  It is widely acknowledged that we need to establish where responsibility lies
for the outputs and impacts of AI-enabled systems. But without a clear and
precise understanding of what "responsibility" means, deliberations about where
responsibility lies will be, at best, unfocused and incomplete and, at worst,
misguided. To address this concern, this paper draws upon central distinctions
in philosophy and law to clarify the concept of responsibility for AI for
policymakers, practitioners, researchers and students from non-philosophical
and non-legal backgrounds. Taking the three-part formulation "Actor A is
responsible for Occurrence O," the paper unravels the concept of responsibility
to clarify that there are different possibilities of who is responsible for AI,
the senses in which they are responsible, and aspects of events they are
responsible for. Criteria and conditions for fitting attributions of
responsibility in the core senses (causal responsibility, role-responsibility,
liability responsibility and moral responsibility) are articulated to promote
an understanding of when responsibility attributions would be inappropriate or
unjust. The analysis is presented with a graphical notation to facilitate
informal diagrammatic reasoning and discussion about specific cases. It is
illustrated by application to a scenario of a fatal collision between an
autonomous AI-enabled ship and a traditional, crewed vessel at sea.
