Documenting Deployment with Fabric: A Repository of Real-World AI Governance

2025-08-18

AI Summary

Existing AI governance research predominantly emphasizes risk critique, lacking systematic empirical documentation of governance practices in real-world deployment contexts. Method: We introduce Fabric—the first scalable, visualizable repository of real-world AI governance cases—built through semi-structured interviews and collaborative workflow modeling to systematically capture, structure, and visualize governance mechanisms, oversight measures, and implementation constraints across 20 deployed AI applications. Contribution/Results: Fabric innovatively operationalizes AI governance practice into a searchable, comparable, and extensible visual case database. It identifies recurrent human oversight patterns (e.g., manual review, threshold-based intervention) and structural gaps (e.g., absent feedback loops, ambiguous accountability). Open-sourced, Fabric provides an empirical foundation and evolving platform for evidence-based AI governance research, policy formulation, and tool development.

Technology Category

• Philosophy and Ethics of AI: AI & Law, Justice, Regulation & Governance
• Humans and AI: Other Foundations of Human Computation & AI
• Computer Vision: Bias, Fairness & Privacy

Application Category

• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Security and Privacy: Data transparency and provenance

Abstract

Artificial intelligence (AI) is increasingly integrated into society, from financial services and traffic management to creative writing. Academic literature on the deployment of AI has mostly focused on the risks and harms that result from the use of AI. We introduce Fabric, a publicly available repository of deployed AI use cases to outline their governance mechanisms. Through semi-structured interviews with practitioners, we collect an initial set of 20 AI use cases. In addition, we co-design diagrams of the AI workflow with the practitioners. We discuss the oversight mechanisms and guardrails used in practice to safeguard AI use. The Fabric repository includes visual diagrams of AI use cases and descriptions of the deployed systems. Using the repository, we surface gaps in governance and find common patterns in human oversight of deployed AI systems. We intend for Fabric to serve as an extendable, evolving tool for researchers to study the effectiveness of AI governance.

Problem

• Documenting real-world AI governance mechanisms in deployment
• Identifying gaps and patterns in human oversight of AI systems
• Creating a repository for studying effectiveness of AI governance

Innovation

• Public repository for AI governance documentation
• Co-designed workflow diagrams with practitioners
• Semi-structured interviews collecting real use cases