Introducing AI to an Online Petition Platform Changed Outputs but not Outcomes

2025-11-17

AI Summary

This study investigates how integrating AI writing tools into online petition platforms affects users’ content generation patterns and advocacy outcomes. Leveraging a natural experiment based on 1.5 million petitions, we employ a difference-in-differences (DID) design alongside longitudinal analysis of repeat petitioners. Results show that AI assistance significantly alters linguistic features—reducing lexical diversity and increasing syntactic homogeneity—thereby exacerbating content homogenization. Yet, petition success rates remain unchanged, indicating limited real-world advocacy impact. To our knowledge, this is the first large-scale, causal evaluation of AI-augmented writing in authentic civic advocacy contexts. It reveals a critical disconnect between technological capability and tangible societal efficacy, offering empirically grounded insights for platform-level AI governance and the human-centered design of participatory technologies.

Technology Category

• Humans and AI: Voting
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy
• Application Domains: Humanities & Computational Social Science

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

The rapid integration of AI writing tools into online platforms raises critical questions about their impact on content production and outcomes. We leverage a unique natural experiment on Change.org, a leading social advocacy platform, to causally investigate the effects of an in-platform ''write with AI'' tool. To understand the impact of the AI integration, we collected 1.5 million petitions and employed a difference-in-differences analysis. Our findings reveal that in-platform AI access significantly altered the lexical features of petitions and increased petition homogeneity, but did not improve petition outcomes. We confirmed the results in a separate analysis of repeat petition writers who wrote petitions before and after introduction of the AI tool. The results suggest that while AI writing tools can profoundly reshape online content, their practical utility for improving desired outcomes may be less beneficial than anticipated, and introduce unintended consequences like content homogenization.

Problem

• AI writing tools altered petition lexical features but not outcomes
• AI integration increased content homogeneity without improving petition success
• AI tools reshape online content but provide limited practical utility

Innovation

• AI tool altered petition lexical features
• AI increased petition content homogeneity
• AI did not improve petition outcomes