Outsourcing in the Age of Machine Learning: How Inscrutable Shared Understanding Drives Outsourcing Relationship Success

Date

2024-01-03

Contributor

Advisor

Department

Instructor

Depositor

Speaker

Researcher

Consultant

Interviewer

Narrator

Transcriber

Annotator

Journal Title

Journal ISSN

Volume Title

Publisher

Volume

Number/Issue

Starting Page

6707

Ending Page

Alternative Title

Abstract

Anchored in the IS outsourcing literature, shared understanding between the client firm and the provider has been consistently reported to support successful outsourcing engagement. A lack of shared understanding, on the other hand, is linked to deteriorating performance. In this study, we examined how shared understanding changed throughout an outsourcing engagement between a Bank (the client) and a Machine Learning (ML) service provider. Based on a longitudinal qualitative study of ML service outsourcing, from both client and provider perspectives, we found that in the early stage of the outsourcing relationship the parties bestowed shared understanding. However, in the later stages a different form of shared understanding evolved in which the ML provider intentionally limited information about how the ML model works, while the client ‘blackboxed’ the technology, while focusing on increasing the supply of data required to train the ML model and verifying its outcome. We theorize that ‘inscrutable shared understanding’ emerged in this ML outsourcing service and point out three practices pursued by the client and provider to support this new form of shared understanding.

Description

Keywords

Socio-Technical Issues in Organizational Information Technologies, inscrutability, machine learning, outsourcing, shared understanding

Citation

Extent

10 pages

Format

Geographic Location

Time Period

Related To

Proceedings of the 57th Hawaii International Conference on System Sciences

Related To (URI)

Table of Contents

Rights

Attribution-NonCommercial-NoDerivatives 4.0 International

Rights Holder

Local Contexts

Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.