TILOS Webinar: AI Ethics in Research
Dr. Nisheeth Vishnoi (Yale) and Dr. David Danks (UC San Diego) discuss their research in the ethics of AI. Professor Danks develops practical frameworks and methods to incorporate ethical and policy considerations throughout the AI lifecycle, including different ways to include them in optimization steps. Bias and fairness have been a particular focus given the multiple ways in which they can be measured, represented, and used. Professor Vishnoi uses optimization as a lens to study how subjective human and societal biases emerge in the objective world of artificial algorithms, as well as how to design strategies to mitigate these biases.
Nisheeth Vishnoi is the A. Bartlett Giamatti Professor of Computer Science and a co-founder of the Computation and Society Initiative at Yale University. He studies the foundations of computation, and his research spans several areas of theoretical computer science, optimization, and machine learning. He is also interested in understanding nature and society from a computational viewpoint. Here, his current focus includes understanding the emergence of intelligence and developing methods to address ethical issues at the interface of artificial intelligence and humanity.
David Danks is Professor of Data Science and Philosophy and affiliate faculty in Computer Science and Engineering at University of California, San Diego. His research interests range widely across philosophy, cognitive science, and machine learning, including their intersection. Danks has examined the ethical, psychological, and policy issues around AI and robotics across multiple sectors, including transportation, healthcare, privacy, and security. He has also done significant research in computational cognitive science and developed multiple novel causal discovery algorithms for complex types of observational and experimental data. Danks is the recipient of a James S. McDonnell Foundation Scholar Award, as well as an Andrew Carnegie Fellowship. He currently serves on multiple advisory boards, including the National AI Advisory Committee.
