Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Feeding the Machine: The Hidden Human Labor Powering A.I.

Feeding the Machine: The Hidden Human Labor Powering A.I.

Graham, Mark
Cant, Callum
Muldoon, James

Hardcover

Business GeneralTechnology & EngineeringSocial Movements

Publisher Price: $29.99

ISBN10: 1639734961
ISBN13: 9781639734962
Publisher: Bloomsbury Publishing
Published: Aug 6 2024
Pages: 288
Weight: 1.20
Height: 1.05 Width: 6.45 Depth: 9.50
Language: English

For readers of Naomi Klein and Nicole Perlroth, a myth-dissolving exposé of how artificial intelligence exploits human labor, and a resounding argument for a more equitable digital future.

Silicon Valley has sold us the illusion that artificial intelligence is a frictionless technology that will bring wealth and prosperity to humanity. But hidden beneath this smooth surface lies the grim reality of a precarious global workforce of millions laboring under often appalling conditions to make A.I. possible. This book presents an urgent, riveting investigation of the intricate network that maintains this exploitative system, revealing the untold truth of A.I.

Based on hundreds of interviews and thousands of hours of fieldwork over more than a decade, Feeding the Machine describes the lives of the workers deliberately concealed from view, and the power structures that determine their future. It gives voice to the people whom A.I. exploits, from accomplished writers and artists to the armies of data annotators, content moderators and warehouse workers, revealing how their dangerous, low-paid labor is connected to longer histories of gendered, racialized, and colonial exploitation.

A.I. is an extraction machine that feeds off humanity's collective effort and intelligence, churning through ever-larger datasets to power its algorithms. This book is a call to arms that details what we need to do to fight for a more just digital future.

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