MAXWELL Winston

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Intelligent video in buses and subways, on-board cameras, drones, the French National Commission for Information Technology and Civil Liberties (CNIL) is calling for a general law on the implementation of these new technologies, an essential measure to guide the development of tomorrow's smart cities. The government has authorized the deployment of intelligent video systems in public transport.

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Machine learning algorithms can improve the fight against money laundering and the financing of terrorism (AML/CFT) by better detecting suspicious activities by bank customers and improving the handling of AML/CFT alerts by human compliance teams. However, the introduction of machine learning in AML/CFT monitoring systems will require a careful review of their compatibility with European fundamental rights and the GDPR. This article examines how algorithmic-based monitoring systems would be analysed under European fundamental rights law, and in particular the CJEU’s case law on the processing of personal data for the purpose of fighting crime. We identified five problems: first, AML/CFT laws imposing transaction monitoring are not clear and precise enough to comply with CJEU case law and Article 23(2) of the GDPR. second, it is impossible to measure the effectiveness of algorithmic monitoring systems, thereby raising questions about their ‘strict necessity’. third, monitoring systems cover a broad a range of offences going from terrorism to tax fraud, violating the CJEU’s principle that intrusive monitoring should be used only for the most serious crimes. fourth, current transparency measures are insufficient because persons targeted by individual AML/CFT alerts are never informed that they have been targeted. finally, institutional oversight mechanisms need to be improved to ensure that questions of effectiveness of monitoring systems and compliance with fundamental rights are considered together. We suggest solutions for each of the fundamental rights problems, drawing in particular from legislation on cyber-security and intelligence gathering.

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Algorithms have an increasingly important role in detecting and removing illegal content. The future European Digital Services Act regulation aims at surrounding these algorithms with certain rules of transparency and accountability.

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Publisher's presentation: "An operational analysis of the law on the protection of personal data. This book offers an operational analysis of a recently published text, delivers a detailed reading of the law relating to the protection of personal data and its application texts. These include the ordinance of December 12, 2018, which rewrites the entire law of January 6, 1978, in order to make the formal corrections and adaptations necessary for its simplification and coherence, as well as for the simplicity of implementation by the persons concerned of the provisions resulting from the law of June 20, 2018. These texts therefore proceed to a thorough adaptation of the 1978 "Informatique et libertés" law to take into account the new European framework resulting from the General Data Protection Regulation (GDPR) and the directive of April 27, 2016 applicable to files in the field of public security and the investigation and repression of criminal offenses (known as "police-justice"). Authors specialized in these subjects offer a practical analysis of the provisions of this new text. Simple reading tools (diagrams, tables, boxes.) accompany it to allow a detailed understanding of the contours and content of this new legislative framework."

The CJEU allows general retention of connection and location data but only to address serious threats to national security. In addition, the CJEU provides some principles on the regulation of algorithms.

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July 2019 - May 2020.

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Anti-money laundering and countering the financing of terrorism (AML) laws require banks to deploy transaction monitoring systems (TMSs) to detect suspicious activity of bank customers and report the activity to law enforcement authorities. Because the monitoring of customer data to detect suspicious activity interferes with fundamental rights, AML systems must comply with the proportionality test under European fundamental rights law, as most recently expressed by the Court of Justice of the European Union (CJEU) in the Digital Rights Ireland and Tele2 Sverige-Watson cases. To our knowledge there has been no analysis as to whether AML systems are compliant with the proportionality test as expressed in these latest cases. Understanding how the proportionality test applies to current AML systems is all the more important as banks and regulators consider moving to AI-based tools to detect suspicious transactions. The objective of this paper is twofold: to study whether current AML systems are compliant with the proportionality test, and to study whether a move toward AI in AML systems could exacerbate the proportionality problems. Where possible, we suggest possible cures to the proportionality problems identified.

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We present a framework for defining the "right" level of explainability based on technical, legal and economic considerations. Our approach involves three logical steps: First, define the main con-textual factors, such as who is the audience of the explanation, the operational context, the level of harm that the system could cause, and the legal/regulatory framework. This step will help characterize the operational and legal needs for explanation, and the corresponding social benefits. Second, examine the technical tools available, including post-hoc approaches (input perturbation, saliency maps.) and hybrid AI approaches. Third, as function of the first two steps, choose the right levels of global and local explanation outputs, taking into the account the costs involved. We identify seven kinds of costs and emphasize that explanations are socially useful only when total social benefits exceed costs.

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The recent enthusiasm for artificial intelligence (AI) is due principally to advances in deep learning. Deep learning methods are remarkably accurate, but also opaque, which limits their potential use in safety-critical applications. To achieve trust and accountability, designers and operators of machine learning algorithms must be able to explain the inner workings, the results and the causes of failures of algorithms to users, regulators, and citizens. The originality of this paper is to combine technical, legal and economic aspects of explainability to develop a framework for defining the "right" level of explain-ability in a given context. We propose three logical steps: First, define the main contextual factors, such as who the audience of the explanation is, the operational context, the level of harm that the system could cause, and the legal/regulatory framework. This step will help characterize the operational and legal needs for explanation, and the corresponding social benefits. Second, examine the technical tools available, including post hoc approaches (input perturbation, saliency maps.) and hybrid AI approaches. Third, as function of the first two steps, choose the right levels of global and local explanation outputs, taking into the account the costs involved. We identify seven kinds of costs and emphasize that explanations are socially useful only when total social benefits exceed costs.

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The CJEU's Quadrature du Net decision on October 6 2020 analyzes the use of algorithms by French intelligence agencies to detect potential terrorist activity. The Court's analysis of the algorithm reveals the core features necessary for algorithms to respect fundamental rights.

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"This book, the first in the new Décryptage collection that offers an operational analysis of a recently published text, provides a detailed reading of the law on personal data protection. This text proceeds to an in-depth adaptation of the 1978 "Informatique et libertés" law to take into account the new European framework resulting from the General Data Protection Regulation (GDPR) and the April 27, 2016 directive applicable to files in the field of public security and the investigation and repression of criminal offenses (known as "police-justice"). Authors specialized in these subjects offer a practical analysis of the provisions of this new text. Simple reading tools (diagrams, tables, boxes.) accompany it to allow a detailed understanding of the contours and content of this new legislative framework."

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The article summarizes the findings of a September 2019 report from the University of Chicago Stigler Center on the regulation of digital platforms.

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June 2018 - July 2019.

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Smart(er) Internet Regulation is about applying better regulation principles to the internet.  The book addresses difficult-to-quantify policy objectives, such as protection of fundamental rights and the preservation of the internet ecosystem, and proposes a method to make trade-offs more explicit, and regulatory solutions better fit for purpose. “…a level-headed look at the costs and benefits that flow from internet regulation… Maxwell’s analysis of fundamental rights is enlightening.” (Martin Cave, Imperial College Business School, London) “…a checklist that should be used by anyone considering a new regulation affecting internet intermediaries.” (Nicolas Curien, French Audiovisual Regulatory Authority - CSA ) “…a must-read for students of digital regulation.” (Maya Bacache, French Council of Economic Analysis -CAE) “Maxwell has shown that cost-benefit analyses can bring clearer thinking to internet regulation.” (Marc Bourreau, Telecom ParisTech).

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Regulators increasingly ask Internet intermediaries to limit access to harmful content. These actions can create negative externalities that are not fully taken into account when the regulatory decision is adopted. Drawing on law and economics literature on better regulation and cost-benefit analyses, the thesis proposes a system to help regulators take better account of the costs and benefits generated by measures affecting Internet intermediaries, and choose the measure that maximizes social welfare. The thesis identifies the various ingredients of a cost-benefit analysis, including a consideration of the different Internet intermediaries involved (search engines, ISPs, etc.), different content policies to be enforced (copyright, fight against terrorism, etc.), different institutional and regulatory approaches (self regulatory, co-regulatory, etc.), and the effects on various fundamental rights. The thesis proposes that any regulatory proposal designed to limit access to harmful Internet content be subject to an initial questionnaire, a cost-benefit analysis, a public consultation and a peer review before being adopted, and that these steps would increase the quality of regulation by, among other things, making the direct and indirect benefits and costs more visible, and trade-offs more explicit. The steps will also facilitate international benchmarking. The thesis points to the European framework for regulation of electronic communications as a source of inspiration for "better regulation" methodology that could be applied to Internet content issues.

The success of digital platforms and their role in structuring and disrupting certain sectors are not without economic, political and societal concerns. In Europe, as in France, there is talk of setting up a regulation of digital platforms. Without disputing the problems that powerful platforms such as Google, Amazon or Facebook can pose, we will show that a specific regulation would raise many difficulties both on the economic and legal levels. We will point out the costs and inefficiency of a targeted intervention on platforms, given the instability of digital markets and their strong potential in terms of technological and societal innovations. A pragmatic approach based on existing laws seems preferable to remedy the failings of platforms, particularly in emerging markets. This cautious approach is recommended by the OECD and the European Commission in their "Better Regulation" methodology.

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