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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. And that AI is generating new categories outside the traditional ones. 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

Cahill, S. &  Makadon, H. J. (2014). Sexual Orientation and Gender Identity Data Collection Update: U.S. Government Takes Steps to Promote Sexual Orientation and Gender Identity Data Collection Through Meaningful Use Guidelines. LGBT Health, 1(3), 157–160. doi:10.1089/lgbt.2014.0033 

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

Fico, B. D. S. D., & Nobrega, H. M. (2022). The Brazilian Data Protection Law for LGBTQIA+ People: Gender identity and sexual orientation as sensitive personal data. Revista Direito e Práxis13, 1262-1288. https://doi.org/10.1590/2179-8966/2022/66817

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

Kokas, A. (2022). Data Trafficking and the International Risks of Surveillance Capitalism: The Case of Grindr and China. Television & New Media0(0). https://doi.org/10.1177/15274764221137250Light, 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

van Zyl, I., & McLean, N. (2021). The Ethical Implications of Digital Contact Tracing for LGBTQIA+ Communities. arXiv preprint arXiv:2108.10096.
https://doi.org/10.48550/arXiv.2108.10096

- NGO Reports & Articles

FPF (2023). New report highlights LGBTQ+ student views on school technology and privacy. https://fpf.org/blog/new-report-highlights-lgbtq-student-viewson-school-technology-and-privacy/

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