Cyber & IT Supervisory Forum - Additional Resources

References Bd. Governors Fed. Rsrv. Sys., Supervisory Guidance on Model Risk Management, SR Letter 11-7 (Apr. 4, 2011). Off. Comptroller Currency, Comptroller’s Handbook: Model Risk Management (Aug. 2021). Margaret Mitchell et al., “Model Cards for Model Reporting.” Proceedings of 2019 FATML Conference. Timnit Gebru et al., “Datasheets for Datasets,” Communications of the ACM 64, No. 12, 2021. Emily M. Bender, Batya Friedman, Angelina McMillan-Major (2022). A Guide for Writing Data Statements for Natural Language Processing. University of Washington. Accessed July 14, 2022. M. Arnold, R. K. E. Bellamy, M. Hind, et al. FactSheets: Increasing trust in AI services through supplier’s declarations of conformity. IBM Journal of Research and Development 63, 4/5 (July-September 2019), 6:1-6:13. Navdeep Gill, Abhishek Mathur, Marcos V. Conde (2022). A Brief Overview of AI Governance for Responsible Machine Learning Systems. ArXiv, abs/2211.13130. John Richards, David Piorkowski, Michael Hind, et al. A Human-Centered Methodology for Creating AI FactSheets. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering. Christoph Molnar, Interpretable Machine Learning, lulu.com. David A. Broniatowski. 2021. Psychological Foundations of Explainability and Interpretability in Artificial Intelligence. National Institute of Standards and Technology (NIST) IR 8367. National Institute of Standards and Technology, Gaithersburg, MD. OECD (2022), “OECD Framework for the Classification of AI systems”, OECD Digital Economy Papers, No. 323, OECD Publishing, Paris.

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