How to Stop Minority Report from Becoming a Reality: Transparency and Accountability of Algorithmic Regulation

25 Pages Posted: 31 Dec 2021

Abstract

In this essay I aim to illuminate on the importance of transparency and accountability in algorithmic regulation, a highly topical legal issue that presents important consequences because Machine Learning algorithms have been constantly developing as of late. Building on prior studies and on current literature, such as Citron, Crootof, Pasquale and Zarsky, I intend to develop a proposal that bridges said knowledge with that of Daniel Kahneman in order to amplify the legal question at hand with the notions of blinders and biases. I will argue that if left unattended or if improperly attended, Machine Learning algorithms will produce more harm than good due to these blinders and biases. After linking the aforementioned ideas, I will focus on the transparency and accountability of algorithmic regulation, and its ties to technological due process. The findings will illustrate the present need of a human element, better exemplified by the concept of cyborg justice, and the public policy challenges it entails. In the end, I will propose what could be done in the future in this area.

Keywords: Law, Technology, Algorithm, Artificial Intelligence, Regulation

Suggested Citation

Edwards, Ernesto, How to Stop Minority Report from Becoming a Reality: Transparency and Accountability of Algorithmic Regulation. Available at SSRN: https://ssrn.com/abstract=3997871 or http://dx.doi.org/10.2139/ssrn.3997871

Ernesto Edwards (Contact Author)

National University of Rosario ( email )

Rosario
Argentina

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