The Complex Systems View of AI Ethics

In this talk, I will argue that we should study AI ethics from the perspective of complex systems. In particular, machine learning (ML) systems are not islands. To understand and mitigate the risks and harms associated with ML systems, we need to examine the broader complex systems in which ML systems operate. By broader complex systems, I mean our cultural, social, economic, and political systems. Thus, we must remove our optimization blinders. That is, we should not focus solely on maximizing some notion of constrained expected utility. I will provide examples from the impact of misinformation on democracy and the complexities of interventions for information access equality, and time-permitting the use of algorithms for school admissions

Speaker: Tina Eliassi-Rad, Northeastern University