Consent as a Foundation for Responsible Autonomy
Munindar Singh
[AAAI-22] Senior Member Presentation Track - Blue Sky
Abstract:
This paper focuses on a dynamic aspect of responsible autonomy, namely, to make intelligent agents be responsible at run time. That is, it considers settings where decision making by agents impinges upon the outcomes perceived by other agents. For an agent to act responsibly, it must accommodate the desires and other attitudes of its users and, through other agents, of their users.
The contribution of this paper is twofold. First, it provides a conceptual analysis of consent, its benefits and misuses, and how understanding consent can help achieve responsible autonomy. Second, it outlines challenges for AI (in particular, for agents and multiagent systems) that merit investigation to form as a basis for modeling consent in multiagent systems and applying consent to achieve responsible autonomy.
The contribution of this paper is twofold. First, it provides a conceptual analysis of consent, its benefits and misuses, and how understanding consent can help achieve responsible autonomy. Second, it outlines challenges for AI (in particular, for agents and multiagent systems) that merit investigation to form as a basis for modeling consent in multiagent systems and applying consent to achieve responsible autonomy.
Sessions where this paper appears
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Poster Session 3
Fri, February 25 8:45 AM - 10:30 AM (+00:00)
Blue 6
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Poster Session 7
Sat, February 26 4:45 PM - 6:30 PM (+00:00)
Blue 6
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Oral Session 7
Sat, February 26 6:30 PM - 7:45 PM (+00:00)
Blue 6