AIRO: an Ontology for Representing AI Risks based on the Proposed EU AI Act and ISO Risk Management Standards

The growing number of incidents caused by (mis)using Artificial Intelligence (AI) is a matter of concern for governments, organisations, and the public. To control the harmful impacts of AI, multiple efforts are being taken all around the world from guidelines promoting trustworthy development and use, to standards for managing risks and regulatory frameworks. Amongst these efforts, the first-ever AI regulation proposed by the European Commission, known as the AI Act, is prominent as it takes a risk-oriented approach towards regulating development and use of AI within systems. In this paper, we present the AI Risk Ontology (AIRO) for expressing information associated with high-risk AI systems based on the requirements of the proposed AI Act and ISO 31000 series of standards. AIRO assists stakeholders in determining `high-risk' AI systems, maintaining and documenting risk information, performing impact assessments, and achieving conformity with AI regulations. To show its usefulness, we model existing real-world use-cases from the AIAAIC repository of AI-related risks, determine whether they are high-risk, and produce documentation for the EU's proposed AI Act.This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813497, as part of the ADAPT SFI Centre for Digital Media Technology is funded by Science Foundation Ireland through the SFI Research Centres Programme and is co-funded under the European Regional Development Fund (ERDF) through Grant#13/RC/2106_P2. Harshvardhan J. Pandit has received funding under the Irish Research Council Government of Ireland Postdoctoral Fellowship Grant#GOIPD/2020/790