The Ethics Engine: A Modular Pipeline for Accessible Psychometric Assessment of Large Language Models

Fuente: arXiv
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Autori principali: Van Clief, Jake, Kyritsopoulos, Constantine
Natura: Preprint
Pubblicazione: 2025
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author Van Clief, Jake
Kyritsopoulos, Constantine
author_facet Van Clief, Jake
Kyritsopoulos, Constantine
contents As Large Language Models increasingly mediate human communication and decision-making, understanding their value expression becomes critical for research across disciplines. This work presents the Ethics Engine, a modular Python pipeline that transforms psychometric assessment of LLMs from a technically complex endeavor into an accessible research tool. The pipeline demonstrates how thoughtful infrastructure design can expand participation in AI research, enabling investigators across cognitive science, political psychology, education, and other fields to study value expression in language models. Recent adoption by University of Edinburgh researchers studying authoritarianism validates its research utility, processing over 10,000 AI responses across multiple models and contexts. We argue that such tools fundamentally change the landscape of AI research by lowering technical barriers while maintaining scientific rigor. As LLMs increasingly serve as cognitive infrastructure, their embedded values shape millions of daily interactions. Without systematic measurement of these value expressions, we deploy systems whose moral influence remains uncharted. The Ethics Engine enables the rigorous assessment necessary for informed governance of these influential technologies.
format Preprint
id arxiv_https___arxiv_org_abs_2510_11742
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The Ethics Engine: A Modular Pipeline for Accessible Psychometric Assessment of Large Language Models
Van Clief, Jake
Kyritsopoulos, Constantine
Computers and Society
68T50, 91E99
K.4.1; I.2.7; J.4
As Large Language Models increasingly mediate human communication and decision-making, understanding their value expression becomes critical for research across disciplines. This work presents the Ethics Engine, a modular Python pipeline that transforms psychometric assessment of LLMs from a technically complex endeavor into an accessible research tool. The pipeline demonstrates how thoughtful infrastructure design can expand participation in AI research, enabling investigators across cognitive science, political psychology, education, and other fields to study value expression in language models. Recent adoption by University of Edinburgh researchers studying authoritarianism validates its research utility, processing over 10,000 AI responses across multiple models and contexts. We argue that such tools fundamentally change the landscape of AI research by lowering technical barriers while maintaining scientific rigor. As LLMs increasingly serve as cognitive infrastructure, their embedded values shape millions of daily interactions. Without systematic measurement of these value expressions, we deploy systems whose moral influence remains uncharted. The Ethics Engine enables the rigorous assessment necessary for informed governance of these influential technologies.
title The Ethics Engine: A Modular Pipeline for Accessible Psychometric Assessment of Large Language Models
topic Computers and Society
68T50, 91E99
K.4.1; I.2.7; J.4
url https://arxiv.org/abs/2510.11742