  Combining big data and machine learning algorithms, the power of automatic
decision tools induces as much hope as fear. Many recently enacted European
legislation (GDPR) and French laws attempt to regulate the use of these tools.
Leaving aside the well-identified problems of data confidentiality and
impediments to competition, we focus on the risks of discrimination, the
problems of transparency and the quality of algorithmic decisions. The detailed
perspective of the legal texts, faced with the complexity and opacity of the
learning algorithms, reveals the need for important technological disruptions
for the detection or reduction of the discrimination risk, and for addressing
the right to obtain an explanation of the auto- matic decision. Since trust of
the developers and above all of the users (citizens, litigants, customers) is
essential, algorithms exploiting personal data must be deployed in a strict
ethical framework. In conclusion, to answer this need, we list some ways of
controls to be developed: institutional control, ethical charter, external
audit attached to the issue of a label.
