abstract

Better Supporting Workers in ML Workplaces

Authors:

Michael F. Clarke,

Joseph Gonzales,

Richard Harper,

Nozomi IkeyaAuthors Info & Claims

CSCW '19 Companion: Companion Publication of the 2019 Conference on Computer Supported Cooperative Work and Social Computing

Pages 443 - 448

https://doi.org/10.1145/3311957.3359429

Published: 09 November 2019 Publication History

Abstract

This workshop is aimed at bringing together a multidisciplinary group to discuss Machine Learning and its application in the workplace as a practical, everyday work matter. It's our hope this is a step toward helping us design better technology and user experiences to support the accomplishment of that work, while paying attention to workplace context. Despite advancement and investment in Machine Learning (ML) business applications, understanding workers in these work contexts have received little attention. As this category experiences dramatic growth, it's important to better understand the role that workers play, both individually and collaboratively, in a workplace where the output of prediction and machine learning is becoming pervasive. There is a closing window of opportunity to investigate this topic as it proceeds toward ubiquity. CSCW and HCI offer concepts, tools and methodologies to better understand and build for this future.

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Cited By

Ayobi AHughes JDuckworth CDylag JJames SMarshall PGuy MKumaran AChapman ABoniface MO'Kane A(2023)Computational Notebooks as Co-Design Tools: Engaging Young Adults Living with Diabetes, Family Carers, and Clinicians with Machine Learning ModelsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581424(1-20)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581424
Simsek Caglar PRoto VVainio T(2022)User Experience Research in the Work Context: Maps, Gaps and AgendaProceedings of the ACM on Human-Computer Interaction10.1145/35129796:CSCW1(1-28)Online publication date: 7-Apr-2022
https://dl.acm.org/doi/10.1145/3512979
Mahdavimoghaddam J(2022)The Utility of Social Media in Understanding the Future of WorkCompanion Publication of the 2022 Conference on Computer Supported Cooperative Work and Social Computing10.1145/3500868.3561397(219-222)Online publication date: 8-Nov-2022
https://dl.acm.org/doi/10.1145/3500868.3561397
Show More Cited By

Index Terms

Better Supporting Workers in ML Workplaces
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI theory, concepts and models

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Information & Contributors

Information

Published In

cover image ACM Conferences

CSCW '19 Companion: Companion Publication of the 2019 Conference on Computer Supported Cooperative Work and Social Computing

November 2019

562 pages

ISBN:9781450366922

DOI:10.1145/3311957

General Chairs:
Eric Gilbert
University of Michigan
,
Karrie Karahalios
University of Illinois, Urbana- Champaign

Copyright © 2019 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 November 2019

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Author Tags

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Abstract

Conference

CSCW '19

Sponsor:

SIGCHI

CSCW '19: Computer Supported Cooperative Work and Social Computing

November 9 - 13, 2019

TX, Austin, USA

Acceptance Rates

CSCW '19 Companion Paper Acceptance Rate 703 of 2,958 submissions, 24%;

Overall Acceptance Rate 2,235 of 8,521 submissions, 26%

Upcoming Conference

CSCW '25

Sponsor:
sigchi

Computer-Supported Cooperative Work and Social Computing

October 18 - 22, 2025

Bergen , Norway

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Cited By

Ayobi AHughes JDuckworth CDylag JJames SMarshall PGuy MKumaran AChapman ABoniface MO'Kane A(2023)Computational Notebooks as Co-Design Tools: Engaging Young Adults Living with Diabetes, Family Carers, and Clinicians with Machine Learning ModelsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581424(1-20)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581424
Simsek Caglar PRoto VVainio T(2022)User Experience Research in the Work Context: Maps, Gaps and AgendaProceedings of the ACM on Human-Computer Interaction10.1145/35129796:CSCW1(1-28)Online publication date: 7-Apr-2022
https://dl.acm.org/doi/10.1145/3512979
Mahdavimoghaddam J(2022)The Utility of Social Media in Understanding the Future of WorkCompanion Publication of the 2022 Conference on Computer Supported Cooperative Work and Social Computing10.1145/3500868.3561397(219-222)Online publication date: 8-Nov-2022
https://dl.acm.org/doi/10.1145/3500868.3561397
Küstermann GBittner E(2022)Leveraging Human and Machine Capabilities for Analyzing Citizen Contributions in Participatory Urban Planning and Development: A Design-Oriented ApproachHCI in Business, Government and Organizations10.1007/978-3-031-05544-7_5(56-72)Online publication date: 26-Jun-2022
https://dl.acm.org/doi/10.1007/978-3-031-05544-7_5
Mahdavimoghaddam JKrishnaswamy NBagheri E(2021)On the Congruence Between Online Social Content and Future IT Skill DemandProceedings of the ACM on Human-Computer Interaction10.1145/34795115:CSCW2(1-27)Online publication date: 18-Oct-2021
https://dl.acm.org/doi/10.1145/3479511

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