Red Light, Grey Zone: Interactive narrative shifts how non-experts judge AV ethics

Researchers from multiple institutions (first author Mengyi Wei) have developed Red Light, Grey Zone, a web-based interactive narrative prototype designed to help non-experts engage with the ethical complexities of autonomous driving. Inspired by a real-world incident, the tool invites users to compare stakeholder perspectives, review scene evidence, and assign responsibility in ethically ambiguous scenarios. The team conducted an exploratory user study with 12 participants, measuring three dimensions: ethical cognition, responsibility-focused critical thinking, and multi-perspective reasoning.

Pre-post results showed the strongest self-reported improvement in responsibility-focused critical thinking among participants who completed the intended stakeholder-comparison process, with positive directional trends in the other two dimensions. Qualitatively, participants reflected on safety versus market trade-offs, responsibility ambiguity, transparency, privacy, and governance gaps. Many broadened their judgments from single-actor blame to more distributed accountability after comparing stakeholder views. The authors argue that such interactive narratives can serve as a public-facing method for eliciting situated ethical reflection on AI governance, especially where responsibility is shared across multiple actors.