Evolution of Intelligence: Human Brains and AI Reflect Each Other

Published Date : 30/09/2025 

Blaise Agüera y Arcas, a leading AI researcher, explores the parallels between the evolution of human and artificial intelligence, emphasizing the role of cooperation in increasing complexity. 

The term artificial intelligence (AI) often implies that what computers do is inferior to or separate from human intelligence. However, AI researcher Blaise Agüera y Arcas argues that this may not be the case. Agüera y Arcas, Google’s CTO of technology and society, traced the evolution of both human and artificial intelligence, highlighting their similarities, during a Wednesday event sponsored by Harvard Law School’s Berkman Klein Center for Internet & Society.

Agüera y Arcas, the author of the new book “What Is Intelligence? Lessons from AI About Evolution, Computing, and Minds,” posed a critical question: “Why has the computational power of brains, not just of AI models, grown explosively throughout evolution?” He explained that if we rewind 500 million years, we see only things with very small brains, and if we go back a billion years, we see no brains at all.

According to Agüera y Arcas, human brains evolved to be computational, meaning they process information by transforming various kinds of inputs into signals or outputs. Most of the computation that brains do takes the form of predictions, which is also what AI systems do. “I hear a lot of people say that it’s a metaphor to talk about brains as computers,” said Agüera y Arcas. “I don’t mean this metaphorically. I mean it very literally … The premise of computational neuroscience is that what brains do is process information, not that they are like computers, but that they are computers.”

Agüera y Arcas’ book delves into the evolution and social origins of intelligence, drawing on ideas from scientists such as Alan Turing and John von Neumann, who theorized about self-replication and universal computation. He also incorporates evolutionary biologist Lynn Margulis’ theory of symbiogenesis, which posits that the merging of different organisms to form more complex entities played a crucial role in cell evolution. This theory helps explain the computational similarities between biology and AI models, which also engage in symbiotic relationships and develop greater complexity and intelligence.

Charles Darwin’s theory of evolution, which focuses on random mutation and natural selection, is only part of the story, Agüera y Arcas noted. Symbiogenesis, characterized by cooperation, is the creative engine behind evolutionary progress. “Life was computational from the start,” said Agüera y Arcas. “It becomes more computationally complex over time through symbiogenesis because when two computers come together and start cooperating, they form a parallel computer, leading to more and more parallel computation, which is exactly what we see in nervous systems with many neurons computing functions in parallel.”

During his talk, Agüera y Arcas demonstrated experiments he conducted at Google using a programming language to explore the development of complex programs from simple, random initial conditions. The root programming language used only eight basic instructions, but after millions of interactions, more complex programs began to emerge because they became self-reproducing. “It was an exploration of how self-reproducing entities can arise out of random initial conditions, which is how life must have arisen,” said Agüera y Arcas. “We know that life didn’t always exist in the universe. There must have been initial conditions that are disordered from which life arose.”

Agüera y Arcas views intelligence as the ability to predict and influence the future. He traces the “human intelligence explosion” to the moment when humans formed societies and began cooperating and living together. He argues that the growth and evolution of human brains began when they banded together and created collective societies. The emergence of societies was a major evolutionary transition, he said, citing the work of scientists Eörs Szathmáry and John Maynard Smith.

“Human individuals are not very smart, but when we get together, we can do amazing things, like transplanting organs and going to the moon,” said Agüera y Arcas. “These are not individual capabilities. No individual human can do that. That’s a collective human intelligence sort of thing, and it comes about through specialization, through theory of mind, through us being able to model each other in order to work in groups.” 

Frequently Asked Questions (FAQS): 

Q: What is the main argument of Blaise Agüera y Arcas regarding AI and human intelligence?

A: Blaise Agüera y Arcas argues that AI and human intelligence are not as different as commonly thought. He suggests that both are computational in nature and that the growth of computational power in both brains and AI models is driven by cooperation and symbiosis.

Q: How does Agüera y Arcas explain the computational nature of human brains?

A: Agüera y Arcas explains that human brains are computational, meaning they process information by transforming inputs into outputs. Most of this computation takes the form of predictions, similar to what AI systems do.

Q: What is symbiogenesis, and how does it relate to the evolution of intelligence?

A: Symbiogenesis is the theory that the merging of different organisms to form more complex entities played a crucial role in cell evolution. Agüera y Arcas uses this concept to explain how cooperation leads to greater computational complexity in both biological and AI systems.

Q: What experiments did Agüera y Arcas conduct to support his theories?

A: Agüera y Arcas conducted experiments using a programming language with only eight basic instructions. After millions of interactions, more complex programs began to emerge, demonstrating how self-reproducing entities can arise from random initial conditions, similar to the origin of life.

Q: How does Agüera y Arcas view the role of cooperation in human intelligence?

A: Agüera y Arcas views cooperation as crucial to the evolution of human intelligence. He argues that the growth and evolution of human brains began when humans formed societies and started working together, leading to collective human intelligence. 

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