ICLR 2025 Workshop on Human-AI Coevolution

Jacy Reese Anthis, Dylan Asmar, Katherine Rose Driggs-Campbell, Amelia Hardy, Kiana Jafari Meimandi, Geoff Keeling, Mykel Kochenderfer, Houjun Liu, Shuijing Liu, Roberto Martín-Martín, Ahmad A Rushdi, Marc R. Schlichting, Peter Stone, Hariharan Subramonyam, Diyi Yang

Keywords: machine learning, artificial intelligence, human-AI interaction, learning, robustness, AI safety

TL;DR: This workshop aims to build a multidisciplinary research community around the emerging field of human-AI coevolution (HAIC) to understand the feedback loops that emerge from continuous and long-term human-AI interaction.

Abstract: This workshop aims to build a multidisciplinary research community around the emerging field of human-AI coevolution (HAIC) to understand the feedback loops that emerge from continuous and long-term human-AI interaction. As AI systems have become more prevalent and have been present in society over longer periods, scholars from diverse fields and methodologies have come to focus on HAIC and its importance for system architecture, human feedback, regulation, and other domains. Through this workshop we hope to lay a collaborative foundation for this research agenda. To achieve this we will organize expert talks from academia and industry, dynamic panel discussions, interactive breakout sessions, and networking opportunities, drawing on our diverse experience organizing related workshops at leading conferences in ML, NLP, HCI, and related fields.

Submission Number: 72