Session title
Ensuring Fair and Effective AI-Based Photographic Traffic Enforcement
Synopsis
The integration of Artificial Intelligence (AI) into photographic traffic enforcement systems has introduced a new frontier in road safety and regulatory efficiency. By automating critical tasks such as infringement detection, evidence analysis, adjudication, and infringement issuance, AI holds the potential to enhance the scalability, consistency, and reliability of enforcement systems. However, these benefits come with significant socio-legal and technical implications that must be addressed through structured governance, robust validation processes, and ongoing stakeholder engagement. This paper provides a detailed exploration of how AI technologies are applied in traffic enforcement contexts, the associated risks and advantages, and the mechanisms required to ensure their accuracy, legality, and public acceptability. Emphasis is placed on the importance of Explainable AI (XAI), adherence to ISO/IEC 42001:2023 standards for AI governance, and the necessity of transparency in decision-making. By synthesising global best practices, current deployments, and future pathways, the paper offers a comprehensive guide for decision-makers, engineers, and legal authorities tasked with implementing or regulating AI-based enforcement systems.
Agenda
| Time | Presentation title | Speaker |
| 12:30 | Intro: How AI in Photo Enforcement Works | Lee Davey |
| 12:35 | Opportunities, Risk, and Challenges | Mohi Khalili |
| 12:40 | Compliance: Accuracy, Validation, and Continuous Improvement | Mohi Khalili |
| 12:45 | A Framework for Responsible Deployment | Lee Davey |
| 12:55 | Q&A + Close | All |
| 1:00 | Session End | – |
Session Chairs: Lee Davey and Mohi Khalili