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Cited by 225Ethics and Social Impacts of AIInformation Systems Theories and ImplementationExplainable Artificial Intelligence (XAI)

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Trust in Data Science: Collaboration, Translation, and Accountability in Corporate Data Science Projects

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Passi, Samir, Jackson, Steven J.·2018·Proceedings of the ACM on Human-Computer Interaction
DOI 10.1145/3274405
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Abstract

The trustworthiness of data science systems in applied and real-world settings emerges from the resolution of specific tensions through situated, pragmatic, and ongoing forms of work. Drawing on research in CSCW, critical data studies, and history and sociology of science, and six months of immersive ethnographic fieldwork with a corporate data science team, we describe four common tensions in applied data science work: (un)equivocal numbers, (counter)intuitive knowledge, (in)credible data, and (in)scrutable models. We show how organizational actors establish and re-negotiate trust under messy and uncertain analytic conditions through practices of skepticism, assessment, and credibility. Highlighting the collaborative and heterogeneous nature of real-world data science, we show how the management of trust in applied corporate data science settings depends not only on pre-processing and quantification, but also on negotiation and translation. We conclude by discussing the implications of our findings for data science research and practice, both within and beyond CSCW.

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Metadata

Authors
Passi, S., & Jackson, S. J.
Affiliations
Cornell University (US)
ORCID
Passi, Samir
Venue
Proceedings of the ACM on Human-Computer Interaction
Publisher
Association for Computing Machinery (ACM)
Published
2018-11
Volume
2
Issue
CSCW
Pages
1-28
ISSN
2573-0142 (ISSN-L)
DOI
10.1145/3274405
OpenAlex
W4288083705
Cited by
225
References
100
Citations by year
2026: 18 · 2025: 34 · 2024: 34 · 2023: 38 · 2022: 39 · 2021: 32 · 2020: 24 · 2019: 6
FWCI
31.17
Type
journal article
Language
en
Open access
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations
  • Proceedings of the ACM on Human-Computer Interaction (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Funders
National Science Foundation (CHS-1526155)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
  • Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
  • Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
Keywords
applied data science, trust negotiation, credibility, skepticism, model interpretability, data quality, uncertainty, collaboration, critical data studies, sociology of science, computer-supported cooperative work

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