Generative Artificial Intelligence: What Everyone Needs to Know ®

by Jerry Kaplan

"AI expert Jerry Kaplan explains how generative AI will revolutionize virtually every human activity. Highly recommended." - Francis Fukuyama, Political scientist and author of The End of History and the Last Man

Advances in Generative Artificial Intelligence (GAI) have created a new class of computer systems that exhibit astonishing proficiency on a wide variety of tasks with superhuman performance, producing novel text, images, music, and software by analyzing enormous collections of digitized information. Soon, these systems will provide expert medical care; offer legal advice; draft documents; write computer programs; tutor our children; and generate music and art. These advances will accelerate progress in science, art, and human knowledge, but they will also bring new dangers.

Have we finally discovered the holy grail of AI - machines that match or exceed human intelligence? Which industries and professions will thrive, and which will wither? What risks and dangers will it pose? How can we ensure that these systems respect our ethical principles? Will the benefits be broadly distributed or accrue to a lucky few? How will GAI alter our political systems and international conflicts? Are we merely a stepping stone to a new form of non-biological life, or are we just getting better at building useful gadgets?

Generative Artificial What Everyone Needs to Know? equips readers with the knowledge to answer these pressing questions.

Genres: Artificial Intelligence, Audiobook, Technology, Nonfiction

236 pages, Kindle Edition

First published January 1, 2024

About the author

Kaplan is widely known as a serial entrepreneur, technical innovator, bestselling author, and futurist. He co-founded four Silicon Valley startups, two of which became publicly traded companies. His best-selling non-fiction novel "Startup: A Silicon Valley Adventure" was selected by Business Week as one of the top ten business books of the year, was optioned to Sony Pictures, and is available in Japanese, Chinese, and Portuguese. Kaplan has been profiled in The New York Times, The Wall Street Journal, Forbes, Business Week, Red Herring, and Upside, and is a frequent public speaker.

Kaplan is currently a Fellow at The Stanford Center for Legal Informatics. He also teaches Philosophy, Ethics, and Impact of Artificial Intelligence in the Computer Science Department, Stanford University. He holds a BA (1972) from the University of Chicago in History and Philosophy of Science, and an MSE (1975) and PhD (1979) in Computer and Information Science, specializing in Artificial Intelligence and Computational Linguistics, from the University of Pennsylvania.

Reviews

[Olivia Schwern · Rating 4 out of 5]

Solid fundamental explanation of GenAI and its applications, regulatory considerations, etc. Written in Q&A format so allowed you to skip sections and jump ahead without getting lost.

[Kenneth C · Rating 4 out of 5]

Kaplan’s captivating title for his third book on the topic of artificial intelligence (AI) is useful for anyone hoping to understand the basics of a technology that continues to mature and provide improvements in many areas of life as well as ethical challenges to how we manage these machines.
Kaplan has practical experience in the development, marketing and fielding of AI systems which spans 40 years, making him a knowledgeable spokesperson for the industry. Kaplan speaks optimistically of the future of AI, while recognizing risks and barriers to that future. He writes “It is not yet clear whether this technological revolution will be a net positive for society, though I expect it will be.” He then proceeds to defend this position across key aspects of Generative Artificial Intelligence (GAI) history, application, regulation and philosophy.
Kaplan dismisses the rhetoric regarding the capability of GAI to surpass human capabilities and assume a deistic like quality. “We are not conversing with some new kind of deity in waiting” Kaplan writes, “GAI’s are better understood as a way to mine actionable insights from accumulated wisdom and experience of humankind.”
Kaplan’s book, published in 2024, is well organized. It contains a helpful summary of the history of the development of GAI, including a simple explanation of basic theory, written at a level that a reader who is not conversant in computer science can understand.
Kaplan then describes his view of the likely impacts on society as the result of utilizing GAI across many fields of discipline. His review of historic precedents is helpful. Looking back through history we can see that the wheel, printing press, the light bulb and penicillin as developments which changed the course of human history. Kaplan believes GAI will supersede all these creations in the way it impacts the lives of virtually everyone. He specifically discusses the potential impacts across a broad spectrum of areas, including education, healthcare, creative arts, law and engineering.
Kaplan offers insight into how GAI will change the nature of work. While some fear the impact of automation, Kaplan skillfully explains that improvements in processes over the past 200 years have resulted in more wealth and leisure time for most, at least in Western society. He points out that 200 years ago 98 percent of the US population of 6 million was directly involved in agriculture or farming. This large workforce was necessary to provide the food to keep Americans alive. Today, only 2 percent of the population is engaged in agriculture or farming, yet the food supply is generally plentiful enough to feed 335 million people.
When addressing the fear that GAI will replace so many workers that meaningful employment will not be available, Kaplan points out that 57 percent of all jobs 65 years ago no longer exist today. Kaplan then forecasts those areas which will see job opportunities decline and others that will see growth.
Kaplan’s writing on risks and benefits of GAI is particularly valuable, though he does intermingle philosophical positions that could be more coherently discussed in his later chapter on the philosophical implications of GAI. His discussion of the drawbacks of Automated Decision Systems is a good example of the challenges of using algorithms to make decisions. The unintended impacts of unintentional biases was explained. Kaplan writes that Amazon, a company with a renowned history of embracing leading edge technology, discovered their automatic resume readers for job applicants contained clear gender bias and didn’t account for the differences in how women and men used descriptors in resumes.
Kaplan’s concerns about the ethical use of robots employing GAI having the ability to use lethal force on a person without a human decision maker in the loop, whether it is in a military or law enforcement application, was clearly and appropriately articulated.
In the area of regulation of GAI, Kaplan provided a thought-provoking discussion of the differences in regulation of GAI between the European Union (EU), the United States and China. Kaplan writes the EU is ahead of the U.S. and China in developing basic AI regulations, though he does acknowledge the advantages of Chinese communism in managing and advancing GAI, albeit with the associated loss of freedom and creativity that can drive AI advances. He also acknowledges China’s demographic advantage due to a significantly larger population and an emphasis on science and technology education.
Kaplan finishes his chapter on regulation and policy with a set of definitions and responsibilities for GAI systems and for “Responsible Persons” (those who create, oversee or sell GAI systems) that are useful in understanding what potential boundary areas are for management of GAI.
Kaplan’s writing style effectively communicates his ideas; he appears to present a balanced assessment of the benefits and risks of GAI. His writing bogs down on two topics, the legal status of GAI’s and the philosophical implications of GAI. In the former he gets bogged down on the topics of internet election voting and GAI’s legal rights and criminal/civil liability.
In the latter Kaplan proves his depth of knowledge on philosophical issues is doesn’t match his computer systems and entrepreneurial knowledge. He correctly identifies semantic challenges, specifically how the words “think” and “feel” are not clearly defined when it comes to GAI. His discussion of free will is rambling and he doesn’t clearly define free will as it relates to GAI; he misses an opportunity to take a philosophical stand when he concludes “Either both people and computers can have free will or neither can—at least until we discover some evidence to the contrary. Take your pick.” Kaplan’s vague position is unsatisfying to the reader who has concerns about the ethical and philosophical impacts of GAI in the wild frontier of GAI development.
Even with these shortcomings Kaplan’s book is informative, relevant and readable as an introduction to the historical, practical and ethical issues society faces as it rushes to embrace technology when it does not comprehend the risk to individual autonomy and personhood.

[Yoda · Rating 3 out of 5]

A Short Primer Intended for the Layman that does an Adequate Job

Any review of this book would have to start out by stating that, as part of the "what everyone needs to know" series, it is relatively short. It is not intended as an in-depth overview of the topic. In addition, it is intended for the extreme-most novice. Anyone with any level of knowledge over and above that would not find almost anything new in this book.

Hence the relevant question becomes how well does the book perform as a primer for its intended audience of the novice? The answer is acceptably well. It provides a few pages on what AI is, how it developed, the author's view on Al's future impacts on the labor market (for a more in-depth book on this subject this reviewer recommends the author's previous book "Human's Need Not Apply") and a few other topics such as the potential of AI transcending human intelligence and human-machine integration a la Ray Kurzweil’s Singularity.

All and all not a bad book for its intended audience but also, simultaneously, not much more insightful than other books on AI that geared to the same intended audience. Three and a half stars.

[JM Reading · Rating 5 out of 5]

After reading and hearing so much about ChatGPT
and other generative AI apps and programs, I needed a crash course in this subject.

Author Jerry Kaplan teaches AI at Stanford University, but, bless him, his book Generative Artificial Intelligence: What Everyone Needs to Know is perfectly titled and wonderfully readable. Without dumbing anything down or dismissing any of the philosophical nuance, this primer made a somewhat daunting subject relatively easy to understand — and I was genuinely entertained. Kaplan is funny!

I haven't just recommended Kaplan's book to my colleagues and friends, I suggested it to my Book Group and my Investment group. We ALL need to be prepared for the revolution and I believe this book is required reading.

Buy it. Read it. Discuss it.

[Donn Lee · Rating 4 out of 5]

This was actually quite a good book. Stylistically and tonally I love how this book was written.

I was on the fence on whether or not it deserved five stars, but left it at 4 because it's somewhat dated. Given how quickly AI is changing, a book published yesterday could be outdated by the time you read it; this book (published in early 2024) is essentially a lifetime ago by AI standards.

Otherwise, this book is a great primer on AI in general. But for those interested in its philosophical and moral arguments, it tends to be a bit thin. For knowing the earlier days of Gen AI and the difficulties and uncertainties of this technology then, it's great. It was really interesting just knowing how far we've come, and how many of his predictions have come to fruition.

[Susana · Rating 2 out of 5]

Abandonado en el cuarto capítulo.

No soporté ni el tono "amigable"y "simple", que, tal como lo advierte el autor, puede sonar condescendiente (patronizing en el original), ni su optimismo extremo, que, desde mi punto de vista, le resta credibilidad a sus planteamientos.

La inteligencia artificial no viene a resolver todos los problemas de la humanidad, ni será su fin; entiendo que es una herramienta más, que, como toda herramienta, debe utilizarse con criterio y conociendo sus limitaciones, así como las necesidades de regulación externa y propia.

Es muy temprano para pronosticar el impacto que tendrá en las empresas y las personas: proyectar solamente escenarios maravillosos, de color rosa, no ayuda a entender sus usos, limitaciones y riesgos.

[Dav · Rating 1 out of 5]

Stopped audiobook in chapter 1 when author describes what is essentially memory recall and pattern application then says “if that’s not general intelligence I don’t know what is.” Author obviously doesn’t know what general intelligence is. I’ll wait for a book that doesn’t start with wild claims. You ‘d likely be better served finding a podcast with Francois Chollet describing the ARC challenge (something children can do but LLMs author contends are General Intelligence fail miserably at) than reading this.

[Tamara · Rating 2 out of 5]

I really enjoyed the first two chapters, where the author provides a brief overview of the history of artificial intelligence and explains how GAIs work. The chapters are structured in a question-and-answer format, and Kaplan’s writing is succinct and clear.

However, the later chapters, where he explores the ethical and societal considerations behind GAI, are where he gradually lost me. It’s not that he doesn’t know what he’s talking about—it's that he is wilfully ignorant, downplaying the significant concerns such as job displacement and the ethics of interacting with anthropomorphic machines.

This book is clearly written by a wealthy AI enthusiast nearing the end of his life, so at least it provided a first-hand insight into how this type of person thinks LOL.

2 stars for the great first two chapters and 0 stars for the following chapters. Overall, 2/5.

[Matt G · Rating 4 out of 5]

For getting a sense of the semantic theory and broad functional approach to AI, how it works conceptually, this is a good book. that said, it lacks in philosophical depth and its arguments are a bit weaker when it comes to the issues explored in the final chapter of the book. It's a great book to pair with another introduction to AI or for anyone seeking more practical understanding of AI who lacks a mathematics or computer science background.

[Nick · Rating 1 out of 5]

Don't worry lawyers, surgeons, teachers, and software developers! When AI takes your job, there will be plenty of new (low paid) jobs in hospitality for you!

In the introduction, the author's proposed solution to potential misuse of AI in a way that's detrimental to society is "don't do that." That should give you an idea of the level we're working at here.

The book broadly suffers from the cognitive dissonance of asserting both of the following:

• GAI will allow everybody to harness its power such that many professionals will see their roles change to "prompt engineer"; and
• This will increase demand for the services of such prompt engineers.

By way of example, the author provides the following example: his mother had perhaps 50 photographs developed per year, but his daughter has many thousands of photos on her smartphone. What? This example makes no sense; more than that, it is an argument against his assertion. How many people worked in photo labs then compared to today. Sure, "demand" for photographs has increased massively, but demand for professional photograph developers...?

I also disliked the smug hand-waving away of people trying to resist AI replacing their jobs. The Hollywood Writers Strike was described as "quixotic luddites" – how dare these people stand in the way of progress! Just get another job, jeez.

[Daval Davis · Rating 2 out of 5]

The technological discussions are very introductory, but I guess the book is intended for "Everyone." There is a LOT of optimistic handwaving around the economic and career effects of AI. I do not share Mr. Kaplan's apparent belief that millions upon millions of doctors, drivers, software engineers, authors, teachers etc. will happily retrain into satisfy careers as "prompt engineers".

[Peter Musso · Rating 4 out of 5]

Although fairly elemental, it’s a quick and accessible read with some valuable insights. I found the argument that human work will shift and evolve in response to AI development (rather than be completely decimated) to be well-founded, though some may still see this as naively optimistic.

[Matt L · Rating 4 out of 5]

Good launch pad for further reading. Addresses many relevant topics with limited depth.

[Susan Y · Rating 5 out of 5]

Writing a book like this was no doubt a Herculean task but Kaplan managed to make the topic accessible, informative and even humorous in parts.

[Camden Polley · Rating 2 out of 5]

Decent enough introduction to GAI but otherwise a little dull and uninsightful.

[Vincent · Rating 3 out of 5]

Chapter 3 is good on which industries GAI will disrupt, especially legal. But the rest of the book is too general.

[JM Reading · Rating 5 out of 5]

After reading and hearing so much about ChatGPT
and other generative AI apps and programs, I needed a crash course in this subject.

Author Jerry Kaplan teaches AI at Stanford University, but, bless him, his book Generative Artificial Intelligence: What Everyone Needs to Know is perfectly titled and wonderfully readable. Without dumbing anything down or dismissing any of the philosophical nuance, this primer made a somewhat daunting subject relatively easy to understand — and I was genuinely entertained. Kaplan is funny!

I haven't just recommended Kaplan's book to my colleagues and friends, I suggested it to my Book group and my Investment group. We ALL need to be prepared for the revolution and I believe this book is required reading.

Buy it. Read it. Discuss it.

[Gogi · Rating 5 out of 5]

I loved this book, super informative on generative AI and also goes into the important details on what is likely to happen in the next 10-20 years and why it is historically and philopsichally important.