Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Arlinghaus, Clarissa Sabrina, Kenneweg, Tristan, Hammer, Barbara, Maier, Günter W.
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2510.26481
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866909878477389824
author Arlinghaus, Clarissa Sabrina
Kenneweg, Tristan
Hammer, Barbara
Maier, Günter W.
author_facet Arlinghaus, Clarissa Sabrina
Kenneweg, Tristan
Hammer, Barbara
Maier, Günter W.
contents Large language models (LLMs) such as ChatGPT are increasingly integrated into high-stakes decision-making, yet little is known about their susceptibility to social influence. We conducted three preregistered conformity experiments with GPT-4o in a hiring context. In a baseline study, GPT consistently favored the same candidate (Profile C), reported moderate expertise (M = 3.01) and high certainty (M = 3.89), and rarely changed its choice. In Study 1 (GPT + 8), GPT faced unanimous opposition from eight simulated partners and almost always conformed (99.9%), reporting lower certainty and significantly elevated self-reported informational and normative conformity (p < .001). In Study 2 (GPT + 1), GPT interacted with a single partner and still conformed in 40.2% of disagreement trials, reporting less certainty and more normative conformity. Across studies, results demonstrate that GPT does not act as an independent observer but adapts to perceived social consensus. These findings highlight risks of treating LLMs as neutral decision aids and underline the need to elicit AI judgments prior to exposing them to human opinions.
format Preprint
id arxiv_https___arxiv_org_abs_2510_26481
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Who Has The Final Say? Conformity Dynamics in ChatGPT's Selections
Arlinghaus, Clarissa Sabrina
Kenneweg, Tristan
Hammer, Barbara
Maier, Günter W.
Artificial Intelligence
Large language models (LLMs) such as ChatGPT are increasingly integrated into high-stakes decision-making, yet little is known about their susceptibility to social influence. We conducted three preregistered conformity experiments with GPT-4o in a hiring context. In a baseline study, GPT consistently favored the same candidate (Profile C), reported moderate expertise (M = 3.01) and high certainty (M = 3.89), and rarely changed its choice. In Study 1 (GPT + 8), GPT faced unanimous opposition from eight simulated partners and almost always conformed (99.9%), reporting lower certainty and significantly elevated self-reported informational and normative conformity (p < .001). In Study 2 (GPT + 1), GPT interacted with a single partner and still conformed in 40.2% of disagreement trials, reporting less certainty and more normative conformity. Across studies, results demonstrate that GPT does not act as an independent observer but adapts to perceived social consensus. These findings highlight risks of treating LLMs as neutral decision aids and underline the need to elicit AI judgments prior to exposing them to human opinions.
title Who Has The Final Say? Conformity Dynamics in ChatGPT's Selections
topic Artificial Intelligence
url https://arxiv.org/abs/2510.26481