aiqbench analysis
The report highlights significant hurdles in implementing the UK Defence's JSP 936 directive, noting that while the governance framework is sound, practical adoption is stalled by unresolved technical and organizational questions. Key friction points include balancing AI performance with safety, managing human-AI interaction, and addressing the limitations of current assurance methodologies in complex, real-world environments. Success will depend on developing iterative guidance and enhanced organizational capabilities to navigate these socio-technical complexities.
AI Assurance in UK Defence: Challenges in Operationalising JSP 936
arXiv:2606.09414v1 Announce Type: cross Abstract: This report examines practical challenges in operationalising JSP 936 Part 1 for AI assurance in UK Defence. Using a structured interpretive review of the directive's requirements, the analysis identifies eight thematic challenge areas adequacy of evidence and argument, management of human interaction with AI, definition of the operational environment, integration of AI within systems of systems, assessment and maintenance of AI performance, analysis of safety and security, measurement of ethicality, and mitigation of the inherent complexities of AI. The report argues that JSP 936 provides a useful governance basis, but that implementation depends on unresolved technical, organisational, and assurance questions. These challenges stem from the socio-technical nature of AI-enabled systems, uncertainty in real-world deployment contexts, limitations in current assurance methodologies, and tensions between performance, safety, human oversight, security, and ethical acceptability. The report identifies areas where further methods, guidance, and organisational capability are needed for the ambitious, safe, and responsible adoption of AI across Defence. This is consistent with MOD's own framing of JSP 936 as requiring iterative implementation and supporting guidance.
Abstract:This report examines practical challenges in operationalising JSP 936 Part 1 for AI assurance in UK Defence. Using a structured interpretive review of the directive's requirements, the analysis identifies eight thematic challenge areas adequacy of evidence and argument, management of human interaction with AI, definition of the operational environment, integration of AI within systems of systems, assessment and maintenance of AI performance, analysis of safety and security, measurement of ethicality, and mitigation of the inherent complexities of AI. The report argues that JSP 936 provides a useful governance basis, but that implementation depends on unresolved technical, organisational, and assurance questions. These challenges stem from the socio-technical nature of AI-enabled systems, uncertainty in real-world deployment contexts, limitations in current assurance methodologies, and tensions between performance, safety, human oversight, security, and ethical acceptability. The report identifies areas where further methods, guidance, and organisational capability are needed for the ambitious, safe, and responsible adoption of AI across Defence. This is consistent with MOD's own framing of JSP 936 as requiring iterative implementation and supporting guidance.
Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI)
arXiv:2606.09414 [cs.HC]
(or arXiv:2606.09414v1 [cs.HC] for this version)
https://doi.org/10.48550/arXiv.2606.09414 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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Full text under the publisher's open licence · 269 words
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