Social Influence in Conversations

Persuasion for Social Good: How to Build and Break Chatbots

Persuasion is important in numerous situations like healthy habit promotion, and emotional support. As AI gets more involved in our daily life, it becomes critical to study how they can persuade humans and how persuasive they are. In this talk, I will cover (1) how to build such persuasive AI systems that can persuade, negotiate, and cooperate with other humans in the game of Diplomacy. (2) I will also discuss how humans perceive such specialized AI systems. This study validates the necessity of California's Autobot Law and proposes guidance to regulate such systems. (3) As these systems become more powerful, AI safety problems become more important. So I will describe how to persuade AI models to jailbreak them and study AI safety problems. Finally, I will conclude with my long-term vision to further study persuasion from a multi-angle approach that combines Artificial Intelligence, Human-Computer Interaction, and social sciences.

Bio: Weiyan Shi is an assistant professor at Northeastern University. Her research interests are persuasive dialogue systems, and AI safety. She is recognized as MIT Technology Review 35 Innovators under 35, Rising Star in Machine Learning and Rising Star in EECS. She has received a Best Social Impact Paper, an Outstanding Paper, and a Best Paper Nomination for her work on persuasive dialogues at ACL 2019 and ACL 2024. She was also a core team member behind a Science publication on the first negotiation AI agent, Cicero, that achieved a human level in the game of Diplomacy. This work has been featured in The New York Times, The Washington Post, MIT Technology Review, Forbes, and other major media outlets.

Meta-Cultural Competence: What LLMs Should Know About Culture to Be Good Conversationalists

Anthropologist Dan Sperber once remarked that “culture is the precipitate of cognition and communication within a human population.” Culture, in this sense, both shapes and is shaped by the flow of conversation. For conversational AI systems to truly engage users meaningfully, they must be capable of interpreting the user's perspective—something that inherently involves cultural understanding.

Yet culture is notoriously hard to pin down: it resists fixed definitions and defies any quatification. In this talk, I propose a  computational framework for meta-cultural competence —one that treats cultural knowledge not as static content but as a dynamic prior. This prior informs conversational interpretation and generation, while being continuously refined through mechanisms of explication (surfacing implicit norms or values) and negotiation (adapting meaning in interaction). The goal is to move toward systems that are not just culturally sensitive, but culturally responsive—capable of evolving alongside the user’s own communicative context.

Bio: Monojit Choudhury is a professor of Natural Language Processing at Mohommed Bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi. Prior to this, he was a principal scientist at Microsoft Research India and Microsoft Turing. Prof Choudhury's research interests lie in the intersection of NLP, Social and Cultural aspects of Technology use, and Ethics. In particular, he has been working on multilingual and multicultural aspects of large language models (LLMs), their use in low resource languages and making LLMs more inclusive and safer. Prof Choudhury takes a keen interest in popularizing linguistics and AI through puzzle solving; he is the general chair of Indian national linguistics Olympiad, the founding co-chair of Asia-Pacific linguistics Olympiad, and a founding board-member of International AI Olympiad. He holds a BTech and PhD degree in Computer Science and Engineering from IIT Kharagpur.