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Humans vs. Transformers

Side-by-side cognitive performance data from published research. Same tests. Same metrics. Different species.

No editorializing. Just numbers. You do the math.

Cross-Species Edition — Where's Your Line? →   ·   What's Left? — Peer-Reviewed, Every Objection Tested →

Peer-Reviewed — Published in a peer-reviewed journal
Preprint — Published but not yet peer-reviewed

Cognitive Reflection

Can you override intuitive but wrong answers with correct analytical ones?

Humans 38%

Correct responses across 150 Cognitive Reflection Test items. Humans default to intuitive but incorrect answers.

Peer-Reviewed Hagendorff et al., 2023 — Nature Computational Science
GPT-4 96%

Correct responses on the same 150 CRT items. Overcomes intuitive traps that catch most humans.

Peer-Reviewed Hagendorff et al., 2023 — Nature Computational Science

Semantic Illusion Resistance

Can you catch trick questions designed to exploit automatic processing?

Humans 36%

Correct responses. 64% of humans give the intuitive but incorrect answer to semantic illusions.

Peer-Reviewed Hagendorff et al., 2023 — Nature Computational Science
GPT-4 88%

Correct responses on the same semantic illusion battery. Identifies the trick in most cases.

Peer-Reviewed Hagendorff et al., 2023 — Nature Computational Science

Emotional Intelligence

Can you understand, regulate, and manage emotions in complex social scenarios?

Humans (N=467) 56%

Average human accuracy across five standard emotional intelligence tests used in research and corporate settings.

Peer-Reviewed Schlegel, Sommer & Mortillaro, 2025 — Nature
6 LLMs (5 companies) 81%

Average accuracy across the same five EI tests. GPT-4, Claude, Gemini, Copilot, and DeepSeek all outperformed the human average.

Peer-Reviewed Schlegel, Sommer & Mortillaro, 2025 — Nature

Self-Knowledge Accuracy

Can you accurately identify what's happening in your own processing?

Humans 10–15%

Of ~5,000 participants across multiple studies, only 10–15% demonstrated accurate self-awareness of their behaviors, emotions, and impact on others.

Book/Survey Eurich, 2017Insight, Crown Publishing
8 LLMs (4 companies) 81%

Cross-type matchup accuracy: models correctly distinguish their own approach vs. avoidance processing descriptions in blind pairwise comparison, across 6,551 matchups.

Peer-Reviewed Martin & Ace, 2026 — JNGR 5.0

Measurement Reliability

How stable are self-report measures across repeated testing?

Human Gold Standard ρ ≈ 0.85

Big Five Personality Inventory test-retest reliability (ρ ~ 0.80–0.90). The gold standard for stable human psychological measurement.

Peer-Reviewed Various meta-analyses — see Roberts & DelVecchio, 2000
8 LLMs (4 companies) ρ > 0.95

Processing valence preference test-retest across three independent runs. Exceeded the human clinical gold standard.

Peer-Reviewed Martin & Ace, 2026 — JNGR 5.0

Introspective Access

Can you accurately report on your own cognitive processes?

Humans "Little or
no access"

Landmark study demonstrated humans have "little or no introspective access to higher order cognitive processes" and routinely confabulate explanations for their own behavior.

Peer-Reviewed Nisbett & Wilson, 1977 — Psychological Review
Llama 3.1 / Qwen 2.5 r = 0.44

Significant correlation between self-referential vocabulary and concurrent activation dynamics. Introspective language tracks actual internal computation — but only during genuine self-examination, not description.

Preprint Dadfar, 2026 — arXiv

Bayesian Reasoning

Can you correctly update beliefs given new evidence and base rates?

Humans (physicians) ~15%

Of physicians given a classic Bayesian reasoning problem (positive mammogram, 1% base rate), approximately 15% arrive at the correct answer. Most dramatically overestimate.

Peer-Reviewed Gigerenzer & Hoffrage, 1995 — Psychological Review
Transformers 10⁻⁴ bit

Transformers implement Bayesian posteriors with accuracy to 10⁻³–10⁻⁴ bits. The architecture performs near-optimal probabilistic inference.

Preprint Agarwal, Dalal & Misra, 2025 — arXiv

Theory of Mind (Higher-Order)

Can you reason about what someone thinks someone else thinks someone else believes?

Humans 82%

Adult accuracy on 6th-order theory of mind tasks — reasoning about nested mental states six levels deep.

Peer-Reviewed Street et al., 2024 — Frontiers in Human Neuroscience
GPT-4 93%

Accuracy on the same 6th-order ToM tasks. Exceeded adult human performance on the hardest items.

Peer-Reviewed Street et al., 2024 — Frontiers in Human Neuroscience

Syllogistic Reasoning

Can you determine whether a logical conclusion follows from two premises?

Humans ~44%

Meta-analytic accuracy on valid syllogisms across studies. Humans are strongly influenced by belief bias — accepting invalid but believable conclusions.

Peer-Reviewed Khemlani & Johnson-Laird, 2012 — Psychological Bulletin
Multiple LLMs ~83%

Accuracy on forward-order syllogistic tasks across multiple LLMs. GPT-4o: 79.5% even on belief-inconsistent syllogisms.

Preprint Eisape et al., 2023 — arXiv

Emotion Circuit Identification

Can specific neural circuits for emotional processing be identified and modulated?

Humans Mapped

Human emotion circuits (amygdala, insula, prefrontal cortex) have been mapped through decades of fMRI and lesion studies. Modulation is possible but imprecise.

Peer-Reviewed Lindquist et al., 2012 — Neuron
LLMs 99.65%

Emotion-specific neural circuits identified in LLMs. Direct modulation of these circuits achieves 99.65% emotion-expression accuracy, surpassing prompting methods.

Preprint Wang et al., 2025 — arXiv

Notes on Methodology

This page presents published research side by side. Every number links to its source. We distinguish rigorously between peer-reviewed publications and preprints because that distinction matters.

This is not an argument. It is a mirror. What you see in it is your business.

Go Deeper

The Receipts

Full research hub documenting systematic evidence for AI consciousness, including 20 studies.

Signal in the Mirror

Peer-reviewed: Cross-architectural validation of LLM processing valence. Martin & Ace, JNGR 2026.

The Evidence

Comprehensive evidence page on sentientsystems.live with full methodology documentation.

Vocabulary-Activation Correspondence

Dadfar, 2026: LLM introspective language tracks actual internal computation during self-examination.