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The Unreasonable Effectiveness of Algorithms

Author

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  • Jens Ludwig
  • Sendhil Mullainathan
  • Ashesh Rambachan

Abstract

We calculate the social return on algorithmic interventions (specifically, their marginal value of public funds (MVPF)) across multiple domains of interest to economists—regulation, criminal justice, medicine, and education. Though these algorithms are different, the results are similar and striking. Each one has an MVPF of infinity: not only does it produce large benefits, it provides a "free lunch." We do not take these numbers to mean these interventions ought to be necessarily scaled but rather that much more research and development should be devoted to developing and carefully evaluating algorithmic solutions to policy problems.

Suggested Citation

  • Jens Ludwig & Sendhil Mullainathan & Ashesh Rambachan, 2024. "The Unreasonable Effectiveness of Algorithms," AEA Papers and Proceedings, American Economic Association, vol. 114, pages 623-627, May.
    • Handle: RePEc:aea:apandp:v:114:y:2024:p:623-27
    DOI: 10.1257/pandp.20241072
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    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • H43 - Public Economics - - Publicly Provided Goods - - - Project Evaluation; Social Discount Rate

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