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Moral Decision Making Frameworks for Artificial Intelligence

Publication ,  Conference
Conitzer, V; Sinnott-Armstrong, W; Schaich Borg, J; Deng, Y; Kramer, M

The generality of decision and game theory has enabled domain-independent progress in AI research. For example, a better algorithm for finding good policies in (PO)MDPs can be instantly used in a variety of applications. But such a general theory is lacking when it comes to moral decision making. For AI applications with a moral component, are we then forced to build systems based on many ad-hoc rules? In this paper we discuss possible ways to avoid this conclusion.

Duke Scholars

Conference Name

Conference on Artificial Intelligence (AAAI-17)
 

Citation

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Conitzer, V., Sinnott-Armstrong, W., Schaich Borg, J., Deng, Y., & Kramer, M. (n.d.). Moral Decision Making Frameworks for Artificial Intelligence. Presented at the Conference on Artificial Intelligence (AAAI-17).
Conitzer, V., W. Sinnott-Armstrong, J. Schaich Borg, Y. Deng, and M. Kramer. “Moral Decision Making Frameworks for Artificial Intelligence,” n.d.
Conitzer V, Sinnott-Armstrong W, Schaich Borg J, Deng Y, Kramer M. Moral Decision Making Frameworks for Artificial Intelligence. In.
Conitzer V, Sinnott-Armstrong W, Schaich Borg J, Deng Y, Kramer M. Moral Decision Making Frameworks for Artificial Intelligence.

Conference Name

Conference on Artificial Intelligence (AAAI-17)