Humans, Algorithmic Decision-Making and Society: Modeling Interactions and Impact

With the widespread adoption of machine learning in social technologies, there are increasingly complex interactions between humans, algorithmic decision-makers, and society at large. For instance, algorithmic decisions influence the information and opportunities that are available to individuals, the news they read, the job listings they are matched to, the credit lines they receive, and the social circle they form. On a macroscopic level, such decisions can therefore affect societal outcomes such as social mobility, mental health, polarization etc. At the same time, humans also influence algorithmic decision-makers, for instance, by expressing their preferences through observed behaviors which might be inconsistent or strategic. To understand long-term individual and societal outcomes resulting from these interactions, and to develop algorithms that mitigate undesired outcomes, it has therefore become increasingly important to model these complex interactions as a whole. The goal of this workshop is to bring together researchers from both academia and industry who work on modeling interactions between AI systems, humans, and society. We aim to cover a wide range of topics including both theory and practice. In particular, we encourage submissions on the following topics:- Feedback loops between human and algorithmic decisions, and their long-term impacts- Strategic behavior and its impact on algorithmic decision-making- Models for human utility/preferences in the presence of irrational behavior- Generative and foundation models for interpretable human behavior- Emergent social phenomena and complex systems- Modeling societal outcomes through multi-agent models, mean-field games, etc.- Fairness and algorithmic approaches to mitigate disparate impactWe will invite speakers and solicit contributed papers and posters covering the various facets of these interactions. We are targeting different communities/fields such as machine learning, network science, social systems, algorithmic game theory, economics. We expect that bringing these different communities together will result in exchange of ideas and stimulate open discussions about the current challenges and future directions.