Creating Group Rules with AI: Human-AI Collaboration in WhatsApp Moderation

2026-05-12

AI Summary

This study addresses the lack of effective governance and moderation mechanisms in WhatsApp groups, which places a substantial burden on administrators responsible for rule creation and enforcement. Through a two-phase speculative design approach—integrating contextual probes, user interviews, and a prototype Meta AI chatbot—the research explores how AI can assist administrators in collaboratively formulating group rules and supporting content moderation. Findings indicate that while administrators recognize AI’s potential to alleviate workload and address rule blind spots, they remain highly sensitive to its handling of privacy, tone, and adaptation to social context. Moreover, current chat interfaces prove inadequate for efficient human-AI collaboration. The work further reveals how group type and administrative style influence willingness to delegate authority to AI, underscoring the critical roles of relational trust, contextual appropriateness, and collective governance in AI-assisted group moderation.

Abstract

WhatsApp is one of the most widely used messaging platforms globally, with billions of users sharing information in private groups. Yet, it offers little infrastructure to support moderation and group governance. In the absence of platform-level oversight, group admins bear the responsibility of governing group behavior. In this paper, we explore how WhatsApp group admins collaborate with AI tools to create, enforce, and maintain group rules. Drawing on a two-phase speculative design study with 20 admins in India, we examine how participants interacted with an AI assistant (Meta AI) to co-create rules and responded to a series of probes illustrating AI-assisted moderation features. Our findings show that while admins appreciated the AI's ability to surface overlooked rules and reduce their moderation burden, they were highly sensitive to issues of relational trust, data privacy, tone, and social context. We identify how group type and admin style shaped their willingness to delegate authority, and surface the limitations of current chatbot interfaces in supporting collaborative rule-making. We conclude with design implications for building moderation tools that center human judgment, relational nuance, contextual adaptability, and collective governance.

Problem

• WhatsApp moderation
• group governance
• AI collaboration
• content moderation
• relational trust

Innovation

• human-AI collaboration
• group moderation
• speculative design
• relational trust
• contextual adaptability