Is AI really ‘intelligent’? This philosopher says yes

2026-02-19 · Source: Artificial intelligence (AI) – The Conversation · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation, Computational Biology · Depth: Intermediate, extended

Summary

Blaise Agüera y Arcas, a Google luminary, challenges conventional views on intelligence in his book "What Is Intelligence: Lessons from AI about Evolution, Computing, and Minds," the inaugural title in MIT Press's Antikythera series. Agüera y Arcas, a polymath with a background in computational neuroscience, argues that computation is the fundamental substrate for intelligence across all life forms, asserting that AI can achieve "real" intelligence. His central premise is that prediction, understood as pattern development from single cells to complex organisms, is the core principle of intelligence. The book explores how scaling up computational power might lead from Artificial Narrow Intelligence (ANI) to Artificial General Intelligence (AGI). He also presents an experiment using the programming language Brainfuck, demonstrating how replicating code can emerge from random "Turing gas" after millions of iterations, suggesting a phase transition that could challenge natural selection's primacy in evolution. The work integrates concepts from microbiology, philosophy, linguistics, cybernetics, and neuroscience, drawing on figures like Alan Turing and Lynn Margulis.

Key takeaway

For AI Scientists grappling with the definition and potential of Artificial General Intelligence, Agüera y Arcas's perspective offers a compelling re-evaluation. You should consider his argument that intelligence is fundamentally computational and driven by prediction, as this reframes the pursuit of AGI from merely mimicking human thought to understanding a universal principle of system function. This shift could guide your research towards emergent properties in large-scale computational systems, rather than solely focusing on organic analogies, potentially accelerating breakthroughs in AI development.

Key insights

Intelligence is a computational property of systems, driven by prediction and pattern completion across biological and artificial forms.

Principles

• Computation underlies intelligence in all life forms.
• Prediction is the fundamental principle of intelligence.
• Intelligence is a property of systems, not just beings.

Method

An experiment using Brainfuck demonstrated that replicating code can emerge from random "Turing gas" through iterative pattern recognition, suggesting a computational basis for life's origins.

In practice

• Explore computational models for emergent biological complexity.
• Re-evaluate AI's potential for "real" intelligence beyond current skepticism.

Topics

• Artificial General Intelligence
• Computational Intelligence
• Evolutionary Biology
• Symbiogenesis
• Genetics

Best for: AI Scientist, AI Researcher, Research Scientist, AI Ethicist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial intelligence (AI) – The Conversation.