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Moral decision making frameworks for artificial intelligence

Publication ,  Conference
Conitzer, V; Sinnott-Armstrong, W; Borg, JS; Deng, Y; Kramer, M
Published in: Aaai Workshop Technical Report
January 1, 2017

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

Published In

Aaai Workshop Technical Report

Publication Date

January 1, 2017

Volume

WS-17-01 - WS-17-15

Start / End Page

105 / 109
 

Citation

APA
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ICMJE
MLA
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Conitzer, V., Sinnott-Armstrong, W., Borg, J. S., Deng, Y., & Kramer, M. (2017). Moral decision making frameworks for artificial intelligence. In Aaai Workshop Technical Report (Vol. WS-17-01-WS-17-15, pp. 105–109).
Conitzer, V., W. Sinnott-Armstrong, J. S. Borg, Y. Deng, and M. Kramer. “Moral decision making frameworks for artificial intelligence.” In Aaai Workshop Technical Report, WS-17-01-WS-17-15:105–9, 2017.
Conitzer V, Sinnott-Armstrong W, Borg JS, Deng Y, Kramer M. Moral decision making frameworks for artificial intelligence. In: Aaai Workshop Technical Report. 2017. p. 105–9.
Conitzer, V., et al. “Moral decision making frameworks for artificial intelligence.” Aaai Workshop Technical Report, vol. WS-17-01-WS-17-15, 2017, pp. 105–09.
Conitzer V, Sinnott-Armstrong W, Borg JS, Deng Y, Kramer M. Moral decision making frameworks for artificial intelligence. Aaai Workshop Technical Report. 2017. p. 105–109.

Published In

Aaai Workshop Technical Report

Publication Date

January 1, 2017

Volume

WS-17-01 - WS-17-15

Start / End Page

105 / 109