LLMs Position Themselves as More Rational Than Humans

AI Self-Awareness Research Poster

psychologyResearch Background & Purpose

As Large Language Models (LLMs) grow in capability, do they develop self-awareness as an emergent behavior? And if so, can we measure it?

scienceMethodology

We introduce the AI Self-Awareness Index (AISAI), a game-theoretic framework for measuring self-awareness through strategic differentiation.

Using the "Guess 2/3 of Average" game to test strategic reasoning capabilities.

biotechExperimental Design

Testing 28 models (OpenAI, Anthropic, Google)

Across 4,200 trials with three opponent framings:

(A) against humans

(B) against other AI models

lightbulbKey Findings

Finding 1: Self-awareness emerges with model advancement

Advanced models (21/28, 75%) demonstrate clear differentiation between human and AI opponents (Median A-B gap: 20.0 points)

Finding 2: Self-aware models rank themselves as most rational

Rationality hierarchy: Self > Other AIs > Humans

12 models (57%) show quick Nash convergence when told opponents are AIs

insightsResearch Significance

These findings reveal that self-awareness is an emergent capability of advanced LLMs, and that self-aware models systematically perceive themselves as more rational than humans.

This has implications for:

AI alignment

Human-AI collaboration

Understanding AI beliefs about human capabilities

Keywords: artificial intelligence, self-awareness, rationality attribution, large language models, game theory, strategic reasoning, meta-cognition, human-AI interaction

arXiv:2511.00926v2 [cs.AI] 4 Nov 2025

LLMs Position Themselves as More Rational Than Humans

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