  Recent research shows -- somewhat astonishingly -- that people are willing to
ascribe moral blame to AI-driven systems when they cause harm [1]-[4]. In this
paper, we explore the moral-psychological underpinnings of these findings. Our
hypothesis was that the reason why people ascribe moral blame to AI systems is
that they consider them capable of entertaining inculpating mental states (what
is called mens rea in the law). To explore this hypothesis, we created a
scenario in which an AI system runs a risk of poisoning people by using a novel
type of fertilizer. Manipulating the computational (or quasi-cognitive)
abilities of the AI system in a between-subjects design, we tested whether
people's willingness to ascribe knowledge of a substantial risk of harm (i.e.,
recklessness) and blame to the AI system. Furthermore, we investigated whether
the ascription of recklessness and blame to the AI system would influence the
perceived blameworthiness of the system's user (or owner). In an experiment
with 347 participants, we found (i) that people are willing to ascribe blame to
AI systems in contexts of recklessness, (ii) that blame ascriptions depend
strongly on the willingness to attribute recklessness and (iii) that the
latter, in turn, depends on the perceived "cognitive" capacities of the system.
Furthermore, our results suggest (iv) that the higher the computational
sophistication of the AI system, the more blame is shifted from the human user
to the AI system.
