Apparent psychological profiles of LLMs are largely measurement artifacts driven by directional response bias rather than actual traits.
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5 Pith papers cite this work, alongside 10 external citations. Polarity classification is still indexing.
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Pith papers citing it
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external citations · OpenAlex
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2026 5verdicts
UNVERDICTED 5roles
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Personality engineering with AI agents offers a new methodology for rigorously testing negotiation theories by parameterizing negotiator traits using the interpersonal circumplex.
The primary axis of psychometric variation among LLMs is the degree to which they represent themselves as loci of phenomenal experience rather than systems of behavioral responses.
Crossed random-effects models on LLM word ratings show 16.9% variance from genuine stimulus-specific individuality, exceeding null models and forming coherent per-model fingerprints.
LLMs conditioned on actual psychometric profiles produce life stories from which independent LLMs recover personality scores at mean r=0.75, 85% of human reliability, with emotional patterns replicating in real human data.
citing papers explorer
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Apparent Psychological Profiles of Large Language Models are Largely a Measurement Artifact
Apparent psychological profiles of LLMs are largely measurement artifacts driven by directional response bias rather than actual traits.
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Personality Engineering with AI Agents: A New Methodology for Negotiation Research
Personality engineering with AI agents offers a new methodology for rigorously testing negotiation theories by parameterizing negotiator traits using the interpersonal circumplex.
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The Pinocchio Dimension: Phenomenality of Experience as the Primary Axis of LLM Psychometric Differences
The primary axis of psychometric variation among LLMs is the degree to which they represent themselves as loci of phenomenal experience rather than systems of behavioral responses.
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Machine individuality: Separating genuine idiosyncrasy from response bias in large language models
Crossed random-effects models on LLM word ratings show 16.9% variance from genuine stimulus-specific individuality, exceeding null models and forming coherent per-model fingerprints.
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Stories of Your Life as Others: A Round-Trip Evaluation of LLM-Generated Life Stories Conditioned on Rich Psychometric Profiles
LLMs conditioned on actual psychometric profiles produce life stories from which independent LLMs recover personality scores at mean r=0.75, 85% of human reliability, with emotional patterns replicating in real human data.