Cited by 7

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

The ethics of AI at the intersection of transgender identity and neurodivergence

Parks, Max·2025·Discover Artificial Intelligence

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s44163-025-00257-1

Cites

7 of 7 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

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?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Show all 7 references

Research works printed but not linked: 54

  1. Aboujaoude E, Starcevic V. Case report: doubts and preoccupations about being transgender- questioning one’s gender identity or a case of obsessive-compulsive disorder? Front Psych. 2021;12:644114. · DOI
  2. Accardo AL, Bomgardner EM, Rubinstein MB, Woodruff J. Valuing neurodiversity on campus: perspectives and priorities of neurodivergent students, faculty, and professional staff. J Divers High Educ. 2024. https://doi.org/10.1037/dhe0000571. · DOI
  3. Armstrong T. The myth of the normal brain: embracing neurodiversity. AMA J Ethics. 2015;17(4):348–52. · DOI
  4. Arístegui I, Beraldi M, Cabral M, Paván V, Vázquez L. The gender identity law in Argentina: a step toward decolonizing transgender healthcare. J Transgender Health. 2017;2(3):147–59.
  5. Barocas S, Selbst AD. Big data’s disparate impact. Calif Law Rev. 2016;104(3):671–732.
  6. Battistuzzi L, Recchiuto CT, Sgorbissa A. Ethical concerns in rescue robotics: a scoping review. Ethics Inf Technol. 2021;23(4):863–75. · DOI
  7. Bennett CL, Gleason C, Scheuerman MK, Bigham JP, Guo A. To A. It’s Complicated: negotiating accessibility and (Mis) representation in image descriptions of race, gender, and disability. In: Proceedings of the 2021 chi conference on human factors in computing systems. 2021; (Pp. 1–19). · DOI · Paper page
  8. Boxleitner A. Pushing boundaries or crossing lines? The complex ethics of ChatGPT jailbreaking. The complex ethics of ChatGPT jailbreaking. SSRN J. 2023. https://doi.org/10.2139/ssrn.4604736. · DOI
  9. Brady E, Morris MR, Bigham JP. Gauge: a framework for transparent evaluation of multi-user sensor systems. In Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing. ACM. 2015; (pp. 821–832)
  10. Bragazzi NL, Crapanzano A, Converti M, Zerbetto R, Khamisy-Farah R. The impact of generative conversational artificial intelligence on the lesbian, gay, bisexual, transgender, and queer community: scoping review. J Med Internet Res. 2023;25:E52091. · DOI · Paper page
  11. Brandsen S, Chandrasekhar T, Franz L, Grapel J, Dawson G, Carlson D. Prevalence of bias against neurodivergence-related terms in artificial intelligence language models. Autism Res. 2024;17(2):234. · DOI
  12. Brayne S. Predict and surveil: data, discretion, and the future of policing. Oxford: Oxford University Press; 2021.
  13. Buolamwini J, Gebru T. Gender shades: intersectional accuracy disparities in commercial gender classification. Proc Mach Learn Res. 2018;81:1–15.
  14. Costanza-Chock S. Design justice: community-led practices to build the worlds we need. Cambridge: Mit Press; 2020. · DOI
  15. Conrad P, Schneider JW. Deviance and medicalization: from badness to sickness. Philadelphia: Temple University Press; 1992.
  16. Pedro De, Tunac K, Shim-Pelayo H, Bishop C. Exploring physical, nonphysical, and discrimination-based victimization among transgender youth in California public schools. Int J Bull Prevent. 2019;1:218–26. · DOI
  17. Dhejne C, Van Vlerken R, Heylens G, Arcelus J. Mental health and gender dysphoria: a review of the literature. Int Rev Psychiatry. 2016;28(1):44–57. · DOI · Paper page
  18. Dietz C. Self-declaration of legal gender status in denmark. Age. 2018;18(30):8.
  19. Dorn R, Kezar L, Morstatter F, Lerman K. Harmful speech detection by language models exhibits gender-queer dialect bias. 2024. Arxiv Preprint https://arxiv.org/abs/2406.00020. Accessed 30 July 2024. · arXiv
  20. Dwork C, Hardt M, Pitassi T, Reingold O, Zemel R. Fairness through awareness. In: Proceedings of the 3rd innovations in theoretical computer science conference. ACM. 2012; (pp. 214–226). · DOI · Paper page
  21. Georges E, Brown EC, Cohen RS. Prohibition of gender-affirming care as a form of child maltreatment: reframing the discussion. Pediatrics. 2024;153(1):E2023064292. · DOI
  22. Gillespie T. Content moderation, AI, and the question of scale. Big Data Soc. 2020. https://doi.org/10.1177/2053951720943234. · DOI
  23. Gollasch D, Branig M, Gerling K, Gulliksen J, Metatla O, Spiel K, Weber G. Designing technology for neurodivergent self-determination: challenges and opportunities. In: Ifip conference on human-computer interaction. Springer. 2023; (Pp. 621–626) · DOI
  24. Haimson OL, Gorrell D, Starks DL, Weinger Z. Designing trans technology: defining challenges and envisioning community-centered solutions. In proceedings of the 2020 CHI conference on human factors in computing systems, 2020; pp. 1–13. · DOI · Paper page
  25. Hamidi F, Scheuerman MK, Branham SM. Gender recognition or gender reductionism? The social implications of embedded gender recognition systems. In Proceedings of the 2018 chi conference on human factors in computing systems, 2018; pp. 1–13. · DOI
  26. Hamraie A, Fritsch K. Crip technoscience manifesto. Catal Fem, Theor, Technosci. 2019;5(1):1–33.
  27. Hoffman S, Podgurski A. Artificial intelligence and discrimination in health care. Yale J Health Policy Law Ethics. 2019;19:1.
  28. Kcomt L, Gorey KM, Barrett BJ, Mccabe SE. Healthcare avoidance due to anticipated discrimination among transgender people: a call to create trans-affirmative environments. Ssm-Popul Health. 2020;11:100608. · DOI
  29. Korpan R, Ray R, Sipos A, Dennler N, Parks M, Cabrera ME, Martín-Martín R. Launching queer in robotics. IEEE Robot Autom Mag. 2024;30:2.
  30. Link BG. Understanding labeling effects in the area of mental disorders: an assessment of the effects of expectations of rejection. Am Sociol Rev. 1987;52:96–112. · DOI
  31. Macaulay M, Moldes MD. Queen don’t compute: reading and casting shade on facebook’s real names policy. In: Queer technologies. Milton Park: Routledge; 2017. p. 6–22. · DOI
  32. MacCarthy M. Fairness in algorithmic decision-making. Washington: Brookings Institution; 2019.
  33. Mizock L, Fleming MZ. Transgender and gender variant populations with mental illness: implications for clinical care. Prof Psychol Res Pract. 2001;42(2):208. · DOI
  34. Parks M, Mark A. Autonomy and fatigue in human-robot teams. In 2023 Ieee international performance, computing, and communications conference (Ipccc). Ieee. 2023; (Pp. 158–159) · DOI
  35. Pasterski V, Gilligan L, Curtis R. Traits of autism spectrum disorders in adults with gender dysphoria. Arch Sex Behav. 2014;43:387–93. · DOI
  36. Perilo M, Valença G, Telles A. Non-binary and trans-inclusive AI: a catalogue of best practices for developing automatic gender recognition solutions. Acm Sigapp Appl Comput Rev. 2024;24(2):55–70. · DOI
  37. Rincón C, Keyes O, Cath C. Speaking from experience: trans/non-binary requirements for voice-activated Ai. Proc Acm Human-Comput Interact. 2021;5(Cscw1):1–27. · DOI
  38. Rothstein A. Review of mental disorder or neurodiversity? New Atl. 2012;36:99–115.
  39. Sawyer K, Christian T, Jennica W. Queering the gender binary: understanding transgender workplace experiences. In: Sexual orientation and transgender issues in organizations: global perspectives on lgbt workforce diversity. Cham: Springer International Publishing; 2016. p. 21–42. · DOI
  40. Schecter E. Introducing Plurals. Center for Cognition and Neuroethics Persons Conference. Journal of Cognition and Neuroethics. 2023. http://jcn.cognethic.org/jcnv9i2_Schechter.pdf. Accessed 30 June 2024.
  41. Scheuerman MK, Wade K, Lustig C, Brubaker JR. How we’ve taught algorithms to see identity: constructing race and gender in image databases for facial analysis. Proc Acm On Human-Comput Interact. 2020;4(Cscw1):1–35. · DOI · Paper page
  42. Sciberras Debono M. The gender identity, gender expression and sex characteristics act, 2015. Malta Med J. 2015;27(2):14–21.
  43. Selbst AD, Boyd D, Friedler SA, Venkatasubramanian S, Vertesi J. Fairness and Abstraction in Sociotechnical Systems. In Proceedings of the Conference on Fairness, Accountability, and Transparency (FAT)*. ACM. 2019; (pp. 59–68). · DOI · Paper page
  44. Shipherd JC, Kauth MR, Firek AD, Garcia R, Mejia S, Young S, Fortney S, et al. Interdisciplinary transgender veteran care: development of a core curriculum For Vha providers. Transgender Health. 2022;7(1):123–31.
  45. Simon S, Silverstein E, Timmons-Sund L, Pinto JM, Castro ME, Mack WJ. Validation of an Ai-assisted treatment outcome measure for gender-affirming voice care: comparing AI Accuracy to listeners’ perception of voice femininity. J Voice. 2023. https://doi.org/10.1016/j.jvoice.2023.12.008. · DOI
  46. Spiel K, Gerling K. The purpose of play: how HCI games research fails neurodivergent populations. Acm Trans Comput Human Interact. 2021;28(2):11. https://doi.org/10.1145/3432245. · DOI
  47. Spiel K, Keyes O, Barlas P. Patching gender: non-binary utopias In HCI. Extended abstracts of the 2019 chi conference on human factors in computing systems, 2019; 1–11. · DOI
  48. Swain J, French S. Towards an affirmation model of disability. Disabil Soc. 2000;15(4):569–82. · DOI
  49. Wagner TL, Kitzie VL, Lookingbill V. Transgender and nonbinary individuals and ict-driven information practices in response to trans-exclusionary healthcare systems: a qualitative study. J Am Med Inform Assoc. 2021;29(2):239–48. · DOI
  50. Wallis C. Neurodivergent children’s right to community and education equality. J Soc Adv Legal Stud. 2024;5:528.
  51. Walker A. Transphobic discourse and moral panic convergence: a content analysis of my hate mail. Criminology. 2023;61(4):994–1021. · DOI
  52. Whittle S, Simkiss A. The UK’s gender recognition act: ongoing debates and future directions. Leg Stud. 2020;40(1):56–73.
  53. Williams B. President trump’s crusade against the transgender community. Am Uj Gender Soc Pol’y L. 2018;27:525.
  54. Wyers K. Leaving no one behind? A research agenda for queer issues In ICT4D. Berlin: Springer; 2024.

Cited by

Sorted by citations

See all 7

Metadata

Authors
Parks, M.
Venue
Discover Artificial Intelligence
Published
2025-04-07
Volume
5
Issue
1
ISSN
2731-0809
Cited by
7
References
7
Language
en

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