What question did this study set out to answer?

To develop and evaluate a psychometrically valid methodology for measuring, validating, and shaping synthetic personality traits in large language models.

July 1, 2023Open Access

Personality Traits in Large Language Models

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To develop and evaluate a psychometrically valid methodology for measuring, validating, and shaping synthetic personality traits in large language models.
Administered standardized psychometric personality tests across 18 widely-used large language models using specific prompting configurations.
Evaluated measurement reliability and validity across varying model sizes and instruction fine-tuning conditions, alongside prompt-based personality steering.
Personality measurements derived from model outputs were psychometrically reliable and valid under specific prompting configurations.
Larger and instruction fine-tuned models exhibited stronger reliability and construct validity compared to smaller baseline models.
Model outputs were successfully shaped along targeted personality dimensions to reproduce specific human personality profiles.

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Implication

Computational evaluation demonstrates reliable measurement and controllable shaping of personality traits across 18 large language models, highlighting pathways for tailored conversational AI.

Cite This Study

Serapio-Garcia et al. (2023) studied this question.

synapsesocial.com/papers/6a157c1c5347fbb1739fda06 https://doi.org/10.48550/arxiv.2307.00184

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Implication

Computational evaluation demonstrates reliable measurement and controllable shaping of personality traits across 18 large language models, highlighting pathways for tailored conversational AI.

Personality Traits in Large Language Models

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Discussion

Implication

Cite This Study

Personality Traits in Large Language Models

Key Points

Discussion

Implication

Cite This Study

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