Critics argue that the AI industry's 'computational' view of the brain is flawed, suggesting that humans function more as dynamic feedback-control systems.

The AI industry frequently characterizes the human brain as a biological computer, a model rooted in the work of Alan Turing. However, some neuroscientists and critics argue this perspective is limited and fails to account for the complex, evolutionary nature of human cognition. They contend that viewing AI as a replacement for human thought processes poses risks to the cognitive systems humans have developed over millennia.

Computational vs. Feedback-Control Models

The computational model views the brain as an algorithm that processes inputs to produce outputs. In contrast, neuroscientist Paul Cisek of the University of Montreal proposes that brains are better understood as feedback-control systems. In this view, humans do not just process information; they take physical action to adjust their environment and the stimuli they receive. This approach is illustrated by the act of catching a baseball. While a computational model suggests the brain performs complex mathematical calculations to predict the ball's trajectory, the feedback-control approach suggests the player simply moves to keep the ball in a consistent position within their visual field.

The Impact of AI on Human Cognition

Critics compare the widespread adoption of AI to the dietary shift toward processed foods. Just as the modern availability of fatty foods can harm physical health, they argue that relying on AI for cognitive tasks may undermine the mental development and knowledge-building processes humans have evolved to use. Despite these concerns, major technology companies are integrating AI into educational environments. OpenAI reported in July 2025 that learners comprised over half of ChatGPT's 900 million average monthly users, while Anthropic recently launched 'Claude for Teachers' to provide educators with access to its models.