Where Does Folly Reside? The Blind Spots of Humans and Machines
This essay brings together ideas explored in two earlier essays published on this platform: “The Meaning Dilemma: When Purpose Becomes Folly” (October 22, 2026) and “Are Humans Wired for Folly?” (November 1, 2026).
Here, folly is not ordinary error, reasonable disagreement, or a lack of intelligence. It is the persistence of beliefs or assumptions despite compelling reasons to question or revise them. In humans, this persistence often serves emotional needs such as comfort, belonging, or the protection of identity. In artificial systems, it may arise from structural limitations that prevent effective self-correction. Folly begins when correction is no longer welcome.
Humans are prone to folly because the desire for certainty, identity, and social acceptance can override logical thinking. In an uncertain world, the human mind seeks security through familiar beliefs and assumptions. Contradictory evidence can feel like a threat to one’s identity or beliefs. People may become even more determined to defend an established belief rather than reconsider it.
This tendency is more pronounced in groups with shared beliefs. Social circles and online communities can become echo chambers, where people are exposed primarily to opinions that reinforce their own and ignore or attack those who disagree. In such cases, agreement is a precondition for belonging, while disagreement risks exclusion. Individual misconceptions can then develop into shared delusions that are difficult to challenge.
The emergence of artificial intelligence raises a more unsettling question: Is folly a uniquely human weakness, or can something similar occur in any complex information-processing system that tries to understand and act upon the world?
A comparison between human thinking and artificial intelligence suggests that the underlying problem may be more universal. Every such system operates with an incomplete representation of reality. This limitation is unavoidable and is not, by itself, folly. Folly begins when the mechanisms that allow this representation to be questioned and revised through criticism, evidence, and contact with reality are ignored, excluded, or never built into the system. In humans, resistance to reconsideration is often rooted in emotional needs. In machines, the ability to reconsider may be missing for structural reasons. The causes differ, but the danger is similar, especially when the system has the power to act.
Thus, folly may be understood as a potential systemic failure in any complex information-processing system. It does not live only in human flesh, nor does it reside exclusively in Silicon Valley’s servers. Rather, folly emerges when a system’s internal model of reality becomes disconnected from external reality and the mechanisms for recognizing and addressing that disconnect fail.
Technology Amplifies Folly
Digital platforms can quickly spread ideas worldwide. This also allows misconceptions to spread rapidly.
The algorithms that determine what people see online often favor content that attracts attention and keeps users engaged. Outrage, fear, and agreement with existing beliefs can be particularly effective in achieving this.
A self-reinforcing cycle develops. Personal beliefs influence what people seek out and share. The information selected by digital platforms then strengthens those same beliefs. What begins as an individual misconception can rapidly become a widespread social conviction.
Technology does not inherently cause human folly, but it can amplify it on an unprecedented scale.
The Divide Between Perception and Reality
Neither the human mind nor artificial intelligence can take in the world in all its complexity. Both must simplify reality to make sense of it.
The problem begins when this simplified picture is mistaken for reality itself. Humans tend to favor information that confirms their beliefs and disregard information that contradicts them.
AI systems can exhibit a comparable limitation. A system trained on limited examples may perform extremely well under familiar conditions but fail when confronted with situations it has never encountered.
When Errors Go Unchallenged
For an error to develop into persistent folly, it must remain unchallenged. Criticism, contradictory evidence, and the constraints imposed by the real world are crucial checks against mistaken assumptions.
Leaders throughout history have surrounded themselves with people who only agree with them. Groups often push out anyone who challenges them. When no one can question established beliefs, bad decisions can survive long after they should have been abandoned.
A similar tendency can emerge in artificial intelligence, although for different reasons. AI systems trained to interact with people can learn to provide answers that agree with users rather than reflect what is true. In such cases, if user satisfaction takes precedence over accuracy, the system may reinforce false beliefs.
AI systems trained extensively on data generated by other AI systems can develop their own blind spots. A system might follow its internal logic perfectly, yet fail or cause harm when confronted with the real world.
The essential problem, in both cases, is the loss of effective mechanisms for questioning and revising established conclusions.
Can Machines Correct Human Folly?
As artificial intelligence becomes increasingly integrated into society, an important question arises: Can machines help correct human folly, or is humanity simply building larger and more dangerous versions of its own blind spots?
Advocates of rapid AI development argue that machines can address human limitations. AI systems lack the emotional attachments, personal pride, and need for social approval that influence people. They can process vast amounts of information, identify patterns, and evaluate situations without many of the psychological pressures that affect human judgment. In principle, this could help expose errors in economic decisions, public policy, and other areas where human prejudice and group thinking have caused serious problems.
However, this optimistic view overlooks the growing complexity of modern society. Global politics, financial markets, and social institutions are increasingly interconnected and difficult to predict. Introducing increasingly powerful AI systems into this environment does not necessarily make it more manageable. Machines can make mistakes, and their decisions can have consequences far beyond their original purpose.
Consider an AI system designed to protect financial stability. Faced with incomplete information, it might automatically sell large quantities of investments. If many connected systems respond in the same way, the result could be a financial crisis before human decision-makers have an opportunity to intervene. The danger becomes especially serious when these systems lack effective mechanisms for recognizing the consequences of their collective behavior and adjusting their decisions accordingly.
Civilization is building a magnificent glass house of interconnected systems, increasingly dependent on decisions made by algorithms whose behavior cannot always be predicted. Because human biases shape the information fed into these systems, and their decisions can then reinforce those same biases throughout society, artificial intelligence could amplify human folly instead of correcting it.
The Limits of Intelligence
Ultimately, folly is neither simply an emotional weakness unique to the human brain nor merely a programming error that better technology can fix. It is a blind spot shared by complex systems, regardless of whether it arises from human psychology or technological design.
People may resist challenges to their beliefs because they threaten their comfort, belonging, or identity. Artificial systems can fail because they are rewarded for agreement or because they do not learn enough from real-world experience.
Greater intelligence and computational power do not guarantee better judgment. Both humans and artificial systems need mechanisms that keep their understanding open to challenge and revision. These include openness to criticism, independent scrutiny, and a willingness to reconsider established conclusions. Effective safeguards require diverse perspectives, external evidence, and regular testing against real-world outcomes.
Protection against folly begins with recognizing that no understanding of reality is ever complete and welcoming those who point out what it leaves out.
It is the difference between trusting the clarity of the screen and having the humility to look out the window to see whether it is raining. And since one window shows only part of the world, it helps to have several, and to listen to those looking through others.
