feature listfrom | Forbes7 classic books to read on artificial intelligence.

no. 5 | the Singularity is Near — by Ray Kurzweil
June 1, 2023

publication: Forbes
list title: 7 classic books to deepen your understanding of artificial intelligence.
author: by Rob Toews
date: December 2019

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An introduction.

The computer software field of artificial (AI) has never been the subject of more attention + analysis than it is today. Almost every week, it seems a new best-selling book comes out examining the tech, business, or ethics of AI.

Yet few of the topics + debates at the center of today’s AI discourse are new. While not always recognized by commentators, artificial intelligence as a serious academic discipline dates back to the 1950s. For well over half a century, many of the world’s leading minds have devoted themselves to the pursuit of machine intelligence — and have grappled with what it would mean to succeed in that pursuit.

Much of the public discourse around AI in year 2019 has been anticipated (and influenced by) AI thought leaders — going back decades. Below is a selection of 7 classic books about intelligence:

  • what it is
  • how we might build machines that have it
  • what that would mean for society

These books have played a formative role in the development of the field of AI. Their influence continues to be felt today. For anyone seeking a deep understanding of AI’s complexities, challenges, and possibilities — they are essential reading.

— Rob Toews


1 . |

book title: Godel, Escher, Bach: an eternal golden braid
deck: A metaphorical fugue on minds + machines in the spirit of Lewis Carroll.
author: by Douglas Hofstadter PhD
year: 1979

summary |

The book Godel, Escher, Bach is sometimes referred to as the Bible of artificial intelligence (AI) — but author Douglas Hofstadter PhD rejects the label.

The book’s central theme is — through self-reference and ‘strange loops’ — systems comprised of independently meaningless elements can acquire meaning + intelligence. Hofstader identifies versions of recursive systems in fields such as: math, music, art, and computer science.

To sketch out his thesis, he takes you into the depths of number theory, classical music, and the computing tech stack. He employs fanciful dialogues between fictional characters in the style of author Lewis Carroll.

He structures the book’s chapters, paragraphs, and sentences to embody his points about recursion. Although Hofstadter was an unknown author at the time of its publication — Godel, Escher, Bach won both the Pulitzer Prize + the National Book Award.

the Atlantic | The man who would teach machines to think

2. |

book title: the Society of Mind
author: by Marvin Minksy PhD
year: 1986

summary |

Marvin Minsky PhD is one of the founding fathers of artificial intelligence (AI). In the Society of Mind — his most famous + readable book — he shares his perspectives on how the human mind functions. And how we might build machines that simulate it.

Minsky’s over-arching thesis is that the human mind is not one coherent entity. But instead it’s a society of countless smaller ‘agents’ — each devoted to a narrow set of tasks, behaving in synchrony to produce intelligent behavior. The book is made of 270 one-page essays. Each essay is a piece of the puzzle — as you progresses through the book, his theory of mind emerges.

He writes at the end: ‘What magic trick makes us intelligent? The trick is there’s no trick. The power of intelligence stems from our vast diversity — not any single, perfect principle.’

3. |

book title: on Intelligence
deck: How a new understanding of the brain will lead to the creation of truly intelligent machines.
author: by Jeff Hawkins
year: 2004

summary |

In his book on Intelligence, author Jeff Hawkins posits that a single fundamental ‘algorithm’ underlies all information processing in the human brain. A feed-forward mechanism that predicts future states.

Hawkins’ theory of intelligence has been highly influential across neuro-science, machine learning, and philosophy in the past 15 years. Also regularly criticized. In year 2005 he co-founded the AI start-up Numenta — with Dileep George PhD.

4 . |

book title: Alan Turing: the Enigma
deck: The persecuted genius of war-time code-breaking and the computer revolution
author: by Andrew Hodges PhD
year: 1983

summary |

It’s only a slight over-statement to say scientist Alan Turing PhD created the computer — and the field of artificial intelligence (AI). His seminal 1936 paper — ahead of its time — laid the conceptual groundwork for the entire field of digital computing. He was one of the 1st thinkers to take the idea of AI seriously.

His 1950 paper opens with the line: ‘I propose to consider the question: can machines think?’ — and he introduced the Turing test, still an AI touchstone today.

Key papers by Alan Turing PhD.

  • visit | year 1936 ~ paper title: On Computable Numbers: with an application to the Entscheidungsproblem
  • visit | year 1950 ~ paper title: Computing Machinery + Intelligence

The 1983 book by Andrew Hodges PhD is a biography of Turing’s life. Prior to its publication, Turing wasn’t well know — because of the total secrecy that surrounded his war-time work on cryptography for the Allies at Bletchley Park. Hodges’ book played a pivotal role in bringing Turing’s ideas to light. And established him at the forefront of machine intelligence pioneers.

On the topic of AI, Turing made it clear where he stood. Generations ahead of his time — in words still provocative today — Turing wrote in year 1951: ‘It’s customary to state that some peculiarly human characteristic could never be imitated by a machine. I can’t offer such comfort. I believe no such bounds can be set.’

5. |

book title: the Singularity is Near
deck: When humans transcend biology.
author: by Ray Kurzweil
year: 2005

summary  |

Nobody has a more relentlessly optimistic view of our tech future than author Ray Kurzweil’s — in his book the Singularity is Near. Grounding his arguments in the concepts of exponential growth + accelerating returns — Kurzweil anticipates a future where run-away machine intelligence transforms everything about the world we know.

He predicts this super-intelligence will help us control genetics, master nano-tech, and easily manipulate physical matter. Eventually, human + non-human intelligence will merge, transcend biology, and spread across the universe. His conclusions are startling, but his approach is data-driven. As the New York Times said: ‘Ray Kurzweil’s vision of our super-enhanced future is completely sane and calmly reasoned.”

The concept of the singularity has inspired generations of technologists. But also garnered plenty of ridicule for its fantastical, utopian overtones. Kurzweil didn’t invent the idea — credit goes to legendary mathematician John von Neumann PhD in the 1950s — but he + this book have played a major role in popularizing it.

6. |

book title: Descartes’ Error
deck: Emotion, reason, and the human brain.
author: by Antonio R. Damasio PhD
year: 1994

summary |

Conventional wisdom has long held that — while the intellect is logic-based and objective — emotions make us irrational and cloud our judgment. In his book Descartes’ Error neurologist Antonio Damasio PhD famously re-conceptualized the relationship between emotion + intellect.

The book argues that emotions play an essential role in cognition + decision-making — and without them our intellectual capabilities would not be possible. This theory of intelligence has intriguing implications for AI. Famed computer scientist Marvin Minsky PhD once said: ‘The question is not whether intelligent machines can have any emotions, but whether machines can be intelligent without any emotions.’

7. |

book title: the Mind’s I
deck: fantasies + reflections on self + soul
editor: Douglas Hofstadter PhD
editor: Daniel Dennett PhD
year: 1981

summary |

In their book the Mind’s I authors Douglas Hofstadter PhD + Daniel Dennett PhD explore fundamental questions.

  • what is thought
  • what is consciousness
  • what is the mind

The book is an annotated anthology of pieces from diverse contributors: Richard Dawkins PhD, Jorge Luis Borges, and Alan Turing PhD. It contains insights about what it would mean for a machine to think — interweaving perspectives from psychology, engineering, philosophy, and literature. But don’t expect to walk away with any straight-forward answers.

They write in the book’s preface: ‘There are no easy answers to the big questions. This book is designed to provoke, disturb, and befuddle you.’

— notes —

AI = artificial intelligence