Forgetting Practices in the Data Sciences

Michael Muller; Angelika Strohmayer

doi:10.1145/3491102.3517644

Forgetting Practices in the Data Sciences

Michael Muller, Angelika Strohmayer

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

26 Citations (Scopus)

28 Downloads (Pure)

Abstract

HCI engages with data science through many topics and themes. Researchers have addressed biased dataset problems, arguing that bad data can cause innocent software to produce bad outcomes. But what if our software is not so innocent? What if the human decisions that shape our data-processing software, inadvertently contribute their own sources of bias? And what if our data-work technology causes us to forget those decisions and operations? Based in feminisms and critical computing, we analyze forgetting practices in data work practices. We describe diverse beneficial and harmful motivations for forgetting. We contribute: (1) a taxonomy of data silences in data work, which we use to analyze how data workers forget, erase, and unknow aspects of data; (2) a detailed analysis of forgetting practices in machine learning; and (3) an analytic vocabulary for future work in remembering, forgetting, and erasing in HCI and the data sciences.

Original language	English
Title of host publication	CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Editors	Simone Barbosa, Cliff Lampe, Caroline Appert , David A. Shamma, Steven Drucker, Julie Williamson, Koji Yatani
Place of Publication	New York, NY, United States
Publisher	ACM
Pages	19-19
Number of pages	19
ISBN (Electronic)	9781450391573
ISBN (Print)	9781450391573
DOIs	https://doi.org/10.1145/3491102.3517644
Publication status	Published - 29 Apr 2022
Event	ACM CHI 2022 - 900 Convention Center Blvd, New Orleans, LA, United States Duration: 30 Apr 2022 → 5 May 2022 https://chi2022.acm.org/

Publication series

Name	Conference on Human Factors in Computing Systems - Proceedings

Conference

Conference	ACM CHI 2022
Country/Territory	United States
City	New Orleans, LA
Period	30/04/22 → 5/05/22
Internet address	https://chi2022.acm.org/

Keywords

datasets
gaze detection
neural networks
text tagging

Access to Document

10.1145/3491102.3517644

CHI_2022_Forgetting_practices_in_the_data_sciences-preprintAccepted author manuscript, 661 KB

Cite this

Muller, M., & Strohmayer, A. (2022). Forgetting Practices in the Data Sciences. In S. Barbosa, C. Lampe, C. A., D. A. Shamma, S. Drucker, J. Williamson, & K. Yatani (Eds.), CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (pp. 19-19). Article 323 (Conference on Human Factors in Computing Systems - Proceedings). ACM. https://doi.org/10.1145/3491102.3517644

Muller, Michael ; Strohmayer, Angelika. / Forgetting Practices in the Data Sciences. CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. editor / Simone Barbosa ; Cliff Lampe ; Caroline Appert ; David A. Shamma ; Steven Drucker ; Julie Williamson ; Koji Yatani. New York, NY, United States : ACM, 2022. pp. 19-19 (Conference on Human Factors in Computing Systems - Proceedings).

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Muller, M & Strohmayer, A 2022, Forgetting Practices in the Data Sciences. in S Barbosa, C Lampe, CA, DA Shamma, S Drucker, J Williamson & K Yatani (eds), CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems., 323, Conference on Human Factors in Computing Systems - Proceedings, ACM, New York, NY, United States, pp. 19-19, ACM CHI 2022, New Orleans, LA, United States, 30/04/22. https://doi.org/10.1145/3491102.3517644

Forgetting Practices in the Data Sciences. / Muller, Michael; Strohmayer, Angelika.
CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. ed. / Simone Barbosa; Cliff Lampe; Caroline Appert; David A. Shamma; Steven Drucker; Julie Williamson; Koji Yatani. New York, NY, United States: ACM, 2022. p. 19-19 323 (Conference on Human Factors in Computing Systems - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Muller, Michael

AU - Strohmayer, Angelika

PY - 2022/4/29

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N2 - HCI engages with data science through many topics and themes. Researchers have addressed biased dataset problems, arguing that bad data can cause innocent software to produce bad outcomes. But what if our software is not so innocent? What if the human decisions that shape our data-processing software, inadvertently contribute their own sources of bias? And what if our data-work technology causes us to forget those decisions and operations? Based in feminisms and critical computing, we analyze forgetting practices in data work practices. We describe diverse beneficial and harmful motivations for forgetting. We contribute: (1) a taxonomy of data silences in data work, which we use to analyze how data workers forget, erase, and unknow aspects of data; (2) a detailed analysis of forgetting practices in machine learning; and (3) an analytic vocabulary for future work in remembering, forgetting, and erasing in HCI and the data sciences.

AB - HCI engages with data science through many topics and themes. Researchers have addressed biased dataset problems, arguing that bad data can cause innocent software to produce bad outcomes. But what if our software is not so innocent? What if the human decisions that shape our data-processing software, inadvertently contribute their own sources of bias? And what if our data-work technology causes us to forget those decisions and operations? Based in feminisms and critical computing, we analyze forgetting practices in data work practices. We describe diverse beneficial and harmful motivations for forgetting. We contribute: (1) a taxonomy of data silences in data work, which we use to analyze how data workers forget, erase, and unknow aspects of data; (2) a detailed analysis of forgetting practices in machine learning; and (3) an analytic vocabulary for future work in remembering, forgetting, and erasing in HCI and the data sciences.

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Muller M, Strohmayer A. Forgetting Practices in the Data Sciences. In Barbosa S, Lampe C, CA, Shamma DA, Drucker S, Williamson J, Yatani K, editors, CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. New York, NY, United States: ACM. 2022. p. 19-19. 323. (Conference on Human Factors in Computing Systems - Proceedings). doi: 10.1145/3491102.3517644

Forgetting Practices in the Data Sciences

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Keywords

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