John A. McDermid

Yoshua Bengio, Sören Mindermann, Daniel Privitera et al. · eth-zurich

This is the interim publication of the first International Scientific Report on the Safety of Advanced AI. The report synthesises the scientific understanding of general-purpose AI -- AI that can perform a wide variety of tasks -- with a focus on understanding and managing its risks. A diverse group of 75 AI experts contributed to this report, including an international Expert Advisory Panel nominated by 30 countries, the EU, and the UN. Led by the Chair, these independent experts collectively had full discretion over the report's content. The final report is available at arXiv:2501.17805

John A. McDermid

Effective software safety standards will contribute to confidence, or assurance, in the safety of the systems in which the software is used. It is infeasible to demonstrate a correlation between standards and accidents, but there is an alternative view that makes standards "testable". Software projects are subject to uncertainty; good standards reduce uncertainty more than poor ones. Similarly assurance or integrity levels in standards should define an uncertainty gradient. The paper proposes an argument -based method of reasoning about uncertainty that can be used as a basis for conducting experiments (tests) to evaluate standards.