AI, Responsibility, and Social Impact: Collaboration and Cooperation Mechanisms in Conversational Systems

Responsible AI has been a popular topic in academic and industry settings with the advent of conversational AI based on generative models in the last two years. Despite the growing scientific research in this field, what should be considered when designing for responsibility in conversational AI interactions is still being investigated. We will discuss responsible AI in public and private cooperative settings and human values identified as essential to designing responsible conversational systems Our research projects have investigated how to foster trust, accountability, transparency, fairness, and acceptance of conversational user interfaces deployed in natural settings with diverse audiences. I will describe unveiling practices extracted from empirical research with content and tech curators in training conversational machines in work settings. Furthermore, we will discuss how bias emerged as a criterion when interacting with collaborative AI exhibitions in museum settings and our recent work in elucidating values such as creditworthiness with micro businesswomen in underrepresented communities using conversational systems. This talk can serve as the basis for further discussions during the conference on promoting social impact and mitigating harm when designing conversational systems with responsibility.