The EU AI Act places a requirement on public sector organisations to undertake a fundamental rights impact assessment before deploying AI system is specific applications areas such. However, the state of the art in anticipating impacts from AI is still in its infancy [1] so its use in high stakes regulatory assessment requires accelerating the evidence base available for impact assessment under the AI Act, especially maintaining what could be regarded as reasonable foreseeable risks that AI providers must take responsibility for mitigating. This project will explore how existing semantic models for AI risk assessment [2] could be use to capture impact assessment taken from publicly available incident report in the press [3] in a way that would be useful for assessing the procurement of AI systems. In particular this can take into account existing data base structures of public procurement [4] and emerging standards for procurement of AI systems [5]
[1] https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3829759
[2] https://dl.acm.org/doi/10.1145/3593013.3594050
[3] https://www.aiaaic.org/aiaaic-repository
[4] https://ted.europa.eu/en/simap/eprocurement-ontology
[5] IEEE Standard for the Procurement of Artificial Intelligence and Automated Decision Systems (IEEE std 3119)