Predicting decision-makers’ algorithm use

Marvin Neumann*, A. Susan M. Niessen, Rob R. Meijer

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Decision makers typically integrate multiple pieces of information to make predictions and decisions. They also sometimes receive algorithmic advice, but often discount such advice. This usually results in less consistent and less accurate predictions than consistently using the advice. We hypothesized that individual differences on psychological traits such as dutifulness (a facet of conscientiousness), decision-making styles, and predictor validity beliefs are related to the consistent use of algorithmic advice, judgment consistency, and predictive validity. We sampled participants with hiring experience (N = 308) who predicted the performance of job applicants based on test scores and interview ratings, and they also received algorithmic advice. The results showed that more dutiful participants and participants with more accurate predictor validity beliefs used the algorithm more, and made more consistent and more accurate predictions. We did not find evidence that an intuitive decision-making style was related to these outcomes. Exploratory analyses showed that cognitive ability was positively related to the consistent use of algorithmic advice and judgment consistency, but not significantly related to predictive validity. Furthermore, the other conscientiousness facets and the general factor were similarly related to the outcome variables as dutifulness. Organizations may want to hire conscientious decision makers, and decision makers with accurate predictor validity beliefs. In addition, organizations could provide training on predictor validities.

Original languageEnglish
Article number107759
Pages (from-to)1-9
Number of pages9
JournalComputers in Human Behavior
Volume145
Early online date25 Mar 2023
DOIs
Publication statusPublished - Aug 2023

Bibliographical note

Funding Information:
We thank Edgar Kausel for sharing the applicant data with us and Sophia Paczulla for assisting in the data collection.

Publisher Copyright:
© 2023 The Authors

Keywords

  • Advice taking
  • Algorithm aversion
  • Algorithm use
  • Decision making
  • Holistic and mechanical prediction
  • Individual differences
  • Predictive validity

Fingerprint

Dive into the research topics of 'Predicting decision-makers’ algorithm use'. Together they form a unique fingerprint.

Cite this