The artificial intelligence industry frequently relies on a computational model of the human brain that traces back to Alan Turing’s foundational work in computer science. Industry leaders, including figures like Demis Hassabis and Elon Musk, describe the brain as essentially a biological computer that processes information through a straightforward input-computation-output algorithm. While this conceptual framework has proved productive in advancing computing technology over the past century, neuroscientists argue it represents a significantly warped and incomplete understanding of how human cognition actually functions.
Paul Cisek, a neuroscientist at the University of Montreal, proposes an alternative model rooted in evolutionary biology. Rather than information processors, Cisek contends that brains function as feedback-control systems shaped by millions of years of neural development. This approach emphasizes that organisms actively take action to adjust the stimuli they receive, rather than passively processing external inputs according to mathematical algorithms. The feedback-control model aligns more closely with how people actually experience cognitive tasks—such as a baseball outfielder catching a fly ball through simple heuristics rather than complex unconscious calculations.
Cisek’s framework maps directly onto observable biological structures and evolutionary history in ways the computational model cannot. As vertebrates developed increased mobility and new environmental opportunities, specialized brain systems emerged to support exploration, navigation, and memory formation. This progression traces from ancient fish through modern humans, with each evolutionary stage introducing new behavioral capabilities and corresponding neural developments. The hippocampus, for instance, arose alongside the capacity for episodic memory as ancestors needed to navigate between locations.
The distinction between these two models has significant implications for how AI systems are designed and deployed. A computational framework that divorces mental processes from physical movement and environmental interaction obscures what brains fundamentally do: control organisms’ interactions within their environments. As artificial intelligence technology becomes increasingly integrated into culture and daily life, the article suggests that misunderstandings about human cognition may be contributing to problems in how these systems function and influence society.
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