Consent as a Foundation for Responsible Autonomy

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.

Inferring Values via Hybrid Intelligence

“…Thus, the quality of the data employed in the value inference steps must be curated to guarantee that the process is fair and free of bias [26,38]. (5) Designing autonomous agents that align with their human users' values is an important step toward trustworthy AI [36,37]. To this end, the value inference processes must be legitimate [14], providing adequate channels for eliciting stakeholders' consent [37] and dissent [10].…”

“…(5) Designing autonomous agents that align with their human users' values is an important step toward trustworthy AI [36,37]. To this end, the value inference processes must be legitimate [14], providing adequate channels for eliciting stakeholders' consent [37] and dissent [10].…”