Toward Understanding Implications of AI‐Powered Intelligent Transportation Systems on Risk Research and Practice

The rapidly evolving use of artificial intelligence (AI)-powered intelligent transportation systems (ITS) and other emerging technologies in the transportation sector has the potential to deliver unprecedented improvements in safety and efficiency. However, recent research has also raised concerns about the implications of using AI and automation, as these technologies can introduce new, understudied risks to such systems. This perspective article evaluates AI-powered ITS through three lenses: risk assessment, concerning whether current conceptual and methodological tools remain sufficient for these systems; the human element, relating to how analysts and operators interact with AI outputs, including explainable AI (XAI) and human-in-the-loop oversight; and governance, concerning frameworks needed to manage these systems. Across these lenses, the article uses risk characterization as a diagnostic tool for locating where established risk practice must adapt and translates the resulting gaps into specific research directions. Although the practical interpretation and application of fundamental risk concepts may change when viewed through the lens of AI-powered ITS, the work of this article provides a basis for research directions and requirements needed for risk practice to adapt to new and emerging technologies and to support future research and training within the risk analysis community. This perspective will be of interest to risk researchers, practitioners, and policymakers.