Quasi-Dilemmas for Artificial Moral Agents
This addresses the problem of moral uncertainty in AI systems for developers and ethicists, but it is incremental as it builds on existing moral dilemma frameworks.
The paper introduces moral quasi-dilemmas (MQDs), situations where agents are uncertain if all moral requirements can be met, and argues that artificial moral agents should handle these by exploring plan spaces rather than accepting dilemmas, potentially aiding in evaluating AMA architectures.
In this paper we describe moral quasi-dilemmas (MQDs): situations similar to moral dilemmas, but in which an agent is unsure whether exploring the plan space or the world may reveal a course of action that satisfies all moral requirements. We argue that artificial moral agents (AMAs) should be built to handle MQDs (in particular, by exploring the plan space rather than immediately accepting the inevitability of the moral dilemma), and that MQDs may be useful for evaluating AMA architectures.