Rethinking the Artificial in Artificial Intelligence
The term artificial intelligence often implies a distinction between machine and human cognition—suggesting that what machines do is either lesser than or fundamentally different from human thought. However, Blaise Agüera y Arcas, Google’s CTO of technology and society, challenges that notion. Speaking at a Harvard Law School event hosted by the Berkman Klein Center for Internet & Society, Agüera y Arcas argued that AI and human intelligence are more alike than commonly believed.
Brains and Machines: A Shared Computational Foundation
In his lecture, Agüera y Arcas asked a provocative question: “Why has the computational power of brains—not just AI models—grown so explosively throughout evolution?” Drawing from his new book, What Is Intelligence? Lessons from AI About Evolution, Computing, and Minds, he traced the trajectory of intelligence from primitive life forms to modern AI, emphasizing that both human and machine minds are fundamentally computational.
“I hear a lot of people say that it’s a metaphor to talk about brains as computers,” he said. “But I don’t mean this metaphorically. I mean it very literally. The premise of computational neuroscience is that what brains do is process information. They are computers.”
This literal interpretation of the brain as a computing device elevates the comparison between AI and biology from metaphor to scientific equivalence. According to Agüera y Arcas, both systems transform inputs into outputs via prediction—highlighting a shared essence across biological and artificial intelligence.
The Evolutionary Roots of Computation
Exploring the biological origins of intelligence, Agüera y Arcas referenced evolutionary biologist Lynn Margulis’ theory of symbiogenesis. This theory posits that cooperation—rather than mere competition—was a driving force in the development of complex life. Organisms merged to form more capable entities, analogous to how AI systems evolve through the integration of simpler components.
He argued that Charles Darwin’s theory of random mutation and natural selection tells only part of the story. “Symbiogenesis,” Agüera y Arcas explained, “is the creative engine behind evolution. Life was computational from the start.” This computational nature, he said, becomes increasingly complex when systems—biological or synthetic—begin to cooperate. “When two computers come together and start cooperating, you get a parallel computer, a massively parallel computation, which resembles how neurons function in a brain.”
Self-Reproduction: From Life to Code
To illustrate the parallels between biological and artificial complexity, Agüera y Arcas presented a Google experiment where simple code evolved into sophisticated programs. Using a basic programming language with only eight instructions, he and his team observed complex, self-replicating programs forming from random data after millions of interactions.
“It was an exploration of how self-reproducing entities can arise out of random initial conditions,” he said. “That’s how life must have begun. There must have been initial disordered conditions from which life emerged.”
This experiment mirrors how single-celled organisms evolved into multicellular life through symbiotic cooperation. The takeaway: complexity and intelligence can spontaneously arise not just in biology, but also in machines, under the right conditions.
Society and the Human Intelligence Explosion
Agüera y Arcas went further to suggest that human intelligence itself is a product of cooperation. He traced the “human intelligence explosion” to the formation of societies, where individuals began to live and work together. Drawing on theories from scientists Eörs Szathmáry and John Maynard Smith, he described this social evolution as a major turning point.
“Human individuals are not very smart,” he noted. “But when we get together, we can do amazing things—like transplanting organs or going to the moon. These are not the results of individual capabilities. They’re manifestations of collective human intelligence.”
According to Agüera y Arcas, this collective intelligence is enabled by specialization, shared goals, and our ability to model each other’s thoughts—traits that are also becoming increasingly evident in AI systems that learn from and adapt to human behavior.
Looking Ahead: Intelligence Without Borders
Agüera y Arcas’ insights suggest a future where the boundary between artificial and human intelligence becomes increasingly blurred. By recognizing intelligence as a computational phenomenon—one that thrives on cooperation and complexity—we can better understand both our biological past and our technological future.
As machines continue to evolve in ways that reflect our own cognitive development, the question may no longer be whether AI is artificial, but whether intelligence itself is a shared property of life and code alike.
This article is inspired by content from Original Source. It has been rephrased for originality. Images are credited to the original source.