What People See (and Miss) About Generative AI Risks: Perceptions of Failures, Risks, and Who Should Address Them

TL;DR

This study develops and validates a survey tool to assess public perceptions of Generative AI risks, failure modes, and stakeholder responsibilities, grounded in real incidents and scenarios.

Contribution

It introduces a validated survey instrument for measuring perceptions of GenAI risks, tailored to real-world contexts and useful for AI literacy and governance efforts.

Findings

The instrument effectively assesses risk awareness in current use contexts.

It is adaptable to new scenarios and emerging risks.

It can inform AI literacy tools and interventions.

Abstract

Despite growing concerns about the risks of Generative AI (GenAI), there is limited understanding of public perceptions of these risks and their associated failure modes -- defined as recurring patterns of sociotechnical breakdown across the GenAI lifecycle that contribute to risks of real-world harm. To address this gap, we present a survey instrument, validated with eight subject matter experts and deployed on a sample of 960 U.S.-based participants, to assess awareness and perceptions of GenAI's failure modes, their associated risks, and stakeholder responsibilities to address them. To support realism and content validity, our instrument is structured around scenarios grounded in publicly reported incidents and a taxonomy of GenAI's failure modes. Findings suggest that our instrument is (1) effective for assessing risk awareness and perceptions in a way that is grounded in people's current contexts of use, yet is extensible to new contexts that will inevitably arise; and (2) potentially useful for informing the design of AI literacy tools and interventions. We argue for AI literacy and governance approaches that align with how people encounter and reason about GenAI in everyday life.