Deep learning AI systems have proven a wide capacity to take over human-related activities such as car driving, medical diagnosing, or elderly care, often displaying behaviour with unpredictable consequences, including negative ones. This has raised the question whether highly autonomous AI may qualify as morally responsible agents. In this article, we develop a set of four conditions that an entity needs to meet in order to be ascribed moral responsibility, by drawing on Aristotelian ethics and contemporary philosophical research. We encode (...) these conditions and generate a flowchart that we call the Moral Responsibility Test. This test can be used as a tool both to evaluate whether an entity is a morally responsible agent and to inform human moral decision-making over the influencing variables of the context of action. We apply the test to the case of Artificial Moral Advisors and conclude that this form of AI cannot qualify as morally responsible agents. We further discuss the implications for the use of AMAs as moral enhancement and show that using AMAs to offload human responsibility is inadequate. We argue instead that AMAs could morally enhance users if they are interpreted as enablers for moral knowledge of the contextual variables surrounding human moral decision-making, with the implication that such a use might actually enlarge human moral responsibility. (shrink)

Skeptical worries about moral responsibility seem to be widely appreciated and deeply felt. To address these worries—if nothing else to show that they are mistaken—theories of moral responsibility need to relate to whatever concept of responsibility underlies the worries. Unfortunately, the nature of that concept has proved hard to pin down. Not only do philosophers have conflicting intuitions; numerous recent empirical studies have suggested that both prosaic responsibility judgments and incompatibilist intuitions among the folk are influenced by a number of (...) surprising factors, sometimes prompting apparently contradictory judgments. In this paper, we show how an independently motivated hypothesis about responsibility judgments provides a unified explanation of the more important results from these studies. According to this ‘Explanation Hypothesis’, to take an agent to be morally responsible for an event is to take a relevant motivational structure of the agent to be part of a significant explanation of the event. We argue that because of how explanatory interests and perspectives affect what we take as significant explanations, this analysis accounts for the puzzling variety of empirical results. If this is correct, the Explanation Hypothesis also provides a new way of understanding debates about moral responsibility. (shrink)