Why Treating the Human Mind as a Computer Is Leading to Cognitive Decline
The tech industry's computational view of the human brain is driving the rise of 'cognitive automation,' threatening our capacity for deep, independent thought.
For decades, the tech industry has operated under the assumption that the human brain functions like a computer. Google’s Demis Hassabis has described the brain as a "biological approximation to a Turing machine," while Elon Musk has called it a "biological computer." However, this computational model of the mind—which reduces thinking to a simple sequence of input, computation, and output—fails to capture the true complexity of human biology. According to neuroscientific and evolutionary perspectives, treating our minds as computers has led to the creation of artificial intelligence tools that act as "cognitive hot dogs": tempting and convenient in the short term, but ultimately damaging to our long-term mental health and cognitive development.
Feedback Systems vs. Computational Models
Paul Cisek, a neuroscientist at the University of Montreal, argues that the human brain is better understood as a feedback-control system rather than an information processor. This perspective aligns with ideas from philosopher John Dewey, who viewed the mind as an organic circuit where actions continuously shape sensory inputs. To illustrate this, consider how a baseball outfielder catches a fly ball. A computational model suggests the brain calculates complex trajectory algorithms. In reality, the outfielder uses a simple feedback heuristic: they move to keep the ball in a constant position within their visual field. Human evolution has shaped our nervous systems to dynamically interact with and control our environment, not just execute calculations.
The Rise of Cognitive Automation
As generative AI tools proliferate, they risk automating the very cognitive processes required to build human knowledge. François Chollet, a former Google software engineer, describes this phenomenon as "cognitive automation"—the practice of encoding human abstractions into software to automate tasks typically performed by humans. This automation is rapidly penetrating educational systems. In July 2025, OpenAI’s VP of education, Leah Belsky, noted that learners constituted more than half of ChatGPT’s 900 million monthly active users. Meanwhile, Anthropic recently introduced its "Claude for Teachers" initiative to bring its models into classrooms.
However, delegating active thinking to AI has measurable drawbacks. Research from China indicates that thousands of students stopped completing their homework once they gained access to AI, resulting in significant learning loss. Furthermore, studies show that using large language models can habituate students to relaxing their critical thinking and judgment. When cognitive tasks are continuously delegated to machines, the social and institutional frameworks that support autonomous reasoning begin to erode.
What it means for developers
For developers building the next generation of AI applications, these insights demand a shift in design philosophy. Rather than building tools aimed at complete cognitive delegation—where the AI does all the thinking and outputs a finished product—developers should focus on creating systems that foster active human engagement and feedback. Designing software that acts as a collaborative partner, prompting users for critical input and verification, can help prevent cognitive decline.
To explore how different LLMs handle interactive prompting and feedback-driven workflows, developers can try top AI models cheaply through one API at https://apixoai.online. Testing how various models from Anthropic, OpenAI, and Google respond to cognitive-preservation designs allows developers to build more responsible, interactive software.
The Pushback and Cognitive Immunization
To counter the negative impacts of cognitive automation, researchers advocate for "cognitive immunization." This involves preserving spaces for unaided problem-solving, critical debate, and deliberate disengagement from AI. Educational institutions and policymakers are already taking action. Norway has banned AI usage for students under the age of 13, and major US school districts, including New York City and Los Angeles, have implemented similar restrictions.
Even students are resisting; the Oberlin Luddite Club recently wrote an open letter protesting their university's embrace of AI, urging a return to raw inquiry and human imperfection. Protecting human cognitive health requires recognizing that our minds are not computers to be programmed, but active biological systems that thrive on effortful engagement.
Source: Our minds aren’t equipped to handle AI — The Verge AI. Written by the Apixo team from that report.
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