Placeholder to discuss the details of designing a algorithms that learn to complement humans.
- Lauren Oakden-Rayner, No Doctor Required: Autonomy, Anomalies, and Magic Puddings
- Machine learning for medical imaging: methodological failures and recommendations for the future
- Impact of artificial intelligence on pathologists’ decisions: an experiment
- Are Model Explanations Useful in Practice? Rethinking How to Support Human-ML Interactions.
- How to Make Tech Products (that Don't Cause Depression and War)
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Charusaie, Mohammad-Amin, Hussein Mozannar, David Sontag, and Samira Samadi. 2022. “Sample Efficient Learning of Predictors That Complement Humans.” In Proceedings of the 39th International Conference on Machine Learning, 2972–3005. PMLR.
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