Here are 100 books that Artificial Intelligence fans have personally recommended if you like
Artificial Intelligence.
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I used to think that most nonhuman animals do not have minds in any rich sense of that word. After publishing a book about some influential philosophers who articulate and defend that view, I was pushed by a very good friend to get curious about what nonhuman creatures do. That led to years of reading, reflecting, teaching college courses, and eventually admitting that I had been profoundly wrong. My change of mind culminated in the publication of a book that explores the idea that plants have minds. The books on this list helped me tremendously along the way, and my students have also learned much from them.
This book made me think even fruitflies might have minds. Before reading this, I didn’t have a good grip on how we could even start to connect whole-body behaviors with specific genes. I was drawn in by the elegance of the early experiments with fruit flies. I remained mesmerized by the fact that when these investigations began in the early twentieth century, scientists were not sure what a gene was or even whether they were really real.
To understand how genes relate to traits of whole fruit flies, such as eye color and wing shape, scientists had to figure out what genes were simultaneously. This is the kind of book I want to memorize in a way that makes the book somehow part of me, stitched into the fibers of my body, shaping how I think and perceive.
The story of Nobel Prize–winning discoveries regarding the molecular mechanisms controlling the body’s circadian rhythm.
How much of our fate is decided before we are born? Which of our characteristics is inscribed in our DNA? Weiner brings us into Benzer's Fly Rooms at the California Institute of Technology, where Benzer, and his asssociates are in the process of finding answers, often astonishing ones, to these questions. Part biography, part thrilling scientific detective story, Time, Love, Memory forcefully demonstrates how Benzer's studies are changing our world view--and even our lives.
Jonathan Weiner, winner of the Pulitzer Prize for The Beak of…
I used to think that most nonhuman animals do not have minds in any rich sense of that word. After publishing a book about some influential philosophers who articulate and defend that view, I was pushed by a very good friend to get curious about what nonhuman creatures do. That led to years of reading, reflecting, teaching college courses, and eventually admitting that I had been profoundly wrong. My change of mind culminated in the publication of a book that explores the idea that plants have minds. The books on this list helped me tremendously along the way, and my students have also learned much from them.
I admire this book’s ingenuity. Bennett wants to understand how human minds differ from other animal minds. To figure this out, he starts from the assumption that language marks the difference. He takes for granted that honeybees communicate with each other, but they don’t use a language.
From there, Bennett asks: what would have to be added to the dances to make them a language of the sort that humans have and use? Adding one ability at a time—such as the ability to “deny” a dance—Bennett asks whether the honeybees yet have language. This strategy is so powerful to me because it allows me to respect how sophisticated honeybees actually are while discovering specific and significant ways in which their dances are limited.
This stimulating work takes the concept of 'rationality', a concept that more than any other is supposed to express the essence of what it means to be human, and submits it to a careful and penetrating analysis. The conclusions drawn often challenge those previously suggested by both philosophers and psychologists.
I used to think that most nonhuman animals do not have minds in any rich sense of that word. After publishing a book about some influential philosophers who articulate and defend that view, I was pushed by a very good friend to get curious about what nonhuman creatures do. That led to years of reading, reflecting, teaching college courses, and eventually admitting that I had been profoundly wrong. My change of mind culminated in the publication of a book that explores the idea that plants have minds. The books on this list helped me tremendously along the way, and my students have also learned much from them.
Psychology wasn’t always an empirical science; it became one; this book showed me how. What is an instinct? What is a reflex? What is an idea? How do we know what an animal is thinking? What is learning? What would be good evidence one way or another? Starting in the nineteenth century, Boakes tells the stories of several people who offered compelling answers to those questions, which continue to shape current discussions.
Although the book might appear to be a textbook, I experienced it more like a Netflix series with cliffhangers. Boakes portrays most of the people in the book—such as C. L. Morgan, Ivan Pavlov, and J.B. Watson—as explorers intrigued and perplexed by these questions, following up observations and experiments made by predecessors, raising further questions and challenges that made me want to turn to the next chapter.
This volume surveys the way that understanding of the minds of animals and ideas about the relationship between animal and human behaviour developed from around 1870 to 1930. In describing the research and theories which contributed to these developments, this book looks at the people who undertook such studies and the reasons why they did so. Its main purpose is to examine the different ways in which the outcome of this work affected their ideas about the human mind and exerted such a formative influence on psychology in general. This book will be used by first and second year undergraduates…
I used to think that most nonhuman animals do not have minds in any rich sense of that word. After publishing a book about some influential philosophers who articulate and defend that view, I was pushed by a very good friend to get curious about what nonhuman creatures do. That led to years of reading, reflecting, teaching college courses, and eventually admitting that I had been profoundly wrong. My change of mind culminated in the publication of a book that explores the idea that plants have minds. The books on this list helped me tremendously along the way, and my students have also learned much from them.
Bees, birds, frogs, and primates communicate with other members of their species, but this book helped me appreciate that they don’t use or have a language. I am fond of this book because Anderson works through the details of several different cases, taking pains to show how communication among bees, birds, frogs, and primates is impressive but still does not qualify as genuine language.
In doing so, Anderson offers an elegant and unique introduction to the science of linguistics. He makes it easy to see how this science is not only about the features of noises or gestures that creatures produce but also about their minds.
Dr. Dolittle-and many students of animal communication-are wrong: animals cannot use language. This fascinating book explains why.
Can animals be taught a human language and use it to communicate? Or is human language unique to human beings, just as many complex behaviors of other species are uniquely theirs? This engrossing book explores communication and cognition in animals and humans from a linguistic point of view and asserts that animals are not capable of acquiring or using human language. Stephen R. Anderson explains what is meant by communication, the difference between communication and language, and the essential characteristics of language. Next…
My passion for generative AI first ignited in 2016 when I spoke about it at a conference, and ever since then, I can’t stop! I've created an online course, a newsletter and even wrote a book to spread knowledge on this groundbreaking technology. As an instructor, I empower others to explore the boundless potential of generative AI applications. Day in day out, I assist clients in crafting their own generative AI solutions, tailoring them to their unique needs.
Bishop’s book laid the mathematical groundwork for me, making it a solid foundation for anyone venturing into Generative AI.
I love how it covers Bayesian inference, graphical models, and machine learning fundamentals in a clear, approachable way. I also think, in my personal opinion, that reading my book after this one would be a natural progression to understand where AI is heading, building on the core concepts that Bishop established.
Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic models. Also, the practical applicability of Bayesian methods has been greatly enhanced through the development of a range of approximate inference algorithms such as variational Bayes and expectation pro- gation. Similarly, new models…
I’ve always been fascinated by the power of language to propel everything we think—from our values and beliefs, to political views, to what we take for absolute truth. Once I learned there’s a whole field devoted to studying language called “rhetoric”—the field in which I’m now an expert—there was no turning back. Rhetoric has been around for more than 2,000 years, and since its inception, it has taught people to step back from language and appraise it with a more critical eye to identify how it works, why it’s persuasive, and what makes people prone to believe it. By studying rhetoric, we become less easily swayed and more comfortable with disagreement.
I love Ted Chiang’s short stories. Chiang’s background is in computer science, and he’s drawn to questions concerning the relationship between language, technology, cognition, and the physical universe.
His stories are fascinating thought experiments: They depict how a change in the medium or format of language transforms meaning and opens new possibilities for what language can be and do, what humans can think and know, and what it means to be a thinking, speaking human against the backdrop of a vast, infinitely complex universe. His stories are often backed by years of detailed research.
When I read Chiang, I find myself entangled in a strong emotional bond with his characters even as I ruminate on larger questions about what it means to be a language-using human.
'Lean, relentless, and incandescent.' Colson Whitehead, Pulitzer Prize winning author of The Underground Railroad and The Nickel Boys
This much-anticipated second collection of stories is signature Ted Chiang, full of revelatory ideas and deeply sympathetic characters. In 'The Merchant and the Alchemist's Gate,' a portal through time forces a fabric seller in ancient Baghdad to grapple with past mistakes and the temptation of second chances. In the epistolary 'Exhalation,' an alien scientist makes a shocking discovery with ramifications not just for his own people, but for all of reality. And in 'The Lifecycle of Software Objects,' a woman cares for…
I’ve been a geeky kid all my life. (I don’t think I’ve quite grown up yet.) Born in the 1970s, my childhood was a wonderful playground of building robots and software. I was awarded one of the early degrees in AI, and a PhD in genetic algorithms. I’ve since spent 25 years exploring how to make computers think, build, invent, compose… and I’ve also spent 20 years writing popular science books. I’m lucky enough to be a Professor in one of the world’s best universities for Computer Science and Machine Learning: UCL, and I guess I’ve written two or three hundred scientific papers over the years. I still think I know nothing at all about real or artificial intelligence, but then does anyone?
I’ve not met Harry, but he seems to have a logical and sensible head on his shoulders. His writing is considered and grounded, which is exactly what you need when discussing the hype that forever seems to surround AI. This book is another look at this topic and finds yet more ways to explain to readers the difference between human intelligence and our algorithmic attempts at intelligence – which are frequently pretty stupid.
Recent startling successes in machine intelligence using a technique called 'deep learning' seem to blur the line between human and machine as never before. Are computers on the cusp of becoming so intelligent that they will render humans obsolete? Harry Collins argues we are getting ahead of ourselves, caught up in images of a fantastical future dreamt up in fictional portrayals. The greater present danger is that we lose sight of the very real limitations of artificial intelligence and readily enslave ourselves to stupid computers: the 'Surrender'.
By dissecting the intricacies of language use and meaning, Collins shows how far…
My passion for generative AI first ignited in 2016 when I spoke about it at a conference, and ever since then, I can’t stop! I've created an online course, a newsletter and even wrote a book to spread knowledge on this groundbreaking technology. As an instructor, I empower others to explore the boundless potential of generative AI applications. Day in day out, I assist clients in crafting their own generative AI solutions, tailoring them to their unique needs.
I absolutely love Nick Bostrom's book because it dives deep into the fascinating yet daunting future of artificial intelligence, a topic that resonates with my own work. Bostrom's exploration of how superintelligent AI could emerge and the profound risks it poses is both thought-provoking and essential reading for anyone curious about technology's trajectory.
His insights on the challenges of control and alignment really struck a chord with me, as they highlight the importance of designing AI systems that prioritize human values. This book not only raises critical questions but also inspires a sense of urgency to navigate the future responsibly, making it a personal favorite and a vital resource for anyone interested in the intersection of AI and ethics.
The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. Other animals have stronger muscles or sharper claws, but we have cleverer brains.
If machine brains one day come to surpass human brains in general intelligence, then this new superintelligence could become very powerful. As the fate of the gorillas now depends more on us humans than on the gorillas themselves, so the fate of our species then would come to depend on the actions of the machine superintelligence.
I have been dreaming about Artificial Intelligence (AI) since a young age. I am currently Professor of AI at UNSW, Sydney. I was named by the Australian newspaper as one of the ”rock stars” of Australia’s digital revolution. Although this is highly improbable, I have spoken at the UN, and to heads of state, parliamentary bodies, company boards, and many others about AI and how it is impacting our lives. I've written three books about AI for a general audience that have been translated into a dozen different languages.
This is an entertaining and lighter read than my other recommendations about AI. It is specifically about chatbots trying to pass the Turing Test, and ultimately is a witty story of what it means to be human. For anyone who has ever mistaken an answerphone for a person, or a person for an answerphone!
A playful, profound book that is not only a testament to one man's efforts to be deemed more human than a computer, but also a rollicking exploration of what it means to be human in the first place.
“Terrific. ... Art and science meet an engaged mind and the friction produces real fire.” —The New Yorker
Each year, the AI community convenes to administer the famous (and famously controversial) Turing test, pitting sophisticated software programs against humans to determine if a computer can “think.” The machine that most often fools the judges wins the Most Human Computer Award. But there…
As a child of the microcomputer revolution in the late 1970s, I’ve always been fascinated by the concept of a general-purpose machine that I could control. The deep learning revolution of 2010 or so, followed most recently by the advent of large language models like ChatGPT, has completely altered the landscape. It is now difficult to interpret the behavior of these systems in a way that doesn’t argue for intelligence of some kind. I’m passionate about AI because, decades after the initial heady claims made in the 1950s, AI has reached a point where the lofty promise is genuinely beginning to be kept. And we’re just getting started.
Alan Turing’s 1936 paper “On Computable Numbers, with an Application to the Entscheidungsproblem” was foundational to the development of computer science. To this day, Turing machines, the theoretical computational devices imagined in Turing’s paper, are a research cornerstone as they embody the concept of “computable.” If a programming language can implement a Turing machine, then the language is deemed Turing complete and is, therefore, general-purpose enough to implement any algorithm.
Turing’s paper is readable, but Petzold’s book breaks it down in minute detail to explain the nomenclature and meaning behind Turing’s words. I believe all computer science students should study this paper, and you’ll be hard-pressed to find a more thorough review than the one presented in this book.
Programming Legend Charles Petzold unlocks the secrets of the extraordinary and prescient 1936 paper by Alan M. Turing
Mathematician Alan Turing invented an imaginary computer known as the Turing Machine; in an age before computers, he explored the concept of what it meant to be computable, creating the field of computability theory in the process, a foundation of present-day computer programming.
The book expands Turing's original 36-page paper with additional background chapters and extensive annotations; the author elaborates on and clarifies many of Turing's statements, making the original difficult-to-read document accessible to present day programmers, computer science majors, math geeks,…
