Artefact is proud to announce that it has been awarded the Labelia - Responsible and Trusted AI label by the independent association Labelia Labs.
Read MoreToday, 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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