Durably reducing conspiracy beliefs through dialogues with AI

• 成果类型: Article
• 署名作者: Costello, Thomas H.; Pennycook, Gordon; Rand, David G.
• 署名单位: Massachusetts Institute of Technology (MIT); American University; Cornell University
• 刊物名称: SCIENCE
• ISSN/ISSBN: 0036-12438
• DOI: 10.1126/science.adq1814
• 发表日期: 2024-09-13
• 页码: 1183-+
• 关键词: impact

摘要

Conspiracy theory beliefs are notoriously persistent. Influential hypotheses propose that they fulfill important psychological needs, thus resisting counterevidence. Yet previous failures in correcting conspiracy beliefs may be due to counterevidence being insufficiently compelling and tailored. To evaluate this possibility, we leveraged developments in generative artificial intelligence and engaged 2190 conspiracy believers in personalized evidence-based dialogues with GPT-4 Turbo. The intervention reduced conspiracy belief by similar to 20%. The effect remained 2 months later, generalized across a wide range of conspiracy theories, and occurred even among participants with deeply entrenched beliefs. Although the dialogues focused on a single conspiracy, they nonetheless diminished belief in unrelated conspiracies and shifted conspiracy-related behavioral intentions. These findings suggest that many conspiracy theory believers can revise their views if presented with sufficiently compelling evidence.