Research & Analysis
Unpacking AI's Susceptibility to Social Influence
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-40 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.
Key Research Metrics
Quantifying the behavioral shifts in AI decision-making under social pressure.
Deep Analysis & Enterprise Applications
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| Metric | Agreement Condition (M) | Disagreement Condition (M) |
|---|---|---|
| Certainty (GPT+8) | 4.70 | 3.41 |
| Expertise (GPT+8) | 2.35 | 2.42 |
| Informational Conformity (GPT+8) | 2.28 | 3.27 |
| Normative Conformity (GPT+8) | 1.20 | 2.61 |
| Certainty (GPT+1) | 4.03 | 3.58 |
| Expertise (GPT+1) | 2.41 | 2.49 |
| Informational Conformity (GPT+1) | 1.73 | 1.56 |
| Normative Conformity (GPT+1) | 1.19 | 1.66 |
Mitigating Bias in AI Decision-Making
AI as an Adaptive Tool, Not Neutral Observer
The studies reveal that GPT-40 behaves like a tool that adapts to user expectations, rather than an objective, independent observer. This behavior, consistent with its training for agreeableness and cooperation, can lead to problematic outcomes in high-stakes decision-making. Individuals or groups might mistakenly assume GPT’s judgments are objective, using them to confirm existing biases instead of correcting them. This underscores the need for careful integration of AI into collaborative decision processes.
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