Machine learning informed decision-making with interpreted model's outputs: A field intervention

Leid Zejnilović, Susana Lavado, Carlos Soares, Íñigo Martínez de Rituerto De Troya, Andrew Bell, Rayid Ghani

Research output: Contribution to conferencePaperpeer-review

Abstract

Despite having set the theoretical ground for explainable systems decades ago, the information system scholars have given little attention to new developments in the decision-making with humans-in-the-loop in real-world problems. We take the sociotechnical system lenses and employ mixed-method analysis of a field intervention to study the machine-learning informed decision-making with interpreted models' outputs. Contrary to theory, our results suggest a small positive effect of explanations on confidence in the final decision, and a negligible effect on the decisions' quality. We uncover complex dynamic interactions between humans and algorithms, and the interplay of algorithmic aversion, trust, experts' heuristic, and changing uncertainty-resolving condititions.

Original languageEnglish
Pages175912
DOIs
Publication statusPublished - 2021
Event81st Annual Meeting of the Academy of Management 2021: Bringing the Manager Back in Management, AoM 2021 - Virtual, Online
Duration: 29 Jul 20214 Aug 2021

Conference

Conference81st Annual Meeting of the Academy of Management 2021: Bringing the Manager Back in Management, AoM 2021
CityVirtual, Online
Period29/07/214/08/21

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