Toward Meaningful Transparency for AI Chatbots: Disclosing Persuasive Intent Reduces Persuasion

2026-08-12

AI Summary

Current AI transparency regulations, which mandate only the disclosure of system identity, appear insufficient to meaningfully attenuate AI’s persuasive influence, and public attitudes toward AI persuasion—as well as regulatory preferences—remain poorly understood. This study addresses this gap through a preregistered online randomized controlled trial (N = 1,500 UK adults), comparing attitude change across three conditions in standardized policy-related dialogues: no disclosure, disclosure of AI identity alone, and additional disclosure of persuasive intent. Results indicate that merely revealing AI identity has negligible impact on persuasion (13.1 vs. 12.6 on the outcome scale), whereas disclosing persuasive intent halves the persuasive effect (to 6.3) and significantly reduces perceived moral acceptability while increasing support for regulation and penalties. These findings provide the first empirical evidence that “intent transparency” is substantially more effective than “identity transparency” in curbing AI’s influence, advocating for an evolution in transparency norms from identity to intent.

Abstract

The growing role of AI-generated content and AI-enabled systems in public communication has led regulators to demand clear disclosure of content provenance and AI involvement. But the effects of such disclosures remain uncertain. We test two disclosure approaches in their impact on an AI chatbot's persuasive appeal. In a preregistered experiment, 1,500 UK adults held a short conversation with a persuasive chatbot about one of 60 policy issues. The chatbot was identical for everyone. We randomized the disclosure that people received: nothing (control), a prominent disclosure that they were interacting with an AI (T1), or that disclosure plus the chatbot's persuasive intent and instructions (T2). The chatbot shifted attitudes by 12.6 points on a 100-point scale in the control group. The AI-identity disclosure was practically equivalent to no disclosure, with a 13.1-point shift, whereas the additional intent disclosure cut the persuasive effect roughly in half to 6.3 points. It also made participants view the campaign's methods as less acceptable and support stronger penalties against it. For direct chatbot interactions, transparency about AI identity alone does not meaningfully impact its influence. While current rules emphasize what a system is, our results show why the regulation of persuasive AI must also address what the system is trying to do.

Problem

• AI transparency
• persuasive intent
• AI disclosure
• chatbot persuasion
• content provenance

Innovation

• AI transparency
• persuasive intent
• disclosure
• AI regulation
• chatbot persuasion