Regulating Machine Learning by Design

CPI TechREG Chronicle, February 2023 issue

9 Pages Posted: 28 Feb 2023 Last revised: 20 Mar 2023

See all articles by Marco Almada

Marco Almada

Universite du Luxembourg - Faculty of Law, Economics and Finance

Date Written: February 22, 2023

Abstract

The regulation of digital technologies around the world draws from various regulatory techniques. One such technique is regulation by design, in which regulation specify requirements that software designers must follow when creating any systems. This paper examines the suitability of regulation by design approaches to machine learning, arguing that they are potentially useful but have a narrow scope of application. Drawing from EU law examples, it shows how regulation by design relies on the delegation of normative definitions and enforcement to software designers, but such delegation is only effective if a few conditions are present. These conditions, however, are seldom met by applications of machine learning technologies in the real world, and so regulation by design cannot address many of the pressing concerns driving regulation. Nonetheless, by-design provisions can support regulation if applied to well-defined problems that lend themselves to clear expression in software code. Hence, regulation by design, within its proper limits, can be a powerful tool for regulators of machine learning technologies.

Keywords: machine learning, regulation by design, meta-regulation

Suggested Citation

Almada, Marco, Regulating Machine Learning by Design (February 22, 2023). CPI TechREG Chronicle, February 2023 issue, Available at SSRN: https://ssrn.com/abstract=4367025

Marco Almada (Contact Author)

Universite du Luxembourg - Faculty of Law, Economics and Finance ( email )

4, rue Alphonse Weicker
Luxembourg, L-2721
Luxembourg

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