Simple Rules for Complex Decisions

9 Pages Posted: 17 Feb 2017

See all articles by Jongbin Jung

Jongbin Jung

Stanford University, School of Engineering, Management Science & Engineering, Students

Connor Concannon

CUNY, John Jay College of Criminal Justice

Ravi Shroff

New York University (NYU)

Sharad Goel

Stanford University

Daniel G. Goldstein

Microsoft Research New York City; London Business School

Date Written: February 16, 2017

Abstract

From doctors diagnosing patients to judges setting bail, experts often base their decisions on experience and intuition rather than on statistical models. While understandable, relying on intuition over models has often been found to result in inferior outcomes. Here we present a new method-select-regress-and-round-for constructing simple rules that perform well for complex decisions. These rules take the form of a weighted checklist, can be applied mentally, and nonetheless rival the performance of modern machine learning algorithms. Our method for creating these rules is itself simple, and can be carried out by practitioners with basic statistics knowledge. We demonstrate this technique with a detailed case study of judicial decisions to release or detain defendants while they await trial. In this application, as in many policy settings, the effects of proposed decision rules cannot be directly observed from historical data: if a rule recommends releasing a defendant that the judge in reality detained, we do not observe what would have happened under the proposed action. We address this key counterfactual estimation problem by drawing on tools from causal inference. We find that simple rules significantly outperform judges and are on par with decisions derived from random forests trained on all available features. Generalizing to 22 varied decision-making domains, we find this basic result replicates. We conclude with an analytical framework that helps explain why these simple decision rules perform as well as they do.

Keywords: Interpretable Models, Policy Evaluation, Causal Inference

Suggested Citation

Jung, Jongbin and Concannon, Connor and Shroff, Ravi and Goel, Sharad and Goldstein, Daniel G., Simple Rules for Complex Decisions (February 16, 2017). Available at SSRN: https://ssrn.com/abstract=2919024 or http://dx.doi.org/10.2139/ssrn.2919024

Jongbin Jung (Contact Author)

Stanford University, School of Engineering, Management Science & Engineering, Students ( email )

473 Via Ortega
Stanford, CA 94305-9025
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Connor Concannon

CUNY, John Jay College of Criminal Justice ( email )

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Ravi Shroff

New York University (NYU) ( email )

Bobst Library, E-resource Acquisitions
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Sharad Goel

Stanford University ( email )

475 Via Ortega
Stanford, CA 94305
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Daniel G. Goldstein

Microsoft Research New York City ( email )

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London Business School ( email )

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HOME PAGE: http://www.dangoldstein.com

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