124 citations · 162 across the 17 of their papers we have counts for
6 papers · 1 filter
Towards A Framework for Levels of Anthropomorphic Deception in Robots and AI
Franziska Babel, Shane Saunderson, Shalaleh Rismani
This paper presents a preliminary draft of a framework around the use of anthropomorphic deception, defined here as misleading users towards humanlike affordances in the design of…
From Use to Oversight: How Mental Models Influence User Behavior and Output in AI Writing Assistants
Shalaleh Rismani, Su Lin Blodgett, Q. Vera Liao +2
AI-based writing assistants are ubiquitous, yet little is known about how users' mental models shape their use. We examine two types of mental models -- functional or related to wh…
Measuring What Matters: Connecting AI Ethics Evaluations to System Attributes, Hazards, and Harms
Shalaleh Rismani, Renee Shelby, Leah Davis +2
Over the past decade, an ecosystem of measures has emerged to evaluate the social and ethical implications of AI systems, largely shaped by high-level ethics principles. These meas…
From plane crashes to algorithmic harm: applicability of safety engineering frameworks for responsible ML
Shalaleh Rismani, Renee Shelby, Andrew Smart +4
Inappropriate design and deployment of machine learning (ML) systems leads to negative downstream social and ethical impact -- described here as social and ethical risks -- for use…
Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction
Renee Shelby, Shalaleh Rismani, Kathryn Henne +8
Understanding the landscape of potential harms from algorithmic systems enables practitioners to better anticipate consequences of the systems they build. It also supports the pros…
Driver perceptions of advanced driver assistance systems and safety
Sophie Le Page, Jason Millar, Kelly Bronson +2
Advanced driver assistance systems (ADAS) are often used in the automotive industry to highlight innovative improvements in vehicle safety. However, today it is unclear whether cer…