  Recently, a lot of attention has been given to undesired consequences of
Artificial Intelligence (AI), such as unfair bias leading to discrimination, or
the lack of explanations of the results of AI systems. There are several
important questions to answer before AI can be deployed at scale in our
businesses and societies. Most of these issues are being discussed by experts
and the wider communities, and it seems there is broad consensus on where they
come from. There is, however, less consensus on, and experience with how to
practically deal with those issues in organizations that develop and use AI,
both from a technical and organizational perspective. In this paper, we discuss
the practical case of a large organization that is putting in place a
company-wide methodology to minimize the risk of undesired consequences of AI.
We hope that other organizations can learn from this and that our experience
contributes to making the best of AI while minimizing its risks.
