2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.CY2026
Real-World AI Evaluation: How FRAME Generates Systematic Evidence to Resolve the Decision-Maker's Dilemma
Reva Schwartz, Gabriella Waters
Organizational leaders are being asked to make high-stakes decisions about AI deployment without dependable evidence of what these systems actually do in the environments they over…
cs.AI2026★ 2 cited
CIRCLE: A Framework for Evaluating AI from a Real-World Lens
Reva Schwartz, Carina Westling, Morgan Briggs +12
This paper proposes CIRCLE, a six-stage, lifecycle-based framework to bridge the reality gap between model-centric performance metrics and AI's materialized outcomes in deployment.…
cs.CY2025
AI Biases as Asymmetries: A Review to Guide Practice
Gabriella Waters, Phillip Honenberger
The understanding of bias in AI is currently undergoing a revolution. Initially understood as errors or flaws, biases are increasingly recognized as integral to AI systems and some…