skip to main content
10.1145/3532836.3536227acmconferencesArticle/Chapter ViewAbstractPublication PagessiggraphConference Proceedingsconference-collections
invited-talk

Sex and Gender in the Computer Graphics Research Literature

Published:24 July 2022Publication History

ABSTRACT

No abstract available.

Skip Supplemental Material Section

Supplemental Material

3532836.3536227.mp4

presentation video

References

  1. S. Barocas, M. Hardt, and A. Narayanan. 2019. Fairness and Machine Learning.Google ScholarGoogle Scholar
  2. T. Beauchamp. 2019. Going Stealth: Transgender Politics and U.S. Surveillance Practices.Google ScholarGoogle ScholarCross RefCross Ref
  3. Y. Behzadi. 2021. Synthetic data to play a real role in enabling ADAS and autonomy.Google ScholarGoogle Scholar
  4. M. Blackless, A. Charuvastra, A. Derryck, A. Fausto-Sterling, K. Lauzanne, and E. Lee. 2000. How sexually dimorphic are we?Am. J. Hum. Biol. 12, 2 (2000).Google ScholarGoogle ScholarCross RefCross Ref
  5. T. Brewer. 2020. DHS Awards $1 Million to Support Machine Learning Development for Airport Security. Synthetik Applied Technologies Blog(2020).Google ScholarGoogle Scholar
  6. Judith Butler. 2003. Gender trouble. Continental feminism reader(2003), 29–56.Google ScholarGoogle Scholar
  7. R. J. Chen, M. Y. Lu, T. Y. Chen, D. FK Williamson, and F. Mahmood. 2021. Synthetic data in machine learning for medicine and healthcare. Nat. Biom. (2021), 1–5.Google ScholarGoogle Scholar
  8. K. A Clarke. 2005. The phantom menace: Omitted variable bias in econometric research. Conflict management and peace science 22, 4 (2005), 341–352.Google ScholarGoogle Scholar
  9. A. Fausto-Sterling. 2012. Sex/gender: Biology in a social world. Routledge.Google ScholarGoogle Scholar
  10. B. Friedman and H. Nissenbaum. 1996. Bias in Computer Systems. ACM Trans. Inf. Syst. 14, 3 (jul 1996), 330–347. https://doi.org/10.1145/230538.230561Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Google. 2020. Ethics in Action: Removing Gender Labels from Cloud’s Vision API.Google ScholarGoogle Scholar
  12. O. Keyes. 2018. The misgendering machines: Trans/HCI implications of automatic gender recognition. Proceedings of the ACM on human-computer interaction (2018).Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. J. Lorber. 1994. Paradoxes of gender. Yale University Press.Google ScholarGoogle Scholar
  14. N. Mehrabi, F. Morstatter, N. Saxena, K. Lerman, and A. Galstyan. 2021. A Survey on Bias and Fairness in Machine Learning. ACM Comput. Surv. 54, 6 (2021).Google ScholarGoogle Scholar
  15. J. Money and A. Ehrhardt. 1972. Man and woman, boy and girl: Differentiation and dimorphism of gender identity from conception to maturity.(1972).Google ScholarGoogle Scholar
  16. The Nature Editors. 2018. US proposal for defining gender has no basis in science.Google ScholarGoogle Scholar
  17. A. Olteanu, C. Castillo, F. Diaz, and E. Kıcıman. 2019. Social data: Biases, methodological pitfalls, and ethical boundaries. Frontiers in Big Data 2(2019), 13.Google ScholarGoogle ScholarCross RefCross Ref
  18. D. Pessach and E. Shmueli. 2020. Algorithmic Fairness. (2020). arXiv:2001.09784Google ScholarGoogle Scholar
  19. L. Silver. 2017. Topshop Refused To Let A Trans Person Into An All-Gender Changing Room. BuzzFeed News (2017).Google ScholarGoogle Scholar
  20. H. Suresh and J. Guttag. 2021. A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle. EAAMO (Oct 2021).Google ScholarGoogle Scholar
  21. UNHCHR. 2015. Discrimination and violence against individuals based on their sexual orientation and gender identity. (2015).Google ScholarGoogle Scholar
  22. Unreal Engine. 2021. Digital Humans | Metahuman Creator.Google ScholarGoogle Scholar

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    cover image ACM Conferences
    SIGGRAPH '22: ACM SIGGRAPH 2022 Talks
    July 2022
    108 pages
    ISBN:9781450393713
    DOI:10.1145/3532836

    Copyright © 2022 Owner/Author

    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 24 July 2022

    Check for updates

    Qualifiers

    • invited-talk
    • Research
    • Refereed limited

    Acceptance Rates

    Overall Acceptance Rate1,822of8,601submissions,21%

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format .

View HTML Format