Optimized scoring systems: Toward trust in machine learning for healthcare and criminal justice

Journal Article (Journal Article)

Abstract. Questions of trust in machine-learning models are becoming increasingly important as these tools are starting to be used widely for high-stakes decisions in medicine and criminal justice. Transparency of models is a key aspect affecting trust. This paper reveals that there is new technology to build transparent machine-learning models that are often as accurate as black-box machine-learning models. These methods have already had an impact in medicine and criminal justice. This work calls into question the overall need for black-box models in these applications. Copyright:

Full Text

Duke Authors

Cited Authors

  • Rudin, C; Ustunb, B

Published Date

  • September 1, 2018

Published In

Volume / Issue

  • 48 / 5

Start / End Page

  • 449 - 466

Electronic International Standard Serial Number (EISSN)

  • 1526-551X

International Standard Serial Number (ISSN)

  • 0092-2102

Digital Object Identifier (DOI)

  • 10.1287/inte.2018.0957

Citation Source

  • Scopus