AI Assurance

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AI assurance studies how to establish that AI systems are sufficiently safe, secure, reliable, compliant, and accountable for a particular use. Approaches include risk-based testing and benchmarks, formal and statistical verification, structured safety cases, audits of evidence and provenance, and runtime monitoring tied to human oversight and governance. Work spans individual models, agentic systems, and larger socio-technical deployments, including safety-critical settings such as aviation, healthcare, and transport. A central tension is that pre-deployment tests and observable behavior provide only bounded evidence about systems that can change, interact with other components, or face adaptive conditions, so claims must be matched to evidence and supplemented by ongoing controls.

Latest papers

79 papers12 papers in the last four weeks, up 20% on the four weeks before. 0.1% of all new papers.

Autonomous Systems Dependability in the era of AI: Design Challenges in Safety, Security, Reliability and Certification
Apr 30, 2026Behnaz Ranjbar, Kirankumar Raveendiran, Sudeep Pasricha +3AI Assurance Safety-Critical Control
Chair of Embedded Systems, Ruhr Universität Bochum, Germany · Colorado State University, US · The University of North Carolina at Chapel Hill, US, and The TUM Institute for Advanced Study, Germany +1
Time-Series Forecasting in Safety-Critical Environments: An EU-AI-Act-Compliant Open-Source Package / Zeitreihenprognose in sicherheitskritischen Umgebungen: Ein KI-VO-konformes Open-Source-Paket
Apr 26, 2026Thomas Bartz-Beielstein, Eva BartzAI Assurance Time Series Forecasting
Bartz & Bartz GmbH, 51643 Gummersbach, Deutschland
Bounding the Black Box: A Statistical Certification Framework for AI Risk Regulation
Apr 23, 2026Natan Levy, Gadi PerlAI Assurance AI Risk Management
School of Computer Science and Engineering The Hebrew University of Jerusalem(HUJI) Jerusalem, Israel · dept. name of organization (of Aff.) The Hebrew University of Jerusalem(HUJI) Jerusalem, Israel
Evaluating Assurance Cases as Text-Attributed Graphs for Structure and Provenance Analysis
Apr 22, 2026Fariz Ikhwantri, Dusica MarijanAI Assurance AI-Generated Text Detection
Simula Research Laboratory Oslo, Norway
enclawed: A Configurable, Sector-Neutral Hardening Framework for Single-User AI Assistant Gateways
Apr 18, 2026Alfredo MetereAI Assurance AI Agent Security
Metere Consulting, LLC.
High-Risk AI Systems and the Problem of Identity in the European AI Act
Apr 17, 2026Andrea FerrarioAI Assurance AI Governance
Institute of Biomedical Ethics and History of Medicine, University of Zürich, Zürich, Switzerland · SUPSI, Dalle Molle Institute for Artificial Intelligence (IDSIA), Lugano, Switzerland · ETH Zürich, Zürich, Switzerland
ContextLens: Modeling Imperfect Privacy and Safety Context for Legal Compliance
Apr 14, 2026Haoran Li, Yulin Chen, Huihao Jing +6LLM Safety Evaluation AI Assurance
Beihang University · HKUST · National University of Singapore +1
AI Integrity: A New Paradigm for Verifiable AI Governance
Apr 13, 2026Seulki LeeAI Governance AI Assurance
AI Integrity Organization (AIO), Geneva, Switzerland
Blockchain and AI: Securing Intelligent Networks for the Future
Apr 7, 2026Joy Dutta, Hossien B. Eldeeb, Tu Dac HoCybersecurity AI Assurance
Department of Electrical Engineering, Khalifa University of Science and Technology, Abu Dhabi, UAE · Department of Information Systems and Security,College of Information Technology, United Arab Emirates University, Al Ain 15551, UAE · Department of Information Security and Communication Technology, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
AI Trust OS -- A Continuous Governance Framework for Autonomous AI Observability and Zero-Trust Compliance in Enterprise Environments
Apr 6, 2026Eranga Bandara, Asanga Gunaratna, Ross Gore +11AI Governance AI Assurance
Old Dominion University, Norfolk, VA, USA · AI Motion Labs, Melbourne, Australia · Deloitte & Touche LLP, USA +4
Compliance-by-Construction Argument Graphs: Using Generative AI to Produce Evidence-Linked Formal Arguments for Certification-Grade Accountability
Apr 5, 2026Mahyar T. MoghaddamAI Accountability AI Assurance
SDU Software Engineering, Odense, Denmark
RAD-AI: Rethinking Architecture Documentation for AI-Augmented Ecosystems
Mar 30, 2026Oliver Aleksander Larsen, Mahyar T. MoghaddamSoftware Architecture Design AI Regulatory Compliance
SDU Software Engineering, University of Southern Denmark, Odense, Denmark
On the Foundations of Trustworthy Artificial Intelligence
Mar 26, 2026TJ DunhamTrustworthy AI Trust in AI
ARC
Sovereign AI at the Front Door of Care: A Physically Unidirectional Architecture for Secure Clinical Intelligence
Mar 26, 2026Vasu Srinivasan, Dhriti VasuAI Assurance Clinical Triage
6Hats AI Labs Inc. · University of California, Berkeley
Operationalising Artificial Intelligence Bills of Materials (AIBOMs) for Verifiable AI Provenance and Lifecycle Assurance
Mar 17, 2026Petar Radanliev, Omar Santos, Carsten Maple +1AI Assurance Data Provenance
Parks Road, Oxford OX1 3PJ United Kingdom
AI Governance Control Stack for Operational Stability: Achieving Hardened Governance in AI Systems
Mar 12, 2026Horatio MorganAI Governance AI Assurance
Morgan Signing House, AI Governance Architect
Clear, Compelling Arguments: Rethinking the Foundations of Frontier AI Safety Cases
Mar 8, 2026Shaun Feakins, Ibrahim Habli, Phillip MorganAI Safety AI Assurance
UKRI Centre for Doctoral Training in Safe AI Systems (SAINTS) Institute for Safe Autonomy Deramore Ln, York YO10 5GH · UKRI Centre for Doctoral Training in Safe AI Systems (SAINTS) The York Law School Freboys Ln, York YO10 5GD
Defining Operational Conditions for Safety-Critical AI-Based Systems from Data
Jan 29, 2026Johann Maximilian Christensen, Elena Hoemann, Frank Köster +1AI Assurance AI Safety
Institute for AI Safety and Security · German Aerospace Center (DLR) · Sankt Augustin, Germany
Operationalising AI Regulatory Sandboxes: Activities, Requirements, and Technical Assessment under the EU AI Act
Sep 27, 2025Alessio Buscemi, Thibault Simonetto, Daniele Pagani +3AI Assurance AI Governance
Luxembourg Institute of Science and Technology (LIST) · University of Luxembourg

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Autonomous Systems Dependability in the era of AI: Design Challenges in Safety, Security, Reliability and Certification

Behnaz Ranjbar, Kirankumar Raveendiran, Sudeep Pasricha, Samarjit Chakraborty+2

Chair of Embedded Systems, Ruhr Universität Bochum, Germany · Colorado State University, US · The University of North Carolina at Chapel Hill, US, and The TUM Institute for Advanced Study, Germany+1

AI Assurance Safety-Critical Control

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The design of embedded safety-critical systems such as those used in next-generation automotive and autonomous platforms, is increasingly challenged by escalating system complexity, hardware-software heterogeneity, and the integration of intelligent, data-driven components. Ensuring dependability in such systems requires a holistic approach that spans multiple abstraction layers and encompasses both design- and run-time assurance. Traditional methods for reliability, safety, and security management often fall short in addressing the dynamic and uncertain behaviors introduced by Artificial Intelligence (AI) and Machine Learning (ML) components, especially under stringent real-time, power, and safety constraints. While AI and ML offer powerful predictive, adaptive, and self-optimizing capabilities that can enhance system dependability, their inherent non-determinism, data-dependence, and lack of formal guarantees introduce new challenges for verification, validation, and certification. This paper explores emerging methodologies, architectures, and frameworks for designing dependable autonomous and embedded systems in the era of AI. It highlight advances in reliability modeling, secure system design, and certification approaches that account for imperfect, learning-enabled components, aiming to bridge the gap between AI innovation and certifiable system-level dependability.