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

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

Cathy O'Neil

Start date: May 1, 2022

Finish date: May 31, 2022

Discussion: Book Club 2022

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Dec 10, 2017 David Rubenstein rated it really liked it

Shelves: mathematics, politics

The subtitle of this book, How Big Data Increases Inequality and Threatens Democracy really says it all. Big data has come into our lives in numerous ways, and many of them are a scourge on our lives. Big data, in and of itself, is not to blame, but the uses to which it is put are often outrageous. Take the case of automated teacher evaluations. These are often based on the improvement of students' scores. It seems like a no-brainer, and since the scores take into account the improvement rather The subtitle of this book, How Big Data Increases Inequality and Threatens Democracy really says it all. Big data has come into our lives in numerous ways, and many of them are a scourge on our lives. Big data, in and of itself, is not to blame, but the uses to which it is put are often outrageous. Take the case of automated teacher evaluations. These are often based on the improvement of students' scores. It seems like a no-brainer, and since the scores take into account the improvement rather than the absolute scores, they seem to be very fair. However, one New York teacher received an abysmal score of 6 (out of 100) one year, and the following year received a wonderful score of 96. Obviously the teacher did not suddenly improve his teaching methods.

If a mathematician were to analyze the scores from such evaluations, their random scatter would be instantly recognized as meaningless. Yet, these automated evaluations are used for hiring/firing decisions, as well as compensation decisions. The worst aspect, is that there is no attempt to improve the algorithms. The algorithms used in these evaluations are opaque, and no attempt is made to apply feedback to tweak the scores to make them more accurate and fair.

Such algorithms are used in many avenues of life. Credit scores are used by loan companies--and even by auto insurance companies! Police departments use algorithms to plan targeting of police activity, while courts use algorithms to predict recidivism. Colleges, especially for-profit colleges, use algorithms to target potential students.

While this book comes across as very preachy, and very liberal, it does make some very good points. Big data is often used--intentionally or not--to punish the down-trodden and to increase inequality. Profitability is usually the goal, and while fairness is often the purported goal, these algorithms rarely turn out to have the effect of being fair.

I recommend this book to people who are curious about the effects of big data on their lives and on democracy. ...more

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