• Media type: E-Book
  • Title: How to Evaluate the Risks of Artificial Intelligence : A Proportionality-Based, Risk Model for the AI Act
  • Contributor: Novelli, Claudio [VerfasserIn]; Casolari, Federico [VerfasserIn]; Rotolo, Antonino [VerfasserIn]; Taddeo, Mariarosaria [VerfasserIn]; Floridi, Luciano [VerfasserIn]
  • imprint: [S.l.]: SSRN, [2023]
  • Extent: 1 Online-Ressource (26 p)
  • Language: English
  • DOI: 10.2139/ssrn.4464783
  • Identifier:
  • Keywords: risk assessment ; AI Act ; IPCC ; proportionality ; Artificial Intelligence
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments May 31, 2023 erstellt
  • Description: The EU proposal for the Artificial Intelligence Act (AIA) defines four risk categories: unacceptable, high, limited, and minimal. However, as these categories statically depend on broad fields of application of AI systems (AIs), the risk magnitude may be wrongly estimated, and the AIA may not be enforced effectively. Our suggestion is to apply the four categories to the risk scenarios of each AIs, rather than solely to its field of application. We address this model flaw by integrating the AIA with the framework arising from the Intergovernmental Panel on Climate Change (IPCC) reports and related literature. This makes possible addressing AI risk considering the interaction between (a) risk determinants, (b) individual drivers of determinants, and (c) multiple risk types. Then we integrate the proposed model with a proportionality-based balance among values considered by the AIA’s risk analysis. The resulting semi-quantitative approach identifies a more efficient way to implement the AIA and addresses the regulatory issue of general-purpose AI (GPAI)
  • Access State: Open Access