"This Whole Thing Smacks of Gender": Algorithmic Exclusion in Bioimpedance-based Body Composition Analysis
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Abstract (arXiv)
Smart weight scales offer bioimpedance-based body composition analysis as a supplement to pure body weight measurement. Companies such as Withings and Fitbit tout composition analysis as providing self-knowledge and the ability to make more informed decisions. However, these aspirational statements elide the reality that these numbers are a product of proprietary regression equations that require a binary sex/gender as their input. Our paper combines transgender studies-influenced personal narrative with an analysis of the scientific basis of bioimpedance technology used as part of the Withings smart scale. Attempting to include nonbinary people reveals that bioelectrical impedance analysis has always rested on physiologically shaky ground. White nonbinary people are merely the tip of the iceberg of those who may find that their smart scale is not so intelligent when it comes to their bodies. Using body composition analysis as an example, we explore how the problem of trans and nonbinary inclusion in personal health tech goes beyond the issues of adding a third "gender" box or slapping a rainbow flag on the packaging. We also provide recommendations as to how to approach creating more inclusive technologies even while still relying on exclusionary data.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Jan 2021.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 0; 2025: 1.
3 papers.
- 2025The AI Model Risk Catalog: What Developers and Researchers Miss About Real-World AI Harmscited by 3
- 2022Sex Trouble: Common pitfalls in incorporating sex/gender in medical machine learning and how to avoid themcited by 1
- 2023Should they? Mobile Biometrics and Technopolicy meet Queer Community Considerationscited by 0
- 2025The AI Model Risk Catalog: What Developers and Researchers Miss About Real-World AI Harms21 Aug 2025
- 2023Should they? Mobile Biometrics and Technopolicy meet Queer Community Considerations6 Oct 2023
- 2022Sex Trouble: Common pitfalls in incorporating sex/gender in medical machine learning and how to avoid them15 Mar 2022