AI Trustworthiness and Risk Assessment for Challenged Contexts

The Workshop on AI Trustworthiness and Risk Assessment for Challenged Contexts addresses one of the most pressing challenges facing AI deployment: ensuring that AI systems are reliable, safe, and accountable when deployed in difficult or adversarial environments. The workshop covers technical methods for assessing AI trustworthiness — including robustness testing, uncertainty quantification, and formal verification — alongside risk assessment frameworks tailored to high-stakes or resource-constrained deployment contexts such as conflict zones, disaster response, and critical infrastructure. The event brings together AI safety researchers, practitioners, and policy experts.

artificial intelligence safety robustness trustworthiness

We invite submissions on AI robustness and reliability, uncertainty quantification in machine learning, adversarial examples and defenses, formal verification of AI systems, AI risk assessment frameworks, fairness and bias in challenged deployment contexts, safe reinforcement learning, AI governance for high-stakes applications, and case studies of AI deployment in resource-constrained or adversarial environments. Interdisciplinary contributions are strongly encouraged.