100 books like Artificial Intelligence

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.

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. 

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. 

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.

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. 

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.

With recent advances in large language models such as GPT-4, it is predicted that AI capabilities in terms of general decision making and problem solving may exceed that of humans even in less than a decade. Is this good or bad news?

This book is a must-read for anyone who wants to understand and navigate this difficult topic. Of particular interest are Bostrom’s two groundbreaking observations: the orthogonality thesis (any level of intelligence can be combined with any final goal) and the instrumental convergence thesis (any sufficiently non-trivial final goal will also create instrumental goals of self-preservation, efficiency, creativity, and unbounded resource acquisition).

A top pick for anyone who wants to figure out the prospects for the human civilization in the face of superhuman artificial general intelligence.

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!

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.

Maggie is a force of nature and anyone involved in the philosophy of AI knows (or should know) her extensive work. This book is an easy-to-read and beautifully-written introduction to Artificial Intelligence, which tells some of the recent history while explaining how and why intelligence is much harder to make than many of the pundits seem to think. No nonsense here – a good solid read by a hugely experienced scientist at the top of her field.