Under monotonicity of outcomes in model performance, a new ML model's causal impact can be tightly bounded using only prior RCT data, with worst-case bounds that cannot be improved without more assumptions.
Safe policy learning through extrapolation: Application to pre-trial risk assessment
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Just Trial Once: Ongoing Causal Validation of Machine Learning Models
Under monotonicity of outcomes in model performance, a new ML model's causal impact can be tightly bounded using only prior RCT data, with worst-case bounds that cannot be improved without more assumptions.