This document provides a prospective catalogue of risks related to AI use in the automotive sector, organized across five AI lifecycle stages: AI & Use Case Specification, AI Model Architecture & Training Processes, Data Specification & Management, Verification & Validation, and Operation/In-Use Monitoring. For each of 23 identified risks, the document lists relevant ISO/PAS 8800, NIST AI RMF, EU AIA, and other standards or frameworks that address potential management and mitigation approaches. Extended descriptions explain how risks such as blackbox behaviour, data poisoning, distribution shift, insufficient test coverage, and concept drift may compromise safety in automotive AI systems.
The Informal Working Group on Artificial Intelligence identified relevant literature for a literature review addressing existing standards, research, best practice, and regulations relating to artificial intelligence in automotive safety applications. Proposal to include IEEE standards on algorithmic bias, robustness testing, and organizational governance; risk assessment frameworks from IEEE and NIST; the EU AI Act; international instruments including the Council of Europe Framework Convention on AI and OECD AI Principles; and the G7 Hiroshima AI Process Code of Conduct. These sources address lifecycle phases and risk management relevant to the prospective catalogue of AI risks in automotive (AI-07-06) and consolidated draft documentation (AI-06-03).
The IWG will be informed on the status of identification of AI Use Cases, the revised draft Terms & Definitions Document, and the ongoing collection of proposals for the literature review. The IWG may wish to exchange views concerning guiding questions for AI in automotive, risks of the use of AI in automotive and their management and mitigation, and the consolidated draft for reference document. The 9th IWG on AI session is planned for June 3-4th, hybrid in London, UK and online.