The IV AMMCS International Conference
Waterloo, Ontario, Canada | August 20-25, 2017
AMMSCS 2017 Plenary Talk
Moral Artificial Intelligence and the Societal Tradeoffs Problem
Vincent Conitzer (Duke University)
AI systems increasingly need to make decisions with a moral component.
Should a self-driving car prioritize the safety of its passengers over
that of others, and to what extent? Should an algorithm that decides
which donors and patients to match in a kidney exchange take features
such as the patient's age into account, and to what extent? I will
briefly discuss two approaches to these problems: extending
game-theoretic frameworks, and learning from examples of human
decisions.
Under the second approach, we will generally find that not all humans agree! How, then, should we aggregate their judgments to make coherent decisions? This is a problem in computational social choice. I will present our work on the societal tradeoffs problem in which, based on multiple human judgments, we aim to find a specific value for x in statements such as using one gallon of gasoline is as bad as creating x bags of landfill trash.
The first part is joint work with Walter Sinnott-Armstrong, Jana Schaich Borg, Yuan Deng, and Max Kramer, and the second part with Rupert Freeman, Markus Brill, and Yuqian Li.)
Under the second approach, we will generally find that not all humans agree! How, then, should we aggregate their judgments to make coherent decisions? This is a problem in computational social choice. I will present our work on the societal tradeoffs problem in which, based on multiple human judgments, we aim to find a specific value for x in statements such as using one gallon of gasoline is as bad as creating x bags of landfill trash.
The first part is joint work with Walter Sinnott-Armstrong, Jana Schaich Borg, Yuan Deng, and Max Kramer, and the second part with Rupert Freeman, Markus Brill, and Yuqian Li.)
Vincent Conitzer is the Kimberly J. Jenkins University Professor of
New Technologies and Professor of Computer Science, Professor of
Economics, and Professor of Philosophy at Duke University. He received
Ph.D. (2006) and M.S. (2003) degrees in Computer Science from Carnegie
Mellon University, and an A.B. (2001) degree in Applied Mathematics
from Harvard University. Most of his research is on artificial
intelligence (especially multiagent systems) and economic theory
(especially game theory, social choice, and mechanism design).
Conitzer has received the Social Choice and Welfare Prize, a
Presidential Early Career Award for Scientists and Engineers (PECASE),
the IJCAI Computers and Thought Award, an NSF CAREER award, the
inaugural Victor Lesser dissertation award, an honorable mention for
the ACM dissertation award, and several awards for papers and service
at the AAAI and AAMAS conferences. He has also been named a Guggenheim
Fellow, a Kavli Fellow, a Bass Fellow, a Sloan Fellow, and one of AI's
Ten to Watch. Conitzer and Preston McAfee are the founding
Editors-in-Chief of the ACM Transactions on Economics and Computation
(TEAC).