Cited by 136Innovative Human-Technology InteractionLGBTQ Health, Identity, and PolicyEthics and Social Impacts of AI

Designing Trans Technology: Defining Challenges and Envisioning Community-Centered Solutions

Haimson, Oliver L., Gorrell, Dykee, Starks, Denny L., Weinger, Zu·2020·Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Abstract

Transgender and non-binary people face substantial challenges in the world, ranging from social inequities and discrimination to lack of access to resources. Though technology cannot fully solve these problems, technological solutions may help to address some of the challenges trans people and communities face. We conducted a series of participatory design sessions (total N = 21 participants) to understand trans people's most pressing challenges and to involve this population in the design process. We detail four types of technologies trans people envision: technologies for changing bodies, technologies for changing appearances / gender expressions, technologies for safety, and technologies for finding resources. We found that centering trans people in the design process enabled inclusive technology design that primarily focused on sharing community resources and prioritized connection between community members.

Integrity signals

Registry

Crossref · 10.1145/3313831.3376669

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The authors did not measure intercoder reliability in line with similar qualitative and participatory design papers, following justification in [9].

    “We did not measure intercoder reliability in line with similar qualitative and participatory design papers [25, 69, 99], following the justification presented in [9].”
  • Enforcement of a project's CoC signals to vulnerable contributors whether they are truly welcomed and supported by the broader community.

    “Enforcement of a project's CoC signals to vulnerable contributors whether they are truly welcomed and supported by the broader community [10].”

    From Codes of Conduct in Open Source (2024) · cites this paper as [10]

  • Work by DeVito and Haimson indicate the importance of safety online for trans people as they become increasingly comfortable with representing their identity.

    “Work by DeVito and Haimson indicate the importance of safety online for trans people as they become increasingly comfortable with representing their identity [23, 40].”

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Haimson, O. L., Gorrell, D., Starks, D. L., & Weinger, Z.
Affiliations
  • University of Michigan (US)
  • University of Illinois Urbana-Champaign (US)
Venue
Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2020-04-21
Pages
1-13
OpenAlex
W3004917411
Cited by
136
References
1
Citations by year
2026: 18 · 2025: 30 · 2024: 34 · 2023: 16 · 2022: 19 · 2021: 17 · 2020: 2
FWCI
9.86
Type
conference paper
Language
en
Open access
closed
Locations
CHI Conference on Human Factors in Computing Systems (publishedVersion)
Funders
Institute for Research on Women and Gender, University of Michigan (U065642)
Topics
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
  • Social Sciences › Psychology › Social Psychology › LGBTQ Health, Identity, and Policy
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
Keywords
transgender people, non-binary people, inclusive technology design, participatory design, gender expression, body modification, personal safety, community resource sharing, social connectedness

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review