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Computer Science > Human-Computer Interaction

arXiv:2403.16795 (cs)
[Submitted on 25 Mar 2024]

Title:"We Have No Idea How Models will Behave in Production until
Production": How Engineers Operationalize Machine Learning

Authors:Shreya Shankar, Rolando Garcia, Joseph M Hellerstein, Aditya
G Parameswaran
View a PDF of the paper titled "We Have No Idea How Models will
Behave in Production until Production": How Engineers Operationalize
Machine Learning, by Shreya Shankar and 3 other authors
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    Abstract:Organizations rely on machine learning engineers (MLEs)
    to deploy models and maintain ML pipelines in production. Due to
    models' extensive reliance on fresh data, the operationalization
    of machine learning, or MLOps, requires MLEs to have proficiency
    in data science and engineering. When considered holistically,
    the job seems staggering -- how do MLEs do MLOps, and what are
    their unaddressed challenges? To address these questions, we
    conducted semi-structured ethnographic interviews with 18 MLEs
    working on various applications, including chatbots, autonomous
    vehicles, and finance. We find that MLEs engage in a workflow of
    (i) data preparation, (ii) experimentation, (iii) evaluation
    throughout a multi-staged deployment, and (iv) continual
    monitoring and response. Throughout this workflow, MLEs
    collaborate extensively with data scientists, product
    stakeholders, and one another, supplementing routine verbal
    exchanges with communication tools ranging from Slack to
    organization-wide ticketing and reporting systems. We introduce
    the 3Vs of MLOps: velocity, visibility, and versioning -- three
    virtues of successful ML deployments that MLEs learn to balance
    and grow as they mature. Finally, we discuss design implications
    and opportunities for future work.

Comments:          arXiv admin note: text overlap with
                   arXiv:2209.09125
Subjects:          Human-Computer Interaction (cs.HC)
Cite as:           arXiv:2403.16795 [cs.HC]
                   (or arXiv:2403.16795v1 [cs.HC] for this version)
                   https://doi.org/10.48550/arXiv.2403.16795
                   Focus to learn more
                   arXiv-issued DOI via DataCite
Journal reference: Proc. ACM Hum.-Comput. Interact. 8, CSCW1, Article
                   206 (April 2024)
                   https://doi.org/10.1145/3653697
Related DOI:       Focus to learn more
                   DOI(s) linking to related resources

Submission history

From: Rolando Garcia [view email]
[v1] Mon, 25 Mar 2024 14:13:43 UTC (1,954 KB)
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    View a PDF of the paper titled "We Have No Idea How Models will
    Behave in Production until Production": How Engineers
    Operationalize Machine Learning, by Shreya Shankar and 3 other
    authors
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