It is asserted that trustworthiness is a systems property, not a single algorithmic feature, and that realising it requires coordinated advances in explainability, uncertainty quantification, human–AI interaction design, failure detection, and domain-specific data governance.
The reality of deploying artificial intelligence in safety-critical systems, such as autonomous vehicles, medical diagnoses and weather forecasting, is considered, including how an AI's mathematical properties relate to its benefit and risk profile.
T. Kolda· Philosophical transactions....· 1 citation
Synthesizing across four constraint-bound engineering domains, agentic AI trustworthiness is shown to be a single problem, with a path outlined toward a reusable, cross-domain assurance framework analogous to the graded certification regimes used by mature safety-critical engineering fields.
Omar Al-Refai, Ibrahim Shahbaz, A. Husseinat et al.· arXiv.org· 1 citation
It is argued that agentic AI should be approached as a socio-technical design problem, where interfaces, oversight mechanisms, and evaluation practices are as critical as algorithms.
Timothy Merritt, Alejandro Jarabo-Peñas, Juan Bravo-Arrabal et al.· 0 citations
The surging deployment of Artificial Intelligence (AI) systems across safety-critical sectors — namely healthcare diagnostics, autonomous driving, aircraft regulation, and industrial automation — has resulted in a burgeoning need for transparent decision-making frameworks capable of justifiability and accountability. T...
Sajjan Choudhuri, A. Agade, Rahul Reddy Gouravaram et al.· 2026 International Conferenc...· 0 citations
The paper describes an approach to automated dynamic operational alignment in a complex high-risk process, exemplified by a case study on autonomous drilling, and possible sources of AI misalignments are discussed.
R. Mihai, Benoit Daireaux, E. Cayeux· Scientific Reports· 0 citations
Improvements in accuracy, robustness, interpretability, and SLA compliance are confirmed as significant, demonstrating that IRED-AI’s enhancements are not incidental but systematically robust.
Thacha Lawanna· Engineering Journal· 0 citations
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