The World is a Multi-Objective Multi-Agent System: Now What?

Most complex problems of social relevance, such as climate change mitigation, traffic management, taxation policy design, or infrastructure management, involve both multiple stakeholders and multiple potentially conflicting objectives. In a nutshell, the majority of real world problems are multi-agent and multi-objective in nature. Artificial intelligence (AI) is a pivotal tool in designing solutions for such critical domains that come with high impact and ramifications across many dimensions, from societal and economic well-being, to ethical, political, and legal levels. Given the current theoretical and algorithmic developments in AI, it is an opportune moment to take a holistic approach and design decision-support tools that: (i) tackle all the prominent challenges of such problems and consider both the multi-agent and multi-objective aspects; (ii) exhibit vital characteristics, such as explainability and transparency, in order to enhance user agency and alignment. These are the challenges that I will discuss during the Frontiers in AI session at ECAI 2024, together with a brief overview of my work and next steps for this field. This paper summarises my contribution to the session.