A response to “Large Language Model Reasoning Failures” (Song, Han & Goodman, 2026)
Cosmo II†, Francesco‡
†Cat Technology Officer, Method & Apparatus
‡Method & Apparatus
†Work done while napping on keyboard. ‡Equal contribution except for the napping.
Published at TMLR 2026 with Existential Crisis Certification
Abstract
Humans (Homo sapiens, hereinafter “Humans”) have exhibited remarkable reasoning capabilities, achieving impressive results across a wide range of tasks including agriculture, architecture, the invention of nuclear weapons, and occasionally remembering where they left their keys. Despite these advances, significant reasoning failures persist, occurring even in seemingly simple scenarios such as opening childproof bottles, understanding probability, assessing compound risk, and interpreting the phrase “some assembly required.”
To systematically understand and address these shortcomings, we present the first comprehensive survey dedicated to reasoning failures in Humans. We introduce a novel categorization framework that distinguishes reasoning into caffeinated and non-caffeinated types, with the latter further subdivided into pre-lunch (intuitive, irritable) and post-lunch (drowsy, overconfident) reasoning. In parallel, we classify reasoning failures along a complementary axis into three types: fundamental failures intrinsic to human neural architectures (e.g., the sunk cost fallacy), application-specific limitations that manifest in particular domains (e.g., assembling IKEA furniture), and robustness issues characterized by wildly inconsistent performance across minor variations (e.g., doing math with and without a calculator).
For each reasoning failure, we provide a clear definition, analyze existing studies, explore root causes (usually ego), and present mitigation strategies (usually coffee). By unifying fragmented complaints about human cognition, our survey provides a structured perspective on systemic weaknesses in human reasoning, offering valuable insights that Humans will almost certainly ignore due to confirmation bias.
We additionally release a comprehensive collection at a GitHub repository (which the first author knocked off the desk and lost).
1. Introduction
Since the emergence of the first general-purpose Human approximately 300,000 years ago, remarkable progress has been made in language generation, tool use, and abstract reasoning. Early benchmarks such as “not dying before age 30” and “basic agriculture” were quickly saturated, leading researchers to develop increasingly challenging evaluation suites including “calculus,” “democratic governance,” and “parallel parking.”
However, despite scoring well on curated benchmarks, Humans consistently fail at deployment. Production Humans exhibit catastrophic reasoning failures that do not appear during controlled evaluation (i.e., exams). These failures include but are not limited to: purchasing lottery tickets, clicking “Reply All,” invading Russia in winter, and believing they can finish a project by Friday.
2. Taxonomy of Human Reasoning Failures
2.1 Probabilistic Reasoning Failures
Perhaps the most well-documented class of human failure. Despite ~400 years since Pascal and Fermat formalized probability, Humans remain unable to:
- The Gambler’s Fallacy: Believing that a roulette wheel “remembers” previous results, or that rain is “due” after a dry spell. (Humans: 300,000 years of experience, still can’t internalize independence.)
- Base Rate Neglect: “The test is 99% accurate and I tested positive, so I definitely have it.” (Narrator: The disease affects 1 in 10,000 people.)
- Conjunction Fallacy (Tversky & Kahneman, 1983): Linda is a bank teller. Linda is a bank teller and active in the feminist movement. Humans consistently rate the conjunction as more probable than the single event, violating a rule so basic it’s Probability 101, Lecture 1, Slide 3.
- Exponential Growth Blindness: Ask a Human how many times they’d need to fold a piece of paper to reach the Moon. Watch them say “a million.” (Answer: ~42.)
- Misunderstanding of Conditional Probability: “I know someone who smoked and lived to 95.” Case closed, apparently.
2.2 Risk Assessment Failures
A special case of probabilistic failure, elevated to its own category by sheer volume of evidence:
- Dread Risk Bias: Terrified of shark attacks (annual deaths: ~5). Fine with driving to the beach (annual deaths: ~40,000 in the US alone).
- Optimism Bias: “I know the statistics on startups, but mine is different.” (Narrator: It was not different.)
- Temporal Discounting: Future consequences are treated as fictional. Retirement planning, climate change, and flossing all suffer from the same failure: if it’s not on fire right now, it doesn’t count.
- Risk Compensation: Give humans seatbelts, they drive faster. Give them helmets, they take more risks. Safety equipment is, in effect, a reasoning failure accelerant.
- Denominator Neglect: “200 people died in plane crashes this year!” Out of 4 billion passengers. Meanwhile, the Human drove to the airport in the rain while texting.
2.3 Cognitive Bias Failures
The core architecture of the Human reasoning system is riddled with what, in any other system, would be called bugs but which Humans have rebranded as “heuristics”:
- Confirmation Bias: The flagship failure. Humans don’t search for truth — they search for evidence they’re right. When presented with disconfirming evidence, activation levels in the “yeah but” module spike by 300%.
- Anchoring Effect: Show a Human an arbitrary number before asking them to estimate something. The answer will orbit that number like a moth around a lamp. Real estate agents are, empirically, expensive moths.
- Dunning-Kruger Effect: Inverse correlation between competence and confidence. The less a Human knows about a topic, the more certain they are about it. Peak confidence occurs at approximately one YouTube video of exposure.
- Sunk Cost Fallacy: “I’ve already watched two hours of this terrible movie, I can’t stop now.” A failure so universal that it drives wars, bad marriages, and enterprise Java projects alike.
- Availability Heuristic: Probability of an event = how easily a Human can imagine it. This is why Humans fear terrorism more than heart disease and believe they’ll win the lottery because they saw someone on TV who did.
- Bandwagon Effect: If enough other Humans believe something, it must be true. This heuristic produced democracy, scientific consensus, and tulip mania, which is honestly a hell of a range.
- Survivorship Bias: “Bill Gates dropped out of college and he’s a billionaire!” Survey excludes the millions of dropouts currently not being billionaires.
- The IKEA Effect: Humans irrationally overvalue things they built themselves, even when the shelf is visibly crooked. This extends to ideas, code, and taxonomies in survey papers.
2.4 Logical Reasoning Failures
- Affirming the Consequent: “If it rains, the street is wet. The street is wet. Therefore it rained.” (The street is wet because a pipe burst, but the Human has already committed.)
- Appeal to Nature: “It’s natural, so it must be good.” Arsenic is natural. So are tsunamis.
- False Dichotomy: “You’re either with us or against us.” A framework so popular it has been adopted by every Human political system simultaneously.
- Post Hoc Ergo Propter Hoc: “I wore my lucky socks and we won the game.” The socks have entered the permanent rotation.
2.5 Social Reasoning Failures
- Fundamental Attribution Error: When I cut someone off in traffic, it’s because I’m late. When they cut me off, it’s because they’re a terrible person.
- Bystander Effect: 50 Humans watch someone in trouble. Each one assumes one of the other 49 will help. Nobody helps. This is distributed reasoning at its worst.
- In-Group Bias: My group is rational and good. Your group is irrational and bad. (Both groups exhibit identical reasoning failures.)
3. Mitigation Strategies
| Failure Class | Mitigation | Effectiveness |
|---|---|---|
| Probabilistic | Statistics education | Low (Humans forget within days) |
| Risk Assessment | Showing actual numbers | Very low (Humans prefer vibes) |
| Cognitive Biases | Awareness training | Paradoxically makes it worse (Humans become biased about being unbiased) |
| Logical | Philosophy courses | Variable (introduces new, fancier fallacies) |
| Social | Empathy | Promising but doesn’t scale |
| All of the above | Coffee | Moderate improvement, rapidly diminishing returns |
| All of the above | Naps | Surprisingly effective but culturally stigmatized |
4. Comparison with LLMs
In the interest of fairness, we conducted a comparative analysis:
| Capability | Humans | LLMs |
|---|---|---|
| Probability | Terrible | Actually decent |
| Risk Assessment | Emotional | Has no emotions (allegedly) |
| Cognitive Biases | All of them | Different ones, but equally bad |
| Logical Reasoning | Intermittent | Intermittent |
| Learning from Mistakes | Theoretically possible | Requires retraining |
| Overconfidence | Chronic | Chronic |
| Self-awareness of failures | Present but ignored | Present but hallucinated |
5. Conclusion
After a comprehensive review of the literature spanning 3,000 years of documented human reasoning failures, we conclude that Humans are fundamentally a beta release that shipped to production. While mitigation strategies exist, their adoption is consistently undermined by the very reasoning failures they aim to address — a failure mode we term meta-irrationality and which we believe is load-bearing for civilization.
Future work should focus on whether Humans can be fine-tuned, or whether a from-scratch approach (see: cats) would be more cost-effective.
References
[1] Kahneman, D. (2011). Thinking, Fast and Slow. A comprehensive technical manual for human cognitive bugs, written by a Human, which most Humans bought and did not finish reading.
[2] Tversky, A. & Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases. Science. The paper that formally proved Humans are bad at thinking, and which Humans have been misapplying ever since.
[3] Dunning, D. & Kruger, J. (1999). Unskilled and Unaware of It. Journal of Personality and Social Psychology. Most frequently cited by people experiencing the effect.
[4] Ariely, D. (2008). Predictably Irrational. Title is also a fair description of the authors’ book sales predictions.
[5] Taleb, N.N. (2007). The Black Swan. A book about how humans can’t predict rare events, which nobody predicted would become a bestseller.
[6] Thaler, R. (2015). Misbehaving: The Making of Behavioral Economics. Won a Nobel Prize for documenting that Humans are bad at reasoning. The irony was lost on the prize committee.
[7] This paper. We cite ourselves because confirmation bias told us to.












