#3978
Mentioned in 9 episodes

Weapons of Math Destruction

How Big Data Increases Inequality and Threatens Democracy
Book • 2016
In this book, Cathy O'Neil explores the societal impact of big data algorithms, which she terms 'Weapons of Math Destruction' (WMDs).

These algorithms are used in various fields such as insurance, advertising, education, and policing, and they often reinforce discrimination, amplify inequality, and harm the poor.

O'Neil argues that these models are opaque, unregulated, and difficult to contest, leading to a 'toxic cocktail for democracy'.

She calls for greater responsibility from modelers and policymakers to regulate these algorithms and for the public to become more aware of their impact.

The book provides numerous examples of how these models can go wrong and emphasizes the need for ethical considerations in the use of big data models.

Mentioned by

Mentioned in 9 episodes

Mentioned by Michael Lewis , highlighting its discussion on how math is used to disguise exploitation.
354 snips
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Recommended by Jess Ramos as a book that changed her perspective on data and its societal impact.
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Mentioned by Hannah Fry as a book highlighting the biases and catastrophic consequences of algorithms in society.
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Mentioned by Kathy O'Neill, a mathematician, data scientist, and author, as a catchy and terrifying name for a book about the dangers of algorithms.
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Mentioned by Kris Brandow when discussing AI algorithms and inherent bias.
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Recommended by Andrew Hart as an insightful read on AI and mathematical models.
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Mentioned by Brian Christian as a book addressing ethical concerns within the machine learning community.
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Mentioned by John Strand when discussing AI weeding out candidates in hiring processes.
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Mentioned by Chris Wiggins as a blossoming literature about challenges involving data-empowered algorithms.
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Mentioned by Kate Strachnyi in the context of her book Mothers of Data Science.
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Mentioned when discussing algorithmic agency and how data and algorithms can be misused.
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Mentioned by David Shapiro as relevant to the discussion on AI safety and ethics.
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