From Automation to Autonomous Systems: A Legal Phenomenology with Problems
of Accountability
Abstract
Over the past decades a considerable amount of
work has been devoted to the notion of autonomy
and the intelligence of robots and of AI systems:
depending on the application, several standards on
the “levels of automation” have been proposed.
Although current AI systems may have the intelligence of a fridge, or of a toaster, some of such autonomous systems have already challenged basic
pillars of society and the law, e.g. whether lethal
force should ever be permitted to be “fully automated.” The aim of this paper is to show that the
normative challenges of AI entail different types of
accountability that go hand-in-hand with choices of
technological dependence, delegation of cognitive
tasks, and trust. The stronger the social cohesion is,
the higher the risks that can be socially accepted
through the normative assessment of the not fully
predictable consequences of tasks and decisions
entrusted to AI systems and artificial agents