Normative Challenges of Risk Regulation of Artificial Intelligence and Automated Decision-Making

• URL: http://arxiv.org/abs/2211.06203v1
• Date: Fri, 11 Nov 2022 13:57:38 GMT
• Title: Normative Challenges of Risk Regulation of Artificial Intelligence and Automated Decision-Making
• Authors: Carsten Orwat (1), Jascha Bareis (1), Anja Folberth (1 and 2), Jutta Jahnel (1) and Christian Wadephul (1) ((1) Karlsruhe Institute of Technology, Institute for Technology Assessment and Systems Analysis, (2) University of Heidelberg, Institute of Political Science)
• Abstract summary: Recent proposals aim at regulating artificial intelligence (AI) and automated decision-making (ADM) The most salient example is the Artificial Intelligence Act (AIA) proposed by the European Commission. This article addresses challenges for adequate risk regulation that arise primarily from the specific type of risks involved.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Recent proposals aiming at regulating artificial intelligence (AI) and automated decision-making (ADM) suggest a particular form of risk regulation, i.e. a risk-based approach. The most salient example is the Artificial Intelligence Act (AIA) proposed by the European Commission. The article addresses challenges for adequate risk regulation that arise primarily from the specific type of risks involved, i.e. risks to the protection of fundamental rights and fundamental societal values. They result mainly from the normative ambiguity of the fundamental rights and societal values in interpreting, specifying or operationalising them for risk assessments. This is exemplified for (1) human dignity, (2) informational self-determination, data protection and privacy, (3) justice and fairness, and (4) the common good. Normative ambiguities require normative choices, which are distributed among different actors in the proposed AIA. Particularly critical normative choices are those of selecting normative conceptions for specifying risks, aggregating and quantifying risks including the use of metrics, balancing of value conflicts, setting levels of acceptable risks, and standardisation. To avoid a lack of democratic legitimacy and legal uncertainty, scientific and political debates are suggested.

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