalist; Kohane, chair of department of medical informatics at Harvard Medical School. 

Publish Date: May 3, 2023

Why it's good: The AI Revolution in Medicine— which is not even out yet, but available for pre-order on Amazon— has already been branded by the site as a bestseller.   

Based on its Amazon description, the book follows its authors, described as "three insiders with months of early access to GPT-4," as they uncover the technology's potential to improve diagnoses, summarize patient visits, accelerate research. 

The AI Revolution in Medicine also includes a foreward by OpenAI's CEO Sam Altman, and contributions from Sebastien Bubeck, an AI expert at Microsoft. 

Learn more about The AI Revolution in Medicine: GPT-4 and Beyond

Author: Margaret A. Boden, a professor of cognitive science at the University of Sussex, who studies artificial intelligence, philosophy, and psychology. 

Publish Date: November 4, 2003

Why it's good: Boden's first version of The Creative Mind, published back in 1990, drew upon examples in jazz improvisation, story writing, physics, and more to uncover the nature of human creativity, according to its online description. The 2nd edition incorporates more recent developments in the field of artificial intelligence to further explore that topic. 

Boden's book is relevant in light of the questions around how generative AI will impact writers, artists, and those in creative fields. 

The work was heralded as "a classic" by Dr. Maya Ackerman, an assistant professor of computer science and engineering at Santa Clara University and the founder of the generative AI music company, WaveAI. 

Learn more about The Creative Mind: Myths and Mechanisms, 2nd Edition

Author: Brian Christian, an researcher and author who has written several books on the human implications of computer science, including the most The Most Human Human and Algorithms to Live By. 

Publish Date: October 6, 2020

Why it's good: In The Alignment Problem, Christian investigates the ethics and safety challenges that emerge when artificial intelligence systems don't behave the way we expect them to. In the process, Christian also introduces readers to the community of researchers working at the forefront of these issues. 

Peter Norvig, a computer scientist who served as the director of research at Google and is now a fellow at Stanford's Institute for Human-Centered Artificial Intelligence, recommended the book, though it was written a few years before the explosion in generative AI. 

"It won't discuss GPT-4, but it discusses these issues like how do we know what the computer is trying to do? And, we trained it on this data and what biases does that give it?" Norvig explained, "so that's certainly crucial to generative AI."

Learn more about The Alignment Problem

Author: William Hertling, a science fiction writer and programmer.

Publish Date: January 9, 2014

Why it's good: In Avogadro Corp., software designer David Ryan is developing a career-making email language-optimization program. Ryan — worried that his project may be canceled — embeds a directive into the software that ends up creating a form of runway artificial intelligence that begins to manipulate Ryan and his team.

Andy Wilson, the CEO of Logikcull, a legal tech company that uses AI, described Avogadro Corp as a "great read." 

"The AI that ends up becoming sentient started as a LLM AI, just like ChatGPT," Wilson said, referring to a large language model. 

Authors: Kai-Fu Lee, Taiwanese businessman and former president of Google China, and Chen Qiufan, a novelist who also wrote Waste Tide and Buddhagram. 

Publish Date: September 14, 2021

Why it's good: Back in 2021, tech exec Kai-Fu Lee and Chen Qiufan teamed up to predict how the world would be reshaped by AI in 2041. Their fictional book, AI 2041, hypothesizes scenarios like a "job reallocation" industry in San Francisco as deep learning AI wipes out existing career paths. Or the story of a music fan in Tokyo who gets swept up in an immersive form of celebrity worship rooted in virtual reality.

Though it's only 2023, many of the authors' predictions already seem plausible, as more and more people worry about generative AI replacing their jobs. 

Stanford's Norvig, who also recommended AI 2041, said each chapter also has an afterward that explains the actual technology behind the story.