The Centers and Margins of Modeling Humans in Well-being Technologies

要旨

This paper critically examines the machine learning (ML) modeling of humans in three case studies of well-being technologies. Through a critical technical approach, it examines how these apps were experienced in daily life (technology in use) to surface breakdowns and to identify the assumptions about the “human” body entrenched in the ML models (technology design). To address these issues, this paper applies agential realism to decenter foundational assumptions, such as body regularity and health/illness binaries, and speculates more inclusive design and ML modeling paths that acknowledge irregularity, human-system entanglements, and uncertain transitions. This work is among the first to explore the implications of decentering theories in computational modeling of human bodies and well-being, offering insights for more inclusive technologies and speculations toward posthuman-centered ML modeling.

受賞
Honorable Mention
著者
Jichen Zhu
IT University of Copenhagen, Copenhagen, Denmark
Pedro Sanches
Umeå University, Umeå, Sweden
Vasiliki Tsaknaki
IT University of Copenhagen, Copenhagen, Denmark
Willem van der Maden
ITU Copenhagen, Copenhagen, Denmark
Irene Kaklopoulou
Umeå University, Umeå, Sweden
DOI

10.1145/3706598.3713940

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713940

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Health and Well-being

G303
7 件の発表
2025-04-30 01:20:00
2025-04-30 02:50:00
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