Bilal Alam Khan (Trinity College (Dublin)) et al. have posted “Designing an Ethical Multimodal Driver Monitoring Systems: Risk Mitigation, Incident Response, and Accountability in Automated Vehicles” on SSRN. Here is the abstract:
As vehicles transition toward higher levels of automation, Driver Monitoring Systems (DMS) have become essential for ensuring human oversight, safety, and regulatory compliance. These systems rely on multimodal sensing and AI-driven inference to assess driver attention, cognitive state, and readiness to take control. While technologically promising, their deployment introduces a complex set of ethical and legal challenges – ranging from privacy and consent to data ownership and algorithmic fairness. While overarching frameworks such as the GDPR, EU AI Act, and IEEE standards offer important guidance, they lack the specificity required for addressing the unique risks posed by in-cabin sensing technologies. This paper addresses this gap by identifying key ethical challenges specific to AI-powered DMS and proposing a comprehensive, modular framework for ethical design, deployment, and governance. It introduces practical design responses – such as user-configurable consent pathways, fairness-aware model training, explainability tools, and emotional well-being safeguards – grounded in established legal and ethical principles. Finally, the paper outlines a risk analysis and failure mitigation strategy, emphasizing proactive incident response and accountability mechanisms tailored to the DMS context. Together, these contributions aim to inform the development of transparent, trustworthy, and human-centered driver monitoring systems for next-generation autonomous vehicles.