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  • CSCW 2020WorkshoponML

    Rights statement: © ACM, 2019. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in CSCW '19 Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing, http://doi.acm.org/10.1145/3311957.3359429

    Accepted author manuscript, 124 KB, PDF document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

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Better supporting workers in ML workplaces

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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Better supporting workers in ML workplaces. / Clarke, M.F.; Gonzales, J.; Randall, D. et al.
CSCW '19 Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing. New York: ACM, 2019. p. 443-448.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Clarke, MF, Gonzales, J, Randall, D, Ludwig, T, Harper, R & Ikeya, N 2019, Better supporting workers in ML workplaces. in CSCW '19 Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing. ACM, New York, pp. 443-448. https://doi.org/10.1145/3311957.3359429

APA

Clarke, M. F., Gonzales, J., Randall, D., Ludwig, T., Harper, R., & Ikeya, N. (2019). Better supporting workers in ML workplaces. In CSCW '19 Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing (pp. 443-448). ACM. https://doi.org/10.1145/3311957.3359429

Vancouver

Clarke MF, Gonzales J, Randall D, Ludwig T, Harper R, Ikeya N. Better supporting workers in ML workplaces. In CSCW '19 Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing. New York: ACM. 2019. p. 443-448 doi: 10.1145/3311957.3359429

Author

Clarke, M.F. ; Gonzales, J. ; Randall, D. et al. / Better supporting workers in ML workplaces. CSCW '19 Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing. New York : ACM, 2019. pp. 443-448

Bibtex

@inproceedings{6224d46dcb844f25b41c4fc23b18c417,
title = "Better supporting workers in ML workplaces",
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.",
author = "M.F. Clarke and J. Gonzales and D. Randall and T. Ludwig and R. Harper and N. Ikeya",
note = "{\textcopyright} ACM, 2019. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in CSCW '19 Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing, http://doi.acm.org/10.1145/3311957.3359429",
year = "2019",
month = nov,
day = "13",
doi = "10.1145/3311957.3359429",
language = "English",
isbn = "9781450366922",
pages = "443--448",
booktitle = "CSCW '19 Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing",
publisher = "ACM",

}

RIS

TY - GEN

T1 - Better supporting workers in ML workplaces

AU - Clarke, M.F.

AU - Gonzales, J.

AU - Randall, D.

AU - Ludwig, T.

AU - Harper, R.

AU - Ikeya, N.

N1 - © ACM, 2019. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in CSCW '19 Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing, http://doi.acm.org/10.1145/3311957.3359429

PY - 2019/11/13

Y1 - 2019/11/13

N2 - 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.

AB - 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.

U2 - 10.1145/3311957.3359429

DO - 10.1145/3311957.3359429

M3 - Conference contribution/Paper

SN - 9781450366922

SP - 443

EP - 448

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

PB - ACM

CY - New York

ER -