> ML_LITERATURE // MITCHELL-2019-MODEL-CARDS-FOR-MODEL-REPORTING_v1.0
Model Cards for Model Reporting
Margaret Mitchell, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, Timnit Gebru · ACM Conference on Fairness, Accountability, and Transparency (FAccT) (2019)
standard-technical-report2019industry-standardartifactsAvailable
Principal Contribution
Introduced Model Cards: structured transparent reporting of model intended use, evaluation benchmarks, performance across demographic subsets, and ethical caveats.
Operational Relevance
Directly guides deployment choices and architecture selection for task-model-governance, task-fairness-audit.
Assumptions
- Standard empirical regularity and statistical stability hold across evaluation domains
Limitations
- Performance characteristics depend on domain distribution and compute allocation parameters
Connected Algorithms, Architectures & Tools
Related Algorithms:
Related Architectures:
Implementing Libraries: