AI can reveal and address institutional failures with careful evidence
From Protocols to Evidence: Bounded Claims for AI in Service of the Common Good
Machine Learning
Summary
AI does more than just raise concerns about how it is controlled; it can show where organizations are not responding well to people's needs. The authors explain that once AI is used, it can either help fix problems, make them worse, or hide them. Responsible use of AI means looking not only at the technology itself but also at the bigger system it affects. The paper suggests ways to make clear, limited claims about AI's impact based on solid evidence, and stresses the need for ongoing ethical and social judgment alongside technical work.
Artificial Intelligenceresponsible AIinstitutional failuresAI governancesystem evaluationevidence-bounded deploymentmeasurement-bounded governanceRISE AI frameworkcommon goodmoral judgment
Authors
Nitesh V. Chawla, Paulo Benanti
Abstract
Artificial Intelligence does more than create a governance problem. It can also reveal where institutions have already failed to provide responsiveness, belonging, care, and accountability. Once deployed, AI becomes an intervention in those conditions. It can repair, compound, substitute for, or conceal the failures it encounters. Responsible AI must therefore evaluate both the system and the institutional rupture into which it is introduced. The move from principles to protocols is already underway. The EU AI Act, NIST AI RMF, ISO/IEC 42001, and assurance practices translate commitments into roles, requirements, records, oversight, and assessment. The harder questions are what these protocols actually establish, whose power they leave untouched, and where measurement must stop. Pope Leo XIV's Magnifica Humanitas provides a broader moral frame centered on dignity, technological power, and the common good. Drawing on that frame, we develop a rupture test that links institutional baselines to system evaluation. We distinguish evidence-bounded deployment, which limits claims to what has actually been evaluated, from measurement-bounded governance, which records constraints that favorable evidence cannot override. Within those limits, RISE AI provides an architecture for making bounded, evidence-based claims about Responsibility, Inclusivity, Safety, and Empowerment. Responsible AI requires better engineering, institutional repair, and continued moral and political judgment.