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Approaches to Understanding AI
Yoshua Bengio · Roel Dobbe · Madeleine Elish · Joshua Kroll · Jacob Metcalf · Jack Poulson

Fri Dec 13 08:45 AM -- 09:45 AM (PST) @
in Minding the Gap: Between Fairness and Ethics »

The stakes of AI certainly alter how we relate to each other as humans - how we know what we know about reality, how we communicate, how we work and earn money, and about how we think of ourselves as human. But in grappling with these changing relations, three fairly concrete approaches have dominated the conversation: ethics, fairness, and safety. These approaches come from very different academic backgrounds, draw attention to very different aspects of AI, and imagine very different problems and solutions as relevant, leading us to ask: • What are the commonalities and differences between ethics, fairness, and safety as approaches to addressing the challenges of AI? • How do these approaches imagine different problems and solutions for the challenges posed by AI? • How can these approaches work together, or are there some areas where they are mutually incompatible?

Author Information

Yoshua Bengio (Mila)

Yoshua Bengio is Full Professor in the computer science and operations research department at U. Montreal, scientific director and founder of Mila and of IVADO, Turing Award 2018 recipient, Canada Research Chair in Statistical Learning Algorithms, as well as a Canada AI CIFAR Chair. He pioneered deep learning and has been getting the most citations per day in 2018 among all computer scientists, worldwide. He is an officer of the Order of Canada, member of the Royal Society of Canada, was awarded the Killam Prize, the Marie-Victorin Prize and the Radio-Canada Scientist of the year in 2017, and he is a member of the NeurIPS advisory board and co-founder of the ICLR conference, as well as program director of the CIFAR program on Learning in Machines and Brains. His goal is to contribute to uncover the principles giving rise to intelligence through learning, as well as favour the development of AI for the benefit of all.

Roel Dobbe (AI Now Institute, New York University)

Roel Dobbe’s research addresses the development, analysis, integration and governance of data-driven systems. His PhD work combined optimization, machine learning and control theory to enable monitoring and control of safety-critical systems, including energy & power systems and cancer diagnosis and treatment. In addition to research, Roel has experience in industry and public institutions, where he has served as a management consultant for AT Kearney, a data scientist for C3 IoT, and a researcher for the National ThinkTank in The Netherlands. His diverse background led him to examine the ways in which values and stakeholder perspectives are represented in the process of designing and deploying AI and algorithmic decision-making and control systems. Roel is passionate about developing practices to help engineers and computer scientists engage more closely both with impacted communities and scholars in the social sciences, and to better contend with serious questions of ethics and governance. Towards this end, Roel founded Graduates for Engaged and Extended Scholarship around Computing & Engineering (GEESE); a student organization stimulating graduate students across all disciplines studying or developing technologies to take a broader lens at their field of study and engage across disciplines.

Madeleine Elish (Data & Society)
Joshua Kroll (Naval Postgraduate School)
Jacob Metcalf (Data & Society)
Jack Poulson (Tech Inquiry)

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