  The societal and ethical implications of the use of opaque artificial
intelligence systems for consequential decisions, such as welfare allocation
and criminal justice, have generated a lively debate among multiple stakeholder
groups, including computer scientists, ethicists, social scientists, policy
makers, and end users. However, the lack of a common language or a
multi-dimensional framework to appropriately bridge the technical, epistemic,
and normative aspects of this debate prevents the discussion from being as
productive as it could be. Drawing on the philosophical literature on the
nature and value of explanations, this paper offers a multi-faceted framework
that brings more conceptual precision to the present debate by (1) identifying
the types of explanations that are most pertinent to artificial intelligence
predictions, (2) recognizing the relevance and importance of social and ethical
values for the evaluation of these explanations, and (3) demonstrating the
importance of these explanations for incorporating a diversified approach to
improving the design of truthful algorithmic ecosystems. The proposed
philosophical framework thus lays the groundwork for establishing a pertinent
connection between the technical and ethical aspects of artificial intelligence
systems.
