AI Assurance
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Related Articles from SNS
AI Assurance in UK Defence: Challenges in Operationalising JSP 936
Announce Type: new 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...
Toward Third-Party Assurance of AI Systems: Design Requirements, Prototype, and Early Testing
arXiv:2601.22424v2 Announce Type: replace Abstract: As Artificial Intelligence (AI) systems proliferate, the need for systematic, transparent, and actionable processes for evaluating them is growing. While many resources exist to support AI evaluation, they have several limitations. Few address both the process of designing, developing, and deploying an AI system and the outcomes it produces.
Toward Pre-Deployment Assurance for Enterprise AI Agents: Ontology-Grounded Simulation and Trust Certification
arXiv:2606.04037v2 Announce Type: replace Abstract: Pre-deployment verification of enterprise artificial intelligence (AI) agents remains a critical gap between large language model (LLM) capability benchmarking and production deployment. Post-deployment monitoring, human-in-the-loop controls, and prompt-level guardrails offer limited assurance once an agent is operating in production. We present an ontology-grounded verification framework -- to our knowledge the first to combine three...
Toward Pre-Deployment Assurance for Enterprise AI Agents: Ontology-Grounded Simulation and Trust Certification
Announce Type: new Abstract: Pre-deployment verification of enterprise artificial intelligence (AI) agents remains a critical gap between large language model (LLM) capability benchmarking and production deployment. Post-deployment monitoring, human-in-the-loop controls, and prompt-level guardrails offer limited assurance once an agent is operating in production. We propose an ontology-grounded verification framework combining three components: an Agent Operational Envelope formalizing the...
Semantic Quorum Assurance: Collective Certification for Non-Deterministic AI Infrastructure
Announce Type: new Abstract: As large language model (LLM) agents are integrated into autonomous cloud operations, distributed systems face a semantic reliability problem: proposer agents can generate production mutations, such as modifying IAM policies, opening firewall security groups, or executing data exports, that are syntactically valid and statically authorized but operationally unsafe. Classical distributed consensus protocols replicate deterministic state transitions but do not...
Making Embodied AI Reliable: A Community Agenda from Testing to Formal Verification
arXiv:2606.03593v1 Announce Type: new Abstract: Embodied AI systems are increasingly deployed in open-world environments, yet ensuring their reliability remains a fundamental challenge. Drawing on discussions from the AAAI'26 Bridge Program on "Making Embodied AI Reliable with Testing and Formal Verification", this article argues that reliability in embodied AI is inherently a lifecycle assurance problem arising from uncertainty, human interaction, and emergent behaviors across tightly...
Teachers more likely to accept low AI grades than equivalent human grades, study finds
Teachers more likely to accept low AI grades than equivalent human grades, study finds Gaby Clark Scientific Editor Andrew Zinin Lead Editor Teachers were more likely to accept an overly harsh grade given to a student by AI than when the unduly low grade was handed out by a human. As AI is increasingly integrated into decision-making, concerns about AI errors are often countered by assurances that humans will oversee and check the algorithm's work. Publishing in PNAS Nexus, Rigissa...
Google explains how it will infuse ads into AI answers
Google is integrating new forms of AI-powered advertising into its search engine's AI-generated answers. These new ad types include "Conversational Discovery ads," which tailor ads to specific search queries, and "Highlighted Answers," which appear within AI Mode recommendations. This development allows Google to serve more profit-generating content alongside its enhanced AI search features.
STMutants: A Mutation Testing Dataset for Structured Text Programs in Industrial Automation
Announce Type: new Abstract: Mutation testing is widely used to evaluate test-suite effectiveness, yet IEC 61131-3 Structured Text (ST) programs still lack a publicly available benchmark that supports reproducible mutation-based research. This gap is especially important because ST is extensively used in Programmable Logic Controllers (PLCs) that operate in real-time, safety-critical industrial environments, where software faults may cause equipment damage, production loss, or unsafe system...