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 |
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| 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 | |
| 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 |
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Conference
| Conference | ACM CHI 2022 |
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| Country/Territory | United States |
| City | New Orleans, LA |
| Period | 30/04/22 → 5/05/22 |
| Internet address |