Ten Books About AI Written Before the Year 2000
A somewhat arbitrary, non-definitive list.
AI is an inescapable subject. There’s obviously an incredible headwind behind the computing progress of the last handful of years — not to mention the usual avarice — but there has also been nearly a century of thought put toward artificial intelligence.
If you want to have a more robust understanding of what is at work beneath, say, the OpenAI chat box, pick any one of these texts. Each one would be worth a read — even a skim (this is by no means light reading).
At the very least, familiarizing yourself with the intellectual path leading to now will help you navigate the funhouse of overblown marketing bullshit filling the internet right now, especially as it pertains to AGI. Read what the heavyweights had to say about it and you’ll see how many semantic games are being played while also moving the goalposts.
Steps to an Ecology of Mind (1972) — Gregory Bateson. Through imagined dialogues with his daughter, Bateson explores how minds emerge from systems of information and communication, providing crucial insights for understanding artificial intelligence.
The Sciences of the Artificial (1969) — Herbert Simon examines how artificial systems, including AI, differ from natural ones and introduces key concepts about bounded rationality.
The Emperor’s New Mind (1989) — Roger Penrose. While arguing against strong AI, Penrose provides insights into consciousness and computation that remain relevant to current AI discussions.
Gödel, Escher, Bach: An Eternal Golden Braid (1979) — Douglas Hofstadter weaves together mathematics, art, and music to explore consciousness, self-reference, and emergent intelligence. Though not explicitly about AI, it explores how complex cognition might emerge from simple rules and patterns.
Perceptrons (1969) — Marvin Minsky & Seymour Papert. This controversial critique of neural networks temporarily halted research in the field but ultimately helped establish its theoretical foundations. Minsky and Papert’s mathematical analysis revealed both the limitations and potential of early neural networks.
The Society of Mind (1986) — Marvin Minsky proposes that intelligence emerges from the interaction of simple agents working together, rather than from a single unified system. This theoretical framework remains relevant to understanding both human cognition and artificial intelligence.
Computers and Thought (1963) — Edward Feigenbaum & Julian Feldman (editors) This is the first collection of articles about artificial intelligence, featuring contributions from pioneers like Herbert Simon and Allen Newell. It captures the foundational ideas and optimism of early AI research.
Artificial Intelligence: A Modern Approach (1995) — Stuart Russell & Peter Norvig. This comprehensive textbook defined how AI would be taught for decades. It presents AI as rational agent design rather than human intelligence simulation, a framework that still influences the field.
Computing Machinery and Intelligence (1950) — Alan Turing’s paper introduces the Turing Test and addresses fundamental questions about machine intelligence that we’re still grappling with today. It’s remarkable how many current AI debates were anticipated in this work.
Cybernetics: Or Control and Communication in the Animal and the Machine (1948) — Norbert Wiener established the theoretical groundwork for understanding control systems in both machines and living things. His insights about feedback loops and communication remain crucial to understanding AI systems.
Written by Christopher Butler on
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