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

Jul 16, 2026

WhatsApp users rely on group admins to govern behavior, because encrypted messaging limits platform oversight and rule infrastructure. The study examines how 20 admins in India collaborate with Meta AI to co-create, enforce, and maintain group rules through a two-phase speculative design process. Results show admins value AI-supported rule discovery and workload reduction, while remaining highly sensitive to relational trust, privacy, tone, and social context. Design implications emphasize human judgment and contextual, collective governance.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages29

Reading Time1 h 13 min

Introduction

Research Questions and Study Overview

Key Findings and Implications

arXiv :2605 . 12613v4 [ cs .HC] 12 Jul 2026 Creating Group Rules with AI: Human-AI Collaboration in WhatsApp Moderation GAURI NAYAK, Cornell University, USA FARHANA SHAHID, Cornell University, USA KIRAN GARIMELLA, Rutgers University, USA ADITYA VASHISTHA, Cornell University, USA 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. CCS Concepts: • Human-centered computing → Empirical studies in collaborative and social computing; Empirical studies in HCI ; Collaborative and social computing systems and tools. Additional Key Words and Phrases: WhatsApp, Content Moderation, Human-AI Collaboration, AI-Assisted Moderation, Group Governance ACM Reference Format: Gauri Nayak, Farhana Shahid, Kiran Garimella, and Aditya Vashistha. 2026. Creating Group Rules with AI: Human-AI Collaboration in WhatsApp Moderation. Proc. ACM Hum.-Comput. Interact. 10, 6, Article CSCW067 (October 2026), 29 pages. [https://doi.org/10.1145/3816915](https://doi.org/10.1145/3816915) 1 Introduction WhatsApp is the most widely used encrypted messaging platform, where billions of global users share information in unregulated groups [5, 34] . Due to end-to-end encryption, WhatsApp has limited visibility into the content circulating in groups. This places the responsibility of moderation on group admins who are often users who created these groups and informally manage them [46] . Prior research shows that in formal WhatsApp groups—such as those for work or study—admins tend to actively enforce rules to prevent unwanted content [46, 54] . In contrast, admins of public or close-knit groups (e.g., family and friends) typically avoid moderation, either due to established social hierarchies or the overwhelming volume of problematic content [35, 37, 46] . While the presence of group rules can promote responsible behavior among members [13, 36], most platforms, including WhatsApp, offer little to no infrastructure for rule creation or enforcement [46, 57] . Although platforms such as Reddit and Twitch have long used automated moderation tools, they Authors’ Contact Information: Gauri Nayak, Cornell University, Ithaca, New York, USA, [gsn33@cornell.edu](gsn33@cornell.edu); Farhana Shahid, Cornell University, Ithaca, New York, USA, [fs468@cornell.edu](fs468@cornell.edu); Kiran Garimella, Rutgers University, New Brunswick, New Jersey, USA, [kiran.garimella@rutgers.edu](kiran.garimella@rutgers.edu); Aditya Vashistha, Cornell University, Ithaca, New York, USA, [adityav@cornell.edu](adityav@cornell.edu). This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4 .0 International License.© 2026 Copyright held by the owner/author(s) . ACM 2573-0142/2026/10-ARTCSCW067 [https://doi.org/10.1145/3816915](https://doi.org/10.1145

FAQs

Why is moderation and rule governance challenging in WhatsApp groups?

WhatsApp provides little infrastructure for rule creation or enforcement, and end-to-end encryption limits visibility into group content, so admins must govern behavior themselves.

How did the study investigate AI-assisted rule creation and enforcement?

Researchers ran a two-phase speculative design study with 20 admins in India, using the Meta AI chatbot to co-create rules in phase 1 and design probes to explore AI-assisted moderation features in phase 2.

What benefits and concerns did admins report when using AI for moderation?

Admins appreciated AI’s ability to surface overlooked rules and reduce moderation burden, but were highly sensitive to relational trust, data privacy, tone, and the social context of the group.

Jul 16, 2026

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