GenderIT.org

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This essay on Algorithmic discrimination and the feminist politics of being in the data was published by GenderIT.org and included in their edition on feminist perspectives on Economic, Social, Cultural Rights and the Internet. It explores the trade off between a desire and necessity to be included in data and resistance against the non-consensual bulk collection of data from a Human Rights and gender perspective.

Read the full article here.

(…) While the right to privacy has enjoyed the most prominent attention in relation to data and the internet, it is important to note that human rights violations as well as human rights in and of themselves are intersectional. As the enjoyment of economic, social, and cultural rights increasingly takes place online, privacy is rarely an end in itself but a prerequisite for exercising other fundamental rights such as education or the participation in cultural life, for human rights advocacy, and for any potentially transformative use of big data. In other words, algorithmic discrimination not only disadvantages those on the intersections between race, gender and sexuality and thus violates their right to freedom from discrimination, but also (intersectionally) threatens the enjoyment and defence of all human rights.
(…)
What follows for feminist data practices is that it doesn’t have to be a contradiction to support the use of data for good – whether by the means of community driven data projects or the rather global endeavours cited above – and to resist the unaccountable and/or non-consensual use of data. On the contrary, it is crucial to question the power relations behind who gets to collect and compute data about whom, to what ends; the terms of agency, consent, ownership and access; and the resulting human rights implications every step along the way. As a reflexive practice, this applies as much to data-driven state surveillance, commercial big data practices, and big data for development initiatives, as to localised uses of data for social justice, including data-based feminist advocacy projects. (…)