Abstract: In virtually every domain (e.g., smart cities, smart multi-modal transportation, policy-making), one user's actions affect other users. AI systems that support or automate decision making affect not only their primary users but also others. AI agents of today tend to prioritise the preferences of a single user, typically the individual who initially configured the agent. Even when designed to represent the preferences of multiple stakeholders, these AI agents tend to optimise for the interests of their primary user. This approach carries inherent risks, as it can inadvertently reinforce existing privileges and potentially exacerbate disadvantages faced by vulnerable individuals and marginalised communities. There is a need to consider the broader societal implications of AI decision-making and ensure that AI systems promote fairness and equitable outcomes. In this talk, I will discuss how could we create multi-user-multi-agent systems that respect values and preferences of all users and promote prosociality and fairness.

Short Bio: Nirav Ajmeri is a Lecturer in Artificial Intelligence in the School of Computer Science at the University of Bristol. His research interests are in socially intelligent agents and multi-agent systems with an emphasis on ethics and privacy in socio-technical systems of humans, organisations, and software agents. He reviews for leading AI journals and conferences and speaks on AI, ethics, and socio-technical systems. He is the academic liaison for the UKRI Centre for Doctoral Training in Interactive Artificial Intelligence and a Co-I for the EPSRC Equitable Privacy project.