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

Created by
  • Haebom

Author

Mackenzie Jorgensen, Kendall Brogle, Katherine M. Collins, Lujain Ibrahim, Arina Shah, Petra Ivanovic, Noah Broestl, Gabriel Piles, Paul Dongha, Hatim Abdulhussein, Adrian Weller, Jillian Powers, Umang Bhatt

Outline

As AI's social integration increases, this paper explores the governance mechanisms of deployed AI use cases. Unlike previous research that focuses on the risks of AI use, this paper introduces Fabric, a publicly accessible repository. The researchers collected 20 AI use cases through semi-structured interviews with practitioners and collaboratively designed AI workflow diagrams. The Fabric repository includes visual diagrams of AI use cases and descriptions of deployed systems, identifying gaps in AI governance and uncovering common patterns in human oversight of deployed AI systems. Fabric is intended to serve as a scalable and evolving tool for researchers studying the effectiveness of AI governance.

Takeaways, Limitations

Takeaways: Contributes to AI governance research by providing valuable data on the governance mechanisms of real-world AI use cases. It provides insights into the oversight and management of AI systems through the Fabric repository. It identifies vulnerabilities and common patterns in AI governance and suggests ways to improve them.
Limitations: Currently, only 20 AI use cases are included, limiting generalizability. The small sample size may insufficiently demonstrate statistical significance. Interview-based data may be subject to bias and subjectivity. The Fabric repository requires ongoing updates and maintenance.
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