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Other. The Dangers of Sorting People by Race and Sex
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- Nombre de pages288
- Date de parution28/01/2027
- FormatePub
- ISBN978-0-00-871522-9
- EAN9780008715229
- Protection num.Adobe DRM
- Infos supplémentairesepub
- ÉditeurFourth Estate
Résumé
From award-winning and bestselling science journalist Angela Saini, comes a groundbreaking exposé of the hidden harms of race and sex data across medicine, education, politics, and society at large.
'One of the world's best science writers' Ed Yong, Pulitzer Prize-winning author of An Immense World
'An amazing science writer. She has an ability to distill big, complicated topics into something digestible and clear without dumbing it down' Daniel Radcliffe, in Vulture
Daily we are asked - on the census, at the doctor's office, on job applications and by social platforms - to mark our sex and race, with the tacit understanding that in doing so we are contributing, somehow, to the greater good.
But as Angela Saini shows in this gripping reassessment of data and identity, we are sleepwalking into a minefield. Other takes us from the idealistic 1960s, when categories used to divide people were repurposed to administer equal rights, to today, when they have been twisted back to their original purpose. Governments from the United States to Hungary are narrowing their definitions of 'man' and 'woman' to curb reproductive freedoms; rogue researchers are mining medical data in the hunt for spurious links between race and intelligence; and lawmakers are using census maps intended to protect civil rights for racial gerrymandering.
Latin American countries that once abandoned race categories on their censuses are bringing them back and in 2027, the Indian census will classify people by caste for the first time since 1931. The rise of artificial intelligence is supercharging it all, with China using ethnicity 'recognition' technologies to track minorities and opaque private firms like Palantir entrusted with government data to manage migration and health. Unaware of the risks, we continue to run headlong for categories that serve those at the top far better than those at the bottom.
Making an original, provocative case for leaning away from categorization, Saini urges us to consider what we lose when we are placed in a box. As classification draws us further into its grip, the only escape route is the final category on any form, the one that defies definition: other.
But as Angela Saini shows in this gripping reassessment of data and identity, we are sleepwalking into a minefield. Other takes us from the idealistic 1960s, when categories used to divide people were repurposed to administer equal rights, to today, when they have been twisted back to their original purpose. Governments from the United States to Hungary are narrowing their definitions of 'man' and 'woman' to curb reproductive freedoms; rogue researchers are mining medical data in the hunt for spurious links between race and intelligence; and lawmakers are using census maps intended to protect civil rights for racial gerrymandering.
Latin American countries that once abandoned race categories on their censuses are bringing them back and in 2027, the Indian census will classify people by caste for the first time since 1931. The rise of artificial intelligence is supercharging it all, with China using ethnicity 'recognition' technologies to track minorities and opaque private firms like Palantir entrusted with government data to manage migration and health. Unaware of the risks, we continue to run headlong for categories that serve those at the top far better than those at the bottom.
Making an original, provocative case for leaning away from categorization, Saini urges us to consider what we lose when we are placed in a box. As classification draws us further into its grip, the only escape route is the final category on any form, the one that defies definition: other.
