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Pragya Agarwal
Visiting Professor of Social Inequities and Injustice, Loughborough University
Pragya Agarwal is a professor of social inequities, writer, speaker, and consultant. Following a PhD from the University of Nottingham, Pragya held the prestigious Leverhulme Fellowship and has held senior academic positions and visiting fellowships at various US and UK universities.
Pragya is the author of a number of scholarly articles and four non-fiction books. Her first book Sway: Unravelling Unconscious Bias was published in 2020 with Bloomsbury, and was a Guardian Book of the Week and shortlisted for the Transmission Prize. Her second book, Wish We Knew What To Say: Talking With Children about Race, was also published in 2020 with Dialogue Books. Her third book, (M)otherhood: On the choices of being a woman, was published in 2021 with Canongate to great acclaim. Her first book for children, Standing up to Racism, was published by Hachette and shortlisted for the Progressive Preschool award. Her latest book, Hysterical: Exploding the myth of gendered emotions, is out now with Canongate books and was one of Waterstones’ best science book of 2022, one of Telegraph's best big ideas book of 2022, and i paper’s best non-fiction of 2022.
Pragya works as a consultant and speaker with organisations around the world, including universities, corporate and non-profits, and schools, delivering talks and workshops on a range of topics. She is a twotime TEDx speaker, a TEDx Woman organiser, and makes regular expert appearances on many international shows and podcasts such as NPR Short Wave, BBC Women’s Hour, BBC Radio 4 The Spark, and Darren Brown’s podcast The Bigoted Brain, Sky News, Australian Broadcasting Service, and Canadian Radio.
She can be found at drpragyaagarwal.com and on twitter at DrPragyaAgarwal
How the brain stops us learning from our mistakes – and what to do about it
Apr 23, 2023 12:36 pm UTC| Health
You learn from your mistakes. At least, most of us have been told so. But science shows that we often fail to learn from past errors. Instead, we are likely to keep repeating the same mistakes. What do I mean by...
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