Allison Fritz

In a representative vignette study in Germany with 1,653 respondents, we investigated laypeople’s attribution of moral responsibility in collaborative medical diagnosis. Specifically, we compare people’s judgments in a setting in which physicians are supported by an AI-based recommender system to a setting in which they are supported by a human colleague. It turns out that people tend to attribute moral responsibility to the artificial agent, although this is traditionally considered a category mistake in normative ethics. This tendency is stronger when people believe that AI may become conscious at some point. In consequence, less responsibility is attributed to human agents in settings with hybrid diagnostic teams than in settings with human-only diagnostic teams. Our findings may have implications for behavior exhibited in contexts of collaborative medical decision making with AI-based as opposed to human recommenders because less responsibility is attributed to agents who have the mental capacity to care about outcomes.

Pro-environmental behaviors symbolic of the three R’s—reduce, reuse, recycle—are focused on individual consumption and use patterns. These traditional environmentalist behaviors—what I shall call “shallow environmentalism”—are vulnerable to the problem of inconsequentialism, in that a single individual engaging in them does little to combat or mitigate climate change. Indeed, some argue that continued occupation with shallow environmental behaviors such as recycling and reducing travel gets in the way of fighting climate change by inappropriately focusing blame on individuals, wasting energy on ineffective means, and creating a low benchmark by which people can measure whether they have done their environmental duty. Using environmental virtue ethics, I will argue for the importance of engaging in shallow environmentalism. I will use findings in behavioral psychology to show how these behaviors play an important role in fostering motivation and how behavioral alignment with popular understandings of environmentalism is related to perceptions of legitimacy of climate activists’ positions.

In a representative vignette study in Germany with 1,653 respondents, we investigated laypeople’s attribution of moral responsibility in collaborative medical diagnosis. Specifically, we compare people’s judgments in a setting in which physicians are supported by an AI-based recommender system to a setting in which they are supported by a human colleague. It turns out that people tend to attribute moral responsibility to the artificial agent, although this is traditionally considered a category mistake in normative ethics. This tendency is stronger when people believe that AI may become conscious at some point. In consequence, less responsibility is attributed to human agents in settings with hybrid diagnostic teams than in settings with human-only diagnostic teams. Our findings may have implications for behavior exhibited in contexts of collaborative medical decision making with AI-based as opposed to human recommenders because less responsibility is attributed to agents who have the mental capacity to care about outcomes.