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Legal requirements on explainability in machine learning

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Academic year: 2021

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Fig. 1   The user classically provides structured data in a tabular format (1). The columns of the data table  correspond to features of the instances in the rows
Fig. 2    Weaker requirements can focus on three views of a model: (1) the whole model, (2) a particular  decision of the model (here when Q 1 = no and Q  3 = yes), or (3) the features involved in a particular  deci-sion (e.g
Fig. 3   Input and output of the learning process with legal requirements on explainability in B2C and  B2B
Fig. 4   Figure inspired by Ribeiro et al. (2016). Local explanation of a complex decision boundary (i.e
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