167 citations · 520 across the 43 of their papers we have counts for
4 papers · 1 filter
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…
Breaking Barriers to Creative Expression: Co-Designing and Implementing an Accessible Text-to-Image Interface
Atieh Taheri, Mohammad Izadi, Gururaj Shriram +2
Text-to-image generation models have grown in popularity due to their ability to produce high-quality images from a text prompt. One use for this technology is to enable the creati…
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…