Dhruv Agarwal

schoolCornell Universitybar_chart#2626 Global Rank

Total Papers

HCI Rank

#2626

Research Areas

Years Active

Recent Publications

'One Style Does Not Regulate All': Moderation Practices in Public and Private WhatsApp Groups

WhatsApp is the largest social media platform in the Global South and is a virulent force in global misinformation and political propaganda. Due to end-to-end encryption WhatsApp can barely review any content and mostly rely on volunteer moderation by group admins. Yet, little is known about how WhatsApp group admins…

CSCW '252nd AuthorCommunicating With/Through AI

Steering AI-driven Personalization of Scientific Text for General Audiences

Digital media platforms (e.g., science blogs) offer opportunities to communicate scientific content to general audiences at scale. However, these audiences vary in their scientific expertise, literacy levels, and personal backgrounds, making effective science communication challenging. To address this challenge, we de…

CHI '251st AuthorMultilingual & Cross-Cultural Voice Interaction +2

AI Suggestions Homogenize Writing Toward Western Styles and Diminish Cultural Nuances

Large language models (LLMs) are being increasingly integrated into everyday products and services, such as coding tools and writing assistants. As these embedded AI applications are deployed globally, there is a growing concern that the AI models underlying these applications prioritize Western values. This paper inv…

CSCW '241st AuthorSession 3f: Conversations with Machines

Conversational Agents to Facilitate Deliberation on Harmful Content in WhatsApp Groups

WhatsApp groups have become a hotbed for the propagation of harmful content including misinformation, hate speech, polarizing content, and rumors, especially in Global South countries. Given the platform's end-to-end encryption, moderation responsibilities lie on group admins and members, who rarely contest such conte…

CSCW '242nd AuthorSession 3e: Trust and Understanding in Explainable AI

“If it is easy to understand then it will have value”: Examining Perceptions of Explainable AI with Community Health Workers in Rural India

AI-driven tools are increasingly deployed to support low-skilled community health workers (CHWs) in hard-to-reach communities in the Global South. This paper examines how CHWs in rural India engage with and perceive AI explanations and how we might design explainable AI (XAI) interfaces that are more understandable to…

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