AI Risk Assessment: A Scenario-Based, Proportional Methodology for the AI Act

Digital Society 3, 13 (2024); https://doi.org/10.1007/s44206-024-00095-1

29 Pages Posted: 2 Jun 2023 Last revised: 11 Mar 2024

See all articles by Claudio Novelli

Claudio Novelli

University of Bologna- Department of Legal Studies; Yale University - Digital Ethics Center

Federico Casolari

Alma Mater Studiorum - University of Bologna

Antonino Rotolo

University of Bologna - Department of Legal Sciences

Mariarosaria Taddeo

University of Oxford - Oxford Internet Institute

Luciano Floridi

Yale University - Digital Ethics Center; University of Bologna- Department of Legal Studies

Date Written: May 31, 2023

Abstract

The EU Artificial Intelligence Act (AIA) defines four risk categories for AI systems: unacceptable, high, limited, and minimal. However, it lacks a clear methodology for the assessment of these risks in concrete situations. Risks are broadly categorized based on the application areas of AI systems and ambiguous risk factors. This paper suggests a methodology for assessing AI risk magnitudes, focusing on the construction of real-world risk scenarios. To this scope, we propose to integrate the AIA with a framework developed by the Intergovernmental Panel on Climate Change (IPCC) reports and related literature. This approach enables a nuanced analysis of AI risk by exploring the interplay between (a) risk determinants, (b) individual drivers of determinants, and (c) multiple risk types. We further refine the proposed methodology by applying a proportionality test to balance the competing values involved in AI risk assessment. Finally, we present three uses of this approach under the AIA: to implement the Regulation, to assess the significance of risks, and to develop internal risk management systems for AI deployers.

Keywords: risk assessment, AI Act, IPCC, proportionality, Artificial Intelligence

Suggested Citation

Novelli, Claudio and Casolari, Federico and Rotolo, Antonino and Taddeo, Mariarosaria and Floridi, Luciano, AI Risk Assessment: A Scenario-Based, Proportional Methodology for the AI Act (May 31, 2023). Digital Society 3, 13 (2024); https://doi.org/10.1007/s44206-024-00095-1, Available at SSRN: https://ssrn.com/abstract=4464783 or http://dx.doi.org/10.2139/ssrn.4464783

Claudio Novelli (Contact Author)

University of Bologna- Department of Legal Studies ( email )

Via Zamboni 22
Bologna, Bo 40100
Italy

HOME PAGE: http://https://dsg.unibo.it/en

Yale University - Digital Ethics Center ( email )

85, Trumbull Street
New Haven, CT 06511
United States

HOME PAGE: http://https://dec.yale.edu

Federico Casolari

Alma Mater Studiorum - University of Bologna ( email )

Department of Legal Studies
via Zamboni, 27/29
Bologna, Bologna 40126
Italy
+39 051 20 9 9683 (Phone)

HOME PAGE: http://www.unibo.it/faculty/federico.casolari

Antonino Rotolo

University of Bologna - Department of Legal Sciences

Bologna
Italy

Mariarosaria Taddeo

University of Oxford - Oxford Internet Institute ( email )

1 St. Giles
University of Oxford
Oxford OX1 3PG Oxfordshire, Oxfordshire OX1 3JS
United Kingdom

Luciano Floridi

Yale University - Digital Ethics Center ( email )

85 Trumbull Street
New Haven, CT CT 06511
United States
2034326473 (Phone)

University of Bologna- Department of Legal Studies ( email )

Via Zamboni 22
Bologna, Bo 40100
Italy

HOME PAGE: http://www.unibo.it/sitoweb/luciano.floridi/en

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