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What data scientists can learn from feminist social scientists in India. With Radhika Radhakrishnan.

What data scientists can learn from feminist social scientists in India. With Radhika Radhakrishnan.

Released Monday, 28th November 2022
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What data scientists can learn from feminist social scientists in India. With Radhika Radhakrishnan.

What data scientists can learn from feminist social scientists in India. With Radhika Radhakrishnan.

What data scientists can learn from feminist social scientists in India. With Radhika Radhakrishnan.

What data scientists can learn from feminist social scientists in India. With Radhika Radhakrishnan.

Monday, 28th November 2022
Good episode? Give it some love!
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In this episode, we're in conversation with feminist scholar and activist, Radhika Radhakrishnan. Radhika is a PhD student at the Massachusetts Institute of Technology (MIT) in the HASTS (History, Anthropology, Science, Technology & Society) programme. This programme uses methods from history and anthropology to study how science and technology shape – and are shaped by – the world we live in.

Trained in Gender Studies and Computer Science engineering in India, Radhika has worked for over five years with civil society organisations to study the intersections of gender justice and digital technologies using feminist, qualitative research methodologies.

Her research focuses on understanding the challenges faced by gender-minoritized communities with emerging digital technologies in India and finding entry points to intervene meaningfully. Her scholarship has spanned the domains of Artificial Intelligence, data governance pertaining to surveillance technologies and health data, and feminist Internets, among others.

Radhika shares with us what she'll be researching for her PhD and why she moved away from computer science to social science.

In 2021 Radhika’s paper, “Experiments with Social Good: Feminist Critiques of Artificial Intelligence in Healthcare in India” was published in the journal, Catalyst, and we explore her findings, as well as why she was drawn to artificial intelligence in healthcare.

We also discuss her experiences of studying up (see Nader 1972) as a female researcher and some of the strategies she used to overcome these challenges.

Lastly, Radhika recommends Annihilation of Caste by B. R. Ambedkar, and explains why it's important that we openly discuss caste. (Check out this article in WIRED about caste in Silicon Valley.)

Follow Radhika on Twitter @so_radhikal, and connect with her on LinkedIn. Check out her website, and read her blog on Medium.

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