Publications

The World Bank compares the economies of 190 countries in accordance with their capability to incentivize entrepreneurial activity. At the international level, the report confirms the positive convergence between the systems of the most advanced countries and those of developing countries. At the Italian level, the World Bank points out the almost total immobility of the regulatory system, with serious problems in tax and judicial matters (Rassegna trimestrale dell’Osservatorio AIR, July 2019 X/3)

Rassegna dell’Osservatorio AIR, n. 4, October

Studi Parlamentari e di Politica Costituzionale, 203-204, 1-2

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The legal system is awash with excessive and incomprehensible information. Yet many of us assume that the unrelenting torrent of information pouring into various legal programs is both inevitable and unstoppable. We have become complacent; but it does not have to be this way. Incomprehensible! argues that surrendering to incomprehensibility is a bad mistake. Drawing together evidence from diverse fields such as consumer protection, financial regulation, patents, chemical control, and administrative and legislative processes, this book identifies a number of important legal programs that are built on the foundational assumption that 'more information is better'. Each of these legal processes have been designed in ways that ignore the imperative of meaningful communication. To rectify this systemic problem, the law must be re-designed to pay careful attention to the problem of incomprehensibility.

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At every level of government, officials contract for technical systems that employ machine learning—systems that perform tasks without using explicit instructions, relying on patterns and inference instead. These systems frequently displace discretion previously exercised by policymakers or individual front-end government employees with an opaque logic that bears no resemblance to the reasoning processes of agency personnel. However, because agencies acquire these systems through government procurement processes, they and the public have little input into—or even knowledge about—their design or how well that design aligns with public goals and values. This Article explains the ways that the decisions about goals, values, risk, and certainty, along with the elimination of case-by-case discretion, inherent in machine-learning system design create policies—not just once when they are designed, but over time as they adapt and change. When the adoption of these systems is governed by procurement, the policies they embed receive little or no agency or outside expertise beyond that provided by the vendor. Design decisions are left to private third-party developers. There is no public participation, no reasoned deliberation, and no factual record, which abdicates Government responsibility for policymaking. This Article then argues for a move from a procurement mindset to policymaking mindset. When policy decisions are made through system design, processes suitable for substantive administrative determinations should be used: processes that foster deliberation reflecting both technocratic demands for reason and rationality informed by expertise, and democratic demands for public participation and political accountability. Specifically, the Article proposes administrative law as the framework to guide the adoption of machine learning governance, describing specific ways that the policy choices embedded in machine-learning system design fail the prohibition against arbitrary and capricious agency actions absent a reasoned decision-making process that both enlists the expertise necessary for reasoned deliberation about, and justification for, such choices, and makes visible the political choices being made. Finally, this Article sketches models for machine-learning adoption processes that satisfy the prohibition against arbitrary and capricious agency actions. It explores processes by which agencies might garner technical expertise and overcome problems of system opacity, satisfying administrative law’s technocratic demand for reasoned expert deliberation. It further proposes both institutional and engineering design solutions to the challenge of policymaking opacity, offering process paradigms to ensure the “political visibility” required for public input and political oversight. In doing so, it also proposes the importance of using “contestable design”—design that exposes value-laden features and parameters and provides for iterative human involvement in system evolution and deployment. Together, these institutional and design approaches further both administrative law’s technocratic and democratic mandates.