[2602.24055] CIRCLE: A Framework for Evaluating AI from a Real-World Lens

Computer Science > Artificial Intelligence arXiv:2602.24055 (cs) [Submitted on 27 Feb 2026] Title:CIRCLE: A Framework for Evaluating AI from a Real-World Lens Authors:Reva Schwartz, Carina Westling, Morgan Briggs, Marzieh Fadaee, Isar Nejadgholi, Matthew Holmes, Fariza Rashid, Maya Carlyle, Afaf Taïk, Kyra Wilson, Peter Douglas, Theodora Skeadas, Gabriella Waters, Rumman Chowdhury, Thiago Lacerda View a PDF of the paper titled CIRCLE: A Framework for Evaluating AI from a Real-World Lens, by Reva Schwartz and Carina Westling and Morgan Briggs and Marzieh Fadaee and Isar Nejadgholi and Matthew Holmes and Fariza Rashid and Maya Carlyle and Afaf Ta\"ik and Kyra Wilson and Peter Douglas and Theodora Skeadas and Gabriella Waters and Rumman Chowdhury and Thiago Lacerda View PDF HTML (experimental) Abstract: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. While existing frameworks like MLOps focus on system stability and benchmarks measure abstract capabilities, decision-makers outside the AI stack lack systematic evidence about the behavior of AI technologies under real-world user variability and constraints. CIRCLE operationalizes the Validation phase of TEVV (Test, Evaluation, Verification, and Validation) by formalizing the translation of stakeholder concerns outside the stack into measurable signals. Unlike participatory design, which often remai...