Posts by Eric Boniface
Growing applications of AI techniques vs. growing concerns: how to ease the tension?

The objective of this article is to present the participative approach on the theme "responsible and trustworthy data science" that we initiated in the summer of 2019 and that we have been leading since then. I will follow the thread of the presentation I made at the "Big data & ML" meeting on September 29, 2020. I hope that this blog format will allow as many people as possible to discover this initiative, perhaps to react to it, or even to come and contribute to it. All the feedbacks are welcome, they come to feed the reflection and the work and we need it!

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Eric Boniface
AI and Sensitive Data: a Trust Problem

Today, anywhere in the world, when a researcher or a data scientist wants to train an algorithm to do machine learning and create a prediction model, s/he must usually begin by grouping or gaining access to an already constituted dataset. S/he observes these data, consults some descriptive statistics, and manipulates them, etc. At this point, a problem of trust arises; from the moment one accesses the data the only protections against an illegitimate use of it are the ethical stances of the data scientist and/or the law, upheld through contracts or data usage agreements. Ethics and the law, that is-- trust, which is at the heart of collaborative work. But is trust always enough?

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