

#3155
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.
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 

, highlighting its discussion on how math is used to disguise exploitation.


Michael Lewis

355 snips
Episode 10: “Anybody Can Win, but Everybody’s Gonna Lose”
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as a book that changed her perspective on data and its societal impact.

Jess Ramos

60 snips
839: Double Your Data Salary in 11 Months, with Jess Ramos
Mentioned by ![undefined]()

as a book highlighting the biases and catastrophic consequences of algorithms in society.

Hannah Fry

57 snips
#87 Hannah Fry: The Role of Algorithms
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.

30 snips
870: Personality Tests | Skeptical Sunday
Mentioned by 

when discussing AI algorithms and inherent bias.


Kris Brandow

A Discourse On AI Discourse
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as a book providing simple examples of destructive algorithms.

Jill Nephew

THE SOUL OF A.I. #2 -- "The Great Illusion" w/ Jill Nephew
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as an insightful read on AI and mathematical models.

Andrew Hart

65 - The Metrics That Matter
Recommended by 

as a primer on understanding the risks of AI.


Sophia Rowland

The Role of Analytics in Shaping the Future of MLOps
Mentioned by 

as a book addressing ethical concerns within the machine learning community.


Brian Christian

#92 – Brian Christian on the alignment problem
Mentioned by 

when discussing AI weeding out candidates in hiring processes.


John Strand

Blackmailing A.I. - 2025-05-27
Mentioned by ![undefined]()

as a blossoming literature about challenges involving data-empowered algorithms.

Chris Wiggins

The power of data: ethics, politics, and public interest
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in the context of her book Mothers of Data Science.

Kate Strachnyi

441: Communicating Data Effectively
Mentioned by 

as a book about the negative consequences of algorithms.


Baratunde Thurston

How Facebook and Twitter are dealing with racist posts and Friend of Pivot Baratunde Thurston on why “now is the time to step up, show up, or shut up”
Mentioned when discussing algorithmic agency and how data and algorithms can be misused.

[Livestream] David Shapiro - AI, Post-Labor Economics, Futurism | Artificial Intelligence Masterclass
Mentioned by ![undefined]()

in relation to the discussion on the dark side of technology.

Andrew Keen

Episode 2300: Sandra Matz makes the Case for a Data-Driven Science of Predicting and Changing Human Behavior
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as relevant to the discussion on AI safety and ethics.

David Shapiro

"Pausing AI is a spectacularly BAD idea―Here's why" - AI Masterclass