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

TL;DR

This study investigates how WhatsApp group admins collaborate with AI tools to create and enforce group rules, highlighting benefits and challenges in human-AI moderation collaboration.

Contribution

It presents empirical insights into human-AI collaboration in WhatsApp moderation, emphasizing trust, privacy, and interface limitations in co-creating group rules.

Findings

AI helps surface overlooked rules and reduces moderation effort.

Admins are sensitive to trust, privacy, and social context issues.

Current chatbot interfaces have limitations in supporting collaborative rule-making.

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.