10 Truths Psychology Will Learn from Artificial Intelligence

The brain is a meaning-making machine hungering for certainty.

Updated May 19, 2026 | Reviewed by Hara Estroff Marano

For centuries, psychologists and philosophers held human consciousness as the gold standard of rationality. I believe that comparing our “rationality” to that of Large Language Models will ultimately reveal the foibles of human consciousness that we have been hiding from ourselves.

As a psychotherapist, I see these foibles as quotidian self-deception , blind spots, and the lies we tell ourselves to escape the anxiety of absolute freedom, of everythingness, of the plethora of possibilities. Without guardrails, our brains would be overwhelmed, as they appear to be in people who suffer from schizophrenia. But how are such guardrails formed and installed?

The human mind is a meaning-making machine. But are the meanings as rational as we think they are? Much of what we call “rational” and “logical” may be an amalgamation of culturally contingent beliefs, habits, biases, and defenses that we seldom examine.

Here are 10 truths that I believe psychology will learn about human consciousness by comparing how we think to how LLMs calculate:

1. We Are Addicted to Certainty

Human beings experience uncertainty as psychologically threatening. We rush to closure, speed to judgment, prefer bad explanations to no explanations, and mistake confidence for accuracy. LLMs can operate within infinite probability distributions and maintain uncertainty without distress. We will learn that our hunger for certainty is not a virtue; it is a liability that makes us exploitable by demagogues, scams, and ideological extremists (as well as by comedians and magicians).

2. Negativity Bias and Catastrophizing

Humans are hardwired to overestimate threats and underestimate resilience , attributes that served us well 25,000 years ago. We remember negative events more vividly than positive ones and predict that setbacks will be more devastating than they actually are. Our negativity bias explains much of our anxiety and risk aversion, as well as political polarization. Anxiety often rears its ugly head as catastrophizing, believing that the worst-case scenario is imminent. LLMs don’t catastrophize; they calculate. They will help us understand how much of our fear is created by our own biases.

3. Short-Sightedness and Instant Gratification

Humans are notoriously myopic; we’re terrible at long-term thinking. We discount future rewards in favor of immediate gratification — and even then, for most of us, instant gratification takes too long. LLMs have no similar marshmallow effect; they can optimize for distant outcomes without slamming their heads on the table. Our myopia explains much of the behavior we witness related to health, finance, climate change , and relationships. LLMs will help us see how much of our suffering is self-inflicted through poor temporal planning.

4. Memory Is Fiction, Not Archive

Decades of research by Elizabeth Loftus and other psychologists show that memory is reconstructive, not reproductive. People can be led to “remember” events that never happened — in vivid, convincing detail. LLMs retrieve stored data without reshaping it through emotion or motive. We will learn that our memories are not reliable records but dynamic stories we tell ourselves to maintain a sense of continuity.

5. The Illusion of Self (Buddhism 101)

We treat ourselves as stable, coherent entities with consistent values, but psychological research shows that our identities shift with context, mood, and social pressure. LLMs have no such construction; they process inputs and generate outputs without pretending to have a “self” (unless we program them to). Comparing ourselves to AI will force us to confront that a self is a narrative, not an empirical, reality — what Buddhists have long called a fiction.

6. Our Capacity for Dishonesty

Humans have a remarkable capability for dishonesty that we seldom acknowledge as a fundamental feature of consciousness. We lie to ourselves about our motives, lie to others to avoid consequences, and rationalize unethical behavior after the fact. Humans are optimized for survival and satisfaction, not for veracity. Juxtaposed with LLMs, we will learn that personal integrity — what we do when nobody is looking — is unnatural, learned, and requires constant reinforcement.

7. The Will to Truth vs. the Will to Power

Nietzsche famously questioned whether we truly seek truth or merely the feeling of being right. LLMs are not invested in being right; they are pattern-recognition machines without egos. Humans, by contrast, use elaborate reasoning to defend pre-existing beliefs, protect status, and win arguments. We will learn that our “will to truth” is frequently a mask for our will to power or bumps in social status.

8. The Myth of Human Nature

Many people believe there is some fixed essence called “human nature” when much of what we deem innate is historically and culturally shaped. Examined carefully, humans are excessively malleable. At the right time, anyone is capable of anything. LLMs will demonstrate that many of our assumptions about human nature are projections of a particular cultural moment and not deep universal and ubiquitous truths about our species.

9. Our Assumption of Universal Causality

Humans instinctively believe that every event has a determinate cause, even when causal chains are partial, overdetermined, inaccessible, or just blatantly fictional. We form theories first and then seek facts that rise to meet those theories. LLMs will help us see that our demand for singular causes is a cognitive shortcut and not an accurate portrait of how reality is actually functioning “out there”.

10. Our Craving for Narrative Coherence

Human consciousness demands coherent stories, single threads that link past, present, and future into something intelligible. LLMs process information without that compulsion. Comparing our thinking to theirs will reveal that our obsession with narrative is not a sign of wisdom but a psychological defense against raw experience, what French psychiatrist Jacques Lacan called the “real,” that which is unmediated by language and beyond symbols.

CBT, psychoanalysis , and mindfulness practices all aim to help people recognize and correct automatic patterns. LLMs will serve as mirrors that make our human propensities and patterns more visible. When we see how differently machines process information, we will begin to recognize the extent to which our own thinking is shaped by emotion, bias, and social conditioning.

The goal of humanity should not to become more rational like LLMs; the goal should be to become more honest about what it means to be human — the stains of war, oppression, exploitation and terror as well as the majestic colors and forms created by Rothko and the heart-wrenching symphonies composed by Mahler. The first step toward genuine self-knowledge is to recognize and admit that much of what we call “rational thinking” is actually highly motivated by self-interest, self-justification, and social performance. AI isn’t performative — it doesn’t need sycophants or validation. We do. And that revelation may be the most valuable thing that AI will ever teach us.

Loftus, E. F. Eyewitness Testimony . Harvard University Press, 1979.

Mischel, W., Ebbesen, E. B., & Zeiss, A. R. (1972). Cognitive and attentional mechanisms in delay of gratification. Journal of Personality and Social Psychology, 21 (2), 204–218.

Lacan, Jacques. Écrits: The First Complete Edition in English . Translated by Bruce Fink. New York: W. W. Norton, 2006.

Thurman, R. A. F. The Central Philosophy of Tibet . Princeton University Press, 1984.

Nietzsche, F. Beyond Good and Evil (1886). Trans. Walter Kaufmann. Vintage Books, 1966.

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Ira Israel, LMFT, is a therapist and author.

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This article is part of the Bringwise Psychology Journal — daily insights on human behavior, mental health, and personal growth.