As artificial intelligence becomes more sophisticated and robots approach autonomous decision-making, debates about how to assign moral responsibility have gained importance, urgency, and sophistication. Answering Stenseke’s (2022a) call for scaffolds that can help us classify views and commitments, we think the current debate space can be represented hierarchically, as answers to key questions. We use the resulting taxonomy of five stances to differentiate—and defend—what is known as the “blank check” proposal. According to this proposal, a person activating a robot could (...) willingly make themselves answerable for whatever events ensue, even if those events stem from the robot’s autonomous decision(s). This blank check solution was originally proposed in the context of automated warfare (Champagne & Tonkens, 2015), but we extend it to cover all robots. We argue that, because moral answerability in the blank check is accepted voluntarily and before bad outcomes are known, it proves superior to alternative ways of assigning blame. We end by highlighting how, in addition to being just, this self-initiated and prospective moral answerability for robot harm provides deterrence that the four other stances cannot match. (shrink)

The claim I want to explore in this paper is simple. In social ontology, Margaret Gilbert, Abe Roth, Michael Bratman, Antonie Meijers, Facundo Alonso and others talk about rights or entitlements against other participants in joint action. I employ several intuition pumps to argue that we have reason to assume that such entitlements or rights can be ascribed even to non-sentient robots that we collaborate with. Importantly, such entitlements are primarily identified in terms of our normative discourse. Justified criticism, for (...) example, presupposes that another person acted wrongly, i.e., was not entitled to this action. Praise is supposed to encourage another person and acknowledge that one did more than one was obligated to. I show that such normative talk serves the same function when cooperating with robots. This, I argue, suggests that they have the same kind of entitlements and duties at least in the context of a joint action. (shrink)

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)