Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy

by Cathy O'Neil

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Mathematician and former Wall Street quant Cathy O'Neil exposes how opaque, unregulated, and unaccountable mathematical models she calls Weapons of Math Destruction are being used to make consequential decisions about employment, lending, policing, and education, often reinforcing existing inequalities. She shows how these models create destructive feedback loops that punish the poor and reward the privileged while operating under an illusion of objectivity.

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Pages:
272
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In the Conversation

In this collection, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy references 4 other books.

It draws on The Signal and the Noise, Thinking, Fast and Slow and Predictably Irrational.

Scroll down to read the exact passages where other authors reference this book and what they say about it.

What This Book Draws On

4

The books O'Neil references and why each one mattered to the argument.

O'Neil contrasts her WMD framework with Silver's The Signal and the Noise approach to prediction, arguing that when algorithms are deployed at scale on human populations without feedback correction, the noise becomes a self-fulfiling prophecy that entrenches inequality

The Signal and the Noise

References

The Signal and the Noise

by Nate Silver

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Draws on Kahneman's Thinking, Fast and Slow analysis of anchoring bias and base-rate neglect to explain how algorithmic scoring systems bake cognitive biases into automated decision-making at unprecedented scale

Thinking, Fast and Slow

References

Thinking, Fast and Slow

by Daniel Kahneman

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References Ariely's Predictably Irrational research on systematic human decision failures to argue that replacing human judgement with algorithms does not eliminate irrationality but merely encodes it in code

Predictably Irrational

References

Predictably Irrational

by Dan Ariely

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Critiques the techno-optimism in Domingos's The Master Algorithm vision of a universal learning machine, arguing that without ethical guardrails, more powerful algorithms simply produce more powerful instruments of discrimination

The Master Algorithm

References

The Master Algorithm

by Pedro Domingos

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What Other Authors Say About It

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Intellectual Lineage

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Books with the highest citation overlap within the same categories.

Pitch Anything

Pitch Anything

Oren Klaff

2 shared citations
You Are Not So Smart

You Are Not So Smart

David McRaney

2 shared citations
Alchemy: The Dark Art and Curious Science of Creating Magic in Brands, Business, and Life

Alchemy: The Dark Art and Curious Science of Creating Magic in Brands, Business, and Life

Rory Sutherland

2 shared citations
Risk Savvy: How to Make Good Decisions

Risk Savvy: How to Make Good Decisions

Gerd Gigerenzer

2 shared citations
Future Babble: Why Expert Predictions Are Next to Worthless, and You Can Do Better

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Dan Gardner

2 shared citations
Head in the Cloud: Why Knowing Things Still Matters When Facts Are So Easy to Look Up

Head in the Cloud: Why Knowing Things Still Matters When Facts Are So Easy to Look Up

William Poundstone

2 shared citations

Citation Network

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Thinking, Fast and Slow

Hover a node to highlight its connections. Click to open the book page. Node size reflects total citation links.