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Explaining the Black Box: when law controls AI

  • February 3, 2020
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ISSUE PAPER | Explaining the Black Box: when law controls AI

The explainability of Artificial Intelligence algorithms, in particular Machine-Learning algorithms, has become a major concern for society. Policy-makers across the globe are starting to reply to such concern.

In Europe, a High-level Expert Group on AI has proposed seven requirements for a trustworthy AI, which are: human agency and oversight, technical robustness and safety, privacy and data governance, transparency, diversity/non-discrimination/fairness, societal and environmental wellbeing, and accountability.

On that basis, the Commission proposed six types of requirement for high risk AI applications in its White Paper on AI: ensuring quality of training data; keeping data and records of the programming of AI systems; information to be proactively provided to various stakeholders (transparency and explainability); ensuring robustness and accuracy;  having human oversight; and other specific requirements for certain particular AI applications, such as those used for purposes of remote biometric identification. Thus in both documents, transparency and explainability are considered key. This is why several new obligations, specific to automated systems (and thus, to AI), in particular in data protection rules and consumer protection rules, have been adopted in Europe to enhance the explainability of algorithmic decisions.

This CERRE Technology Issue Paper deals with various aspects of AI explainability obligations:

  • the different meanings of explainability, in particular by confronting the legal and the computer science meanings;
  • the European AI-specific obligations imposing explainability to operators of such systems;
  • the rationale of the above-mentioned rules;
  • obligations implemented by different Machine Learning techniques.

The paper also lists a series of issues for further discussion.

Author(s)
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Alexandre De Streel
Alexandre de Streel
CERRE Academic Director
University of Namur

Alexandre de Streel is the Academic Director of the digital research programme at CERRE and Professor of European law at the University of Namur where he chairs the Namur Digital Institute (NADI). Alexandre is also visiting professor at the College of Europe (Bruges) and SciencesPo Paris. Besides, he chairs the expert group on the online platform economy advising the European Commission and is a part-time judge at the Belgian Competition Authority.

His main areas of research are regulation and competition policy in the digital economy as well as the legal issues raised by the developments of artificial intelligence.

Previously, Alexandre held visiting positions at New York University Law School, European University Institute in Florence, Barcelona Graduate School of Economics and University of Louvain. He also worked for the Belgian Deputy Prime Minister, the Belgian Permanent Representation to the European Union and the European Commission.

Benoit Frenay
Benoît Frenay
Associated Professor
University of Namur

Benoît Frenay is Associate Professor at the Faculty of Computer Science of the University of Namur. His main research interests in machine learning include support vector machines, label noise, efficient learning, graphical models, classification, data clustering, probability density estimation and feature selection.

He completed a degree in computing science engineering (spec. in artificial intelligence) in 2007 at the Université catholique de Louvain (UCL). He then obtained a PhD degree in Machine Learning from UCL in 2013.

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