Why, when, and from whom: considerations for collecting and reporting race and ethnicity data in HCI

要旨

Engaging diverse participants in HCI research is critical for creating safe, inclusive, and equitable technology. However, there is a lack of guidelines on when, why, and how HCI researchers collect study participants' race and ethnicity. Our paper aims to take the first step toward such guidelines by providing a systematic review and discussion of the status quo of race and ethnicity data collection in HCI. Through an analysis of 2016--2021 CHI proceedings and a survey with 15 authors who published in these proceedings, we found that reporting race and ethnicity of participants is very rare (<3\%) and that researchers are far from consensus. Drawing from multidisciplinary literature and our findings, we devise considerations for HCI researchers to decide why, when, and from whom to collect race and ethnicity data. For truly inclusive, equitable technologies, we encourage deliberate decisions rather than default omissions.

受賞
Honorable Mention
著者
Yiqun T.. Chen
University of Washington, Seattle, Seattle, Washington, United States
Angela D. R.. Smith
University of Texas at Austin, Austin, Texas, United States
Katharina Reinecke
University of Washington, Seattle, Washington, United States
Alexandra To
Northeastern University, Boston, Massachusetts, United States
論文URL

https://doi.org/10.1145/3544548.3581122

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Inclusive Futures

Hall G2
6 件の発表
2023-04-24 23:30:00
2023-04-25 00:55:00