The genie in the bottle: Different stakeholders, different interpretations of machine learning

Mahboobeh Harandi, Kevin Crowston, Corey Jackson, Carsten Oesterlund

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We explore how people developing or using a system with a machine-learning (ML) component come to understand the capabilities and challenges of ML. We draw on the social construction of technology (SCOT) tradition to frame our analysis of interviews and discussion board posts involving designers and users of a ML-supported citizen-science crowdsourcing project named Gravity Spy. We extend SCOT by anchoring our investigation in the different uses of the technology. We find that the type of understandings achieved by groups having less interaction with the technology is shaped more by outside influences and less by the specifics of the system and its role in the project. This initial understanding of how different participants understand and engage with ML points to challenges that need to be overcome to help users of a system deal with the opaque position that ML often holds in a work system.

Original languageEnglish (US)
Title of host publicationProceedings of the 53rd Annual Hawaii International Conference on System Sciences, HICSS 2020
EditorsTung X. Bui
PublisherIEEE Computer Society
Pages5871-5881
Number of pages11
ISBN (Electronic)9780998133133
StatePublished - 2020
Event53rd Annual Hawaii International Conference on System Sciences, HICSS 2020 - Maui, United States
Duration: Jan 7 2020Jan 10 2020

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume2020-January
ISSN (Print)1530-1605

Conference

Conference53rd Annual Hawaii International Conference on System Sciences, HICSS 2020
Country/TerritoryUnited States
CityMaui
Period1/7/201/10/20

ASJC Scopus subject areas

  • Engineering(all)

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