The Complex Systems View of AI Ethics- Prof. Tina Eliassi-Rad

Join us for the Data Sciences Speaker Series with Prof. Tina Eliassi-Rad is the inaugural President Joseph E. Aoun Professor at Northeastern University.  This talk is co-sponsored by the Data Sciences Institute and the Centre for Analytics and Artificial Intelligence Engineering (CARTE), University of Toronto.

Registration Required – REGISTER HERE 

  • Date: January 22, 2024
  • Time: 11:00 a.m. – 12:00 p.m.
  • Format: In-person
  • Location: Data Sciences Institute, 10th floor Seminar Room, 700 University Avenue, Toronto 

Talk Title: 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 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.


Tina Eliassi-Rad is the inaugural President Joesph E. Aoun Professor at Northeastern University. She is also a core faculty member at Northeastern’s Network Science Institute and the Institute for Experiential AI. In addition, she is an external faculty member at the Santa Fe Institute and the Vermont Complex Systems Center. Prior to joining Northeastern, Tina was an Associate Professor of Computer Science at Rutgers University; and before that she was a member of technical staff and principal investigator at Lawrence Livermore National Laboratory. Tina earned her Ph.D. in Computer Sciences (with a minor in Mathematical Statistics) at the University of Wisconsin-Madison. Her research is at the intersection of data mining, machine learning, and network science. She has over 150 peer-reviewed publications (including a few best paper and best paper runner-up awards); and has given over 250 invited talks and 14 tutorials. Tina’s work has been applied to personalized search on the World-Wide Web, statistical indices of large-scale scientific simulation data, fraud detection, mobile ad targeting, cyber situational awareness, drug discovery, democracy and online discourse, and ethics in machine learning. Her algorithms have been incorporated into systems used by governments and industry (e.g., IBM System G Graph Analytics), as well as open-source software (e.g., Stanford Network Analysis Project). Tina received an Outstanding Mentor Award from the U.S. Department of Energy’s Office of Science in 2010, became an ISI Foundation Fellow in 2019, was named one of the 100 Brilliant Women in AI Ethics in 2021, received Northeastern University’s Excellence in Research and Creative Activity Award in 2022, was awarded the Lagrange Prize-CRT Foundation in 2023, and was elected Fellow of the Network Science Society in 2023.

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Local Time

  • Timezone: America/New_York
  • Date: Jan 22 2024


10th floor, 700 University Avenue, Toronto