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The Black Technical Object

- On Machine Learning and the Aspiration of Black Being

About The Black Technical Object

On the abstruse nature of machine learning, mathematics, and the deep incursion of racial hierarchy. To impair the racial ordering of the world, The Black Technical Object introduces the history of statistical analysis and "scientific" racism into research on machine learning. Computer programming designed for taxonomic patterning, machine learning offers useful insights into racism and racist behavior, but its connection to the racial history of science and the Black lived experience has yet to be developed. In this book, Ramon Amaro explores how the history of data and statistical analysis informs the complex relationship between race and machine learning. He juxtaposes a practical analysis of this type of computerized learning with a theory of Black alienation in order to inspire alternative approaches to contemporary algorithmic practice. In doing so, Amaro contemplates the abstruse nature of programming and mathematics, as well as the deep incursion of racial hierarchies.

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  • Language:
  • English
  • ISBN:
  • 9783956795633
  • Binding:
  • Paperback
  • Pages:
  • 232
  • Published:
  • March 13, 2023
  • Dimensions:
  • 132x208x20 mm.
  • Weight:
  • 318 g.
  In stock
Delivery: 3-5 business days
Expected delivery: December 7, 2024
Extended return policy to January 30, 2025

Description of The Black Technical Object

On the abstruse nature of machine learning, mathematics, and the deep incursion of racial hierarchy. To impair the racial ordering of the world, The Black Technical Object introduces the history of statistical analysis and "scientific" racism into research on machine learning. Computer programming designed for taxonomic patterning, machine learning offers useful insights into racism and racist behavior, but its connection to the racial history of science and the Black lived experience has yet to be developed. In this book, Ramon Amaro explores how the history of data and statistical analysis informs the complex relationship between race and machine learning. He juxtaposes a practical analysis of this type of computerized learning with a theory of Black alienation in order to inspire alternative approaches to contemporary algorithmic practice. In doing so, Amaro contemplates the abstruse nature of programming and mathematics, as well as the deep incursion of racial hierarchies.

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