Home
9

Governance

9

Privacy Policy

9

Cookie Policy

Members
News & Media
Education & Training
9

Summer Academy For Global Privacy Law 2022

Engineering the data regulation(s) in an age of reform

9

BPH Privacy & Data Protection

Doctoral Seminars

9

Visiting Scholars Programme

Events
9

Meet the Author Series

9

Brussels Privacy Symposium

9

Data Protection In the World Series

9

Enforcing Europe Series 2

9

Data Sustainability Series

9

Ad-Hoc Events

Publications
9

Working Papers

Data Protection & Privacy

9

Workshop Summaries

From BPH Events

9

Reports

Projects
9

Data Protection in Humanitarian Action

Contact
9

Contact

The International Observatory on Vulnerable People In data protection

Resources

Disclaimer: The resources are arranged per thematic sections to facilitate the consultation. However, we are aware of the intersections and overlaps thereof. We are also aware that pre-identifying categories of vulnerable people in data processing is not possible, vulnerability being a largely contextual and elusive concept. We are not claiming to be exhaustive, but to initiate a discussion.

Do you have any suggestions as to how improve the repository? Have you come across any resource that should be included in the repository? Contact us.

LGBTQIA+ & non-binary folks

- Academic writings

Beauchamp, T. (2019). Going Stealth. Transgender Politics and U.S. Surveillance Practices. Durham and London: Duke University Press. https://doi.org/10.2307/j.ctv11cw8g8

Bivens, R. (2017). The gender binary will not be deprogrammed: Ten years of coding gender on Facebook, New Media & Society 19(6), 880-898. https://doi.org/10.1177/1461444815621527

Cirillo, D., Catuara-Solarz, S., Morey, C. et al. (2020). Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare. NPJ Digital Medicine, 3, 81. https://doi.org/10.1038/s41746-020-0288-5  

Dias Oliva, Antonialli, D. M., & Gomes, A. (2020). Fighting Hate Speech, Silencing Drag Queens? Artificial Intelligence in Content Moderation and Risks to LGBTQ Voices Online. Sexuality & Culture, 25(2), 700–732. https://doi.org/10.1007/s12119-020-09790-w

Fosch-Villaronga, E., Poulsen, A., Søraa, R. A., & Custers, B. H. M. (2021). A little bird told me your gender: Gender inferences in social media. Information Processing & Management. vol. 58 (3). https://doi.org/10.1016/j.ipm.2021.102541

Fosch-Villaronga, E., Poulsen, A., Søraa, R. A., & Custers, B. H. M. (2020) Don’t guess my gender, gurl: The inadvertent impact of gender inferences. BIAS 2020: Bias and Fairness in AI Workshop at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 14-18 September 2020, online. 95038630 Published paper

Guyan, K. (2022) Queer DataUsing Gender, Sex and Sexuality Data for Action https://www.bloomsbury.com/uk/queer-data-9781350230729/

Hamidi, F., Scheuerman, M. K., & Branham, S. M. (2018, April). 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, 1-13. https://doi.org/10.1177/2056305118768299

Hutson, J., Taft, J. G. , Barocas, S. and Levy K. (2018). Debiasing Desire: Addressing Bias & Discrimination on Intimate Platforms. In Proceedings of the ACM on Human-Computer Interaction, Vol. 2, CSCW, Article 73 (November 2018). ACM, New York, NY. 18 pages. https://doi.org/10.1145/3274342 

Keats Citron, D. (2018). Sexual privacy. Yale LJ128, 1870. https://openyls.law.yale.edu/bitstream/handle/20.500.13051/10382/Citron_q8ew5jjf.pdf?sequence=2&isAllowed=y

Keyes, O. (2018). The misgendering machines: Trans/HCI implications of automatic gender recognition. Proceedings of the ACM on Human-Computer Interaction, 2(CSCW), 1-22. https://doi.org/10.1145/3274357

Light, B., Mitchell, P., & Wikström, P. (2018). Big Data, method and the ethics of location: A case study of a hookup app for men who have sex with men. Social Media+ Society4(2). https://doi.org/10.1177/2056305118768299

MacKee, F. (2016). Social media in gay London: Tinder as an alternative to hook-up apps. Social Media+ Society2(3). https://doi.org/10.1177/2056305116662186

Monea, A. (2022). The Digital Closet: How the Internet Became Straight. The MIT Press. https://doi.org/10.7551/mitpress/12551.001.0001 

Poulsen, A., Fosch-Villaronga, E., & Søraa, R.A. (2020) Queering Machines. Nature Machine Intelligence, Correspondence, https://doi.org/10.1038/s42256-020-0157-6

Rodriguez. (2022). LGBTQ Incorporated: YouTube and the Management of Diversity. Journal of Homosexuality, ahead-of-print(ahead-of-print), 1–22. https://doi.org/10.1080/00918369.2022.2042664

Southerton, C., Marshall, D., Aggleton, P., Rasmussen, M. L., & Cover, R. (2021). Restricted modes: Social media, content classification and LGBTQ sexual citizenship. New Media & Society, 23(5), 920–938. https://doi.org/10.1177/1461444820904362

Sriram, N. (2020). Dating Data: LGBT Dating Apps, Data Privacy, and Data Security. U. Ill. JL Tech. & Pol’y, 507. https://illinoisjltp.com/journal/wp-content/uploads/2020/12/Sriram_Final.pdf

Stardust, Z. (2018). Safe for Work: Feminist Porn, Corporate Regulation and Community Standards. In: Dale, C., Overell, R. (eds) Orienting Feminism. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-70660-3_9

- NGO Reports & Articles

Privacy International (2019). From Oppression to Liberation: Reclaiming the Right to Privacy https://privacyinternational.org/report/2457/report-oppression-liberation-reclaiming-right-privacy

Internet Lab (2019). Drag queens and Artificial Intelligence: should computers decide what is ‘toxic’ on the internet? https://internetlab.org.br/en/news/drag-queens-and-artificial-intelligence-should-computers-decide-what-is-toxic-on-the-internet/

Privacy International (2019). Communities at risk: How security fails are endangering the LGBTIQ+ community https://privacyinternational.org/news-analysis/2782/communities-risk-how-security-fails-are-endangering-lbgtiq-community

Wood, C., Ringrose, K., Gutierrez, C., Stephanovich, A., & Colson, C. (2022). The role of data protection in Safeguarding Sexual Orientation and Gender Identity Information. https://fpf.org/wp-content/uploads/2022/06/FPF-SOGI-Report-R2-singles-1.pdf

- Data Protection Authorities' Guidance

- Laws

- Case Law

European Court of Human Rights

Beizaras and Levickas v. Lithuania (Second Section) 41288/15 2020 https://hudoc.echr.coe.int/eng?i=001-200344

Y.T. v. Bulgaria (Fifth Section) 41701/16 2020 Official Language in French: https://hudoc.echr.coe.int/eng?i=001-203898 Unofficial English Translation: In pp. 379-380 https://rm.coe.int/new-caselaw-06-2021/1680a2fc58

Rana v. Hungary (Fourth Section) 40888/17 2020 https://www.stradalex.com/nl/sl_src_publ_jur_int/document/echr_40888-17

X and Y v. Romania (Fourth Section) 2145/16 and 20607/16 2021 Official Language in French: https://hudoc.echr.coe.int/eng?i=001-207364 Unofficial English Translation: In pp. 391-393 https://rm.coe.int/new-caselaw-06-2021/1680a2fc58

- Policy documents

- Global Developments

- Others

Maury, M. (2022). I feel for you, but…”: How Improved Data Will Support the LGBTQI+ Community https://www.whitehouse.gov/ostp/news-updates/2022/08/29/i-feel-for-you-but-how-improved-data-will-support-the-lgbtqi-community/

Veale, M. (2022). Course Sexuality and the Law (partial syllabus). https://www.homepages.ucl.ac.uk/~ucqnmve/syllabi/satl.html