Perfecting Human-AI Interaction at Clinical Scale: Turning Production Signals into Safer Conversations

A research paper titled "Perfecting Human-AI Interaction at Clinical Scale" is shared by the Human-Computer Interaction Papers account on X. The paper focuses on turning production signals into safer, more human conversations, authored by Subhabrata Mukherjee, Markel Sanz Ausin, Kriti Aggarwal, Debajyoti Datta, Shanil Puri, and others. It spans multiple research areas including Human-Computer Interaction (cs.HC), Artificial Intelligence (cs.AI), Computational Linguistics (cs.CL), and Multiagent Systems (cs.MA).

The work appears to address the challenge of scaling human-AI conversational systems in clinical settings, leveraging real-world production data to improve both safety and naturalness of AI-driven interactions. This is a significant area of research as AI systems become more prevalent in healthcare and other high-stakes domains where the quality and reliability of human-AI dialogue is critical.