On the role of loss-driven systems analysis in assessing AI ethics

Tyler Cody; Laura Freeman; Peter A. Beling

doi:10.1117/12.3012385

7 June 2024 On the role of loss-driven systems analysis in assessing AI ethics

Tyler Cody, Laura Freeman, Peter A. Beling

Proceedings Volume 13054, Assurance and Security for AI-enabled Systems; 1305403 (2024) https://doi.org/10.1117/12.3012385
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

As machine learning (ML) models are integrated more and more into critical systems, questions regarding their ethical use intensify. This paper advocates for a loss-driven engineering approach, incorporating concepts from systems-theoretic process analysis (STPA), to identify external systems, technologies, and processes essential for ethical ML deployment and therefore crticial to assessing AI ethics. STPA facilitates a deep analysis of potential hazards and system-level vulnerabilities, generating actionable insights for designing support systems and safeguards. Resilience engineering principles can be utilized to convert these insights into testable requirements for assessing AI ethics. This innovative, multi-disciplinary approach addresses a critical gap in current ML practices by extending ethical evaluation beyond the model, offering a robust framework for the responsible development and deployment of AI technologies.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Tyler Cody, Laura Freeman, and Peter A. Beling "On the role of loss-driven systems analysis in assessing AI ethics", Proc. SPIE 13054, Assurance and Security for AI-enabled Systems, 1305403 (7 June 2024); https://doi.org/10.1117/12.3012385

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