Body and Wellbeing

会議の名前
CHI 2024
Critiquing Menstrual Pain Technologies through the Lens of Feminist Disability Studies
要旨

Menstrual pain or \textit{dysmenorrhea} refers to abdominal cramping or pain before and during menstruation, causing a spectrum of discomfort among people who menstruate. Menstrual pain is often regarded as `female trouble', as a nuisance that gets dismissed or as a symptom requiring medical intervention. While there are FemTech products that explicitly attend to menstrual pain, they predominantly seek to hide it without accounting for the lived experience of this pain. In this paper we use feminist disability studies (FDS) as a critical analytical lens to reframe the understanding of menstrual pain. Using this lens, we conduct an interaction critique of FemTech market exemplars for alleviating menstrual pain. We then offer three design provocations to better design menstrual pain technology and call for designers to attend to menstrual pain as a cyclical, chronic lived experience with the potential of spurring leaky contagious coalitions.

受賞
Honorable Mention
著者
Joo Young Park
KTH Royal Institute of Technology, Stockholm, Sweden
Stacy Hsueh
KTH Royal Institute of Technology, Stockholm, Sweden
Nadia Campo Woytuk
KTH Royal Institute of Technology, Stockholm, Sweden
Xuni Huang
KTH Royal Institute of Technology , Stockholm , Sweden
Marianela Ciolfi Felice
KTH Royal Institute of Technology, Stockholm, Sweden
Madeline Balaam
KTH Royal Institute of Technology, Stockholm, Sweden
論文URL

https://doi.org/10.1145/3613904.3642691

動画
Enhancing Auto-Generated Baseball Highlights via Win Probability and Bias Injection Method
要旨

The automatic generation of sports highlight videos is emerging in both the sports entertainment domain and research community. Earlier methods for generating highlights rely on visual-audio cues or contextual cues, so they may not capture the overall flow of the game well. In this paper, we propose a technique based on Win Probability Added (WPA), an empirical sabermetric baseball statistic, to generate baseball highlights that can better reflect in-game dynamics. Additionally, we introduce methods for generating “biased” highlights toward one team by systematically manipulating WPAs. Through a mixed-method user study with 43 baseball enthusiasts, we found that participants evaluated WPA-based highlights more favorably than existing AI highlights. For (un)favorably biased highlights, the game result(win/loss) was the most dominating factor in user perception, but bias directions and strengths also had nuanced effects on them. Our work contributes to the development of automated tools for generating customized sports highlights.

著者
Kieun Park
Seoul National University, Seoul, Korea, Republic of
Hajin Lim
Seoul National University , Seoul, Korea, Republic of
Joonhwan Lee
Seoul National University, Seocho-gu, Seoul, Korea, Republic of
Bongwon Suh
Seoul National University, Seoul, Korea, Republic of
論文URL

https://doi.org/10.1145/3613904.3642021

動画
Understanding the Effect of Reflective Iteration on Individuals’ Physical Activity Planning
要旨

Many people do not get enough physical activity. Establishing routines to incorporate physical activity into people's daily lives is known to be effective, but many people struggle to establish and maintain routines when facing disruptions. In this paper, we build on prior self-experimentation work to assist people in establishing or improving physical activity routines using a framework we call “reflective iteration.” This framework encourages individuals to articulate, reflect upon, and iterate on high-level “strategies” that inform their day-to-day physical activity plans. We designed and deployed a mobile application, Planneregy, that implements this framework. Sixteen U.S. college students used the Planneregy app for 42 days to reflectively iterate on their weekly physical exercise routines. Based on an analysis of usage data and interviews, we found that the reflective iteration approach has the potential to help people find and maintain effective physical activity routines, even in the face of life changes and temporary disruptions.

著者
Kefan Xu
Georgia Institute of Technology, Atlanta , Georgia, United States
Xinghui (Erica) Yan
University of Michigan, Ann Arbor, Michigan, United States
Myeonghan Ryu
Georgia Institute of Technology, Atlanta, Georgia, United States
Mark W. Newman
U. of Michigan, Ann Arbor, Michigan, United States
Rosa I.. Arriaga
Georgia Institute of Technology, Atlanta, Georgia, United States
論文URL

https://doi.org/10.1145/3613904.3641937

動画
Sensible and Sensitive AI for Worker Wellbeing: Factors that Inform Adoption and Resistance for Information Workers
要旨

Algorithmic estimations of worker behavior are gaining popularity. Passive Sensing–enabled AI ( PSAI ) systems leverage behavioral traces from workers' digital tools to infer their experience. Despite their conceptual promise, the practical designs of these systems elicit tensions that lead to workers resisting adoption. This paper teases apart the monolithic representation of PSAI by investigating system components that maximize value and mitigate concerns. We conducted an interactive online survey using the Experimental Vignette Method. Using Linear Mixed-effects Models we found that PSAI systems were more acceptable when sensing digital time use or physical activity, instead of visual modes. Inferences using language were only acceptable in work-restricted contexts. Compared to insights into performance, workers preferred insights into mental wellbeing. However, they resisted systems that automatically forwarded these insights to others. Our findings provide a template to reflect on existing systems and plan future implementations of PSAI to be more worker-centered.

受賞
Best Paper
著者
Vedant Das Swain
Northeastern University, Boston, Massachusetts, United States
Lan Gao
University of Chicago, Chicago, Illinois, United States
Abhirup Mondal
Georgia Institute of Technology, Atlanta, Georgia, United States
Gregory D.. Abowd
Northeastern University, Boston, Massachusetts, United States
Munmun De Choudhury
Georgia Institute of Technology, Atlanta, Georgia, United States
論文URL

https://doi.org/10.1145/3613904.3642716

動画
Thrown from Normative Ground: Exploring the Potential of Disorientation as a Critical Methodological Strategy in HCI
要旨

We introduce the concept of disorientation as an emerging critical methodological strategy for design research in HCI. Disorientation is a phenomenological concept developed by queer feminist theorist Sarah Ahmed that acknowledges the spatio-embodied ‘orientations’ of societal and cultural norms and the queering potential of ‘disorientations’. We use humanistic close reading to analyze three examples from queer, feminist, and more-than-human work in HCI. Our interpretation focuses on how HCI researchers utilize disorientation as a methodological strategy for questioning norms of technologies as well as generatively, toward alternatives. We discuss the tenets of disorientation and several tactics we saw emerge in practice for other practitioners to build upon. Finally, we reflect on implications for the field, as disorientation requires vulnerability and willingness to undergo change, acknowledges embodied knowledge that emerges before interpretation, and suggests the possibility of generative and alternative orientations stemming from those epistemological commitments.

著者
Heidi Biggs
Georgia Institute of Technology, Atlanta, Georgia, United States
Shaowen Bardzell
Georgia Institute of Technology, Atlanta, Georgia, United States
論文URL

https://doi.org/10.1145/3613904.3642724

動画