Normative Challenges of Risk Regulation of Artificial Intelligence and Automated Decision-Making
Carsten Orwat (1), Jascha Bareis (1), Anja Folberth (1, 2), Jutta, Jahnel (1), Christian Wadephul (1) ((1) Karlsruhe Institute of Technology,, Institute for Technology Assessment, Systems Analysis, (2) University of, Heidelberg, Institute of Political Science)

TL;DR
This paper examines the normative challenges in regulating AI and automated decision-making, focusing on risks to fundamental rights and societal values, highlighting ambiguities and normative choices in the proposed European AI Act.
Contribution
It identifies key normative ambiguities in risk regulation of AI, emphasizing the need for democratic debate and clarity in normative assumptions within the regulatory framework.
Findings
Normative ambiguities affect risk assessment and regulation.
Critical normative choices influence risk standards and metrics.
Debates are necessary to legitimize normative assumptions in AI regulation.
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…
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Taxonomy
TopicsEthics and Social Impacts of AI
