AIの新たな説得力:あなたの心を変えることができる(AI’s new power of persuasion: it can change your mind)


2024-04-15 スイス連邦工科大学ローザンヌ校(EPFL)



大規模言語モデルの会話による説得力について: 無作為化比較試験 On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

Francesco Salvi, Manoel Horta Ribeiro, Riccardo Gallotti, Robert West
arXiv  Submitted on:21 Mar 2024


The development and popularization of large language models (LLMs) have raised concerns that they will be used to create tailor-made, convincing arguments to push false or misleading narratives online. Early work has found that language models can generate content perceived as at least on par and often more persuasive than human-written messages. However, there is still limited knowledge about LLMs’ persuasive capabilities in direct conversations with human counterparts and how personalization can improve their performance. In this pre-registered study, we analyze the effect of AI-driven persuasion in a controlled, harmless setting. We create a web-based platform where participants engage in short, multiple-round debates with a live opponent. Each participant is randomly assigned to one of four treatment conditions, corresponding to a two-by-two factorial design: (1) Games are either played between two humans or between a human and an LLM; (2) Personalization might or might not be enabled, granting one of the two players access to basic sociodemographic information about their opponent. We found that participants who debated GPT-4 with access to their personal information had 81.7% (p < 0.01; N=820 unique participants) higher odds of increased agreement with their opponents compared to participants who debated humans. Without personalization, GPT-4 still outperforms humans, but the effect is lower and statistically non-significant (p=0.31). Overall, our results suggest that concerns around personalization are meaningful and have important implications for the governance of social media and the design of new online environments.