Author | Cathy O'Neil |
---|---|
Country | United States |
Language | English |
Subject | Mathematics, race, ethnicity |
Genre | Non-fiction |
Publisher | Crown Books |
Publication date | 2016 |
Awards | Euler Book Prize |
ISBN | 0553418815 |
Weapons of Math Destruction is a 2016 American book about the societal impact of algorithms, written by Cathy O'Neil. It explores how some big data algorithms are increasingly used in ways that reinforce preexisting inequality. It was longlisted for the 2016 National Book Award for Nonfiction but did not make it through the shortlist. [1] [2] [3] The book has been widely reviewed, [4] and won the Euler Book Prize.
O'Neil, a mathematician, analyses how the use of big data and algorithms in a variety of fields, including insurance, advertising, education, and policing, can lead to decisions that harm the poor, reinforce racism, and amplify inequality. According to National Book Foundation: [1]
Most troubling, they reinforce discrimination: If a poor student can't get a loan because a lending model deems him too risky (by virtue of his zip code), he's then cut off from the kind of education that could pull him out of poverty, and a vicious spiral ensues. Models are propping up the lucky and punishing the downtrodden, creating a "toxic cocktail for democracy."
She posits that these problematic mathematical tools share three key features: they are opaque, unregulated, and difficult to contest. They are also scalable, thereby amplifying any inherent biases to affect increasingly larger populations. WMDs, or Weapons of Math Destruction, are mathematical algorithms that supposedly take human traits and quantify them, resulting in damaging effects and the perpetuation of bias against certain groups of people.
The book received widespread praise for elucidating the consequences of reliance on big data models for structuring socioeconomic resources. Clay Shirky from The New York Times Book Review said "O'Neil does a masterly job explaining the pervasiveness and risks of the algorithms that regulate our lives," while pointing out that "the section on solutions is weaker than the illustration of the problem". [5] Kirkus Reviews praised the book for being "an unusually lucid and readable" discussion of a technical subject. [6]
In 2019, the book won the Euler Book Prize of the Mathematical Association of America. [7]
The number π is a mathematical constant that is the ratio of a circle's circumference to its diameter, approximately equal to 3.14159. The number π appears in many formulae across mathematics and physics. It is an irrational number, meaning that it cannot be expressed exactly as a ratio of two integers, although fractions such as are commonly used to approximate it. Consequently, its decimal representation never ends, nor enters a permanently repeating pattern. It is a transcendental number, meaning that it cannot be a solution of an equation involving only finite sums, products, powers, and integers. The transcendence of π implies that it is impossible to solve the ancient challenge of squaring the circle with a compass and straightedge. The decimal digits of π appear to be randomly distributed, but no proof of this conjecture has been found.
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Charles Louis Fefferman is an American mathematician at Princeton University, where he is currently the Herbert E. Jones, Jr. '43 University Professor of Mathematics. He was awarded the Fields Medal in 1978 for his contributions to mathematical analysis.
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The Euler Book Prize is an award named after Swiss mathematician and physicist Leonhard Euler (1707-1783) and given annually at the Joint Mathematics Meetings by the Mathematical Association of America to an outstanding book in mathematics that is likely to improve the public view of the field.
Catherine ("Cathy") Helen O'Neil is an American mathematician, data scientist, and author. She is the author of the New York Times best-seller Weapons of Math Destruction, and opinion columns in Bloomberg View. O'Neil was active in the Occupy movement.
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Siobhan Roberts is a Canadian science journalist, biographer, and historian of mathematics.
A data economy is a global digital ecosystem in which data is gathered, organized, and exchanged by a network of companies, individuals, and institutions to create economic value. The raw data is collected by a variety of factors, including search engines, social media websites, online vendors, brick and mortar vendors, payment gateways, software as a service (SaaS) purveyors, and an increasing number of firms deploying connected devices on the Internet of Things (IoT). Once collected, this data is typically passed on to individuals or firms, often for a fee. In the United States, the Consumer Financial Protection Bureau and other agencies have developed early models to regulate the data economy.
Digital redlining is the practice of creating and perpetuating inequities between already marginalized groups specifically through the use of digital technologies, digital content, and the internet. The concept of digital redlining is an extension of the practice of redlining in housing discrimination, a historical legal practice in the United States and Canada dating back to the 1930s where red lines were drawn on maps to indicate poor and primarily black neighborhoods that were deemed unsuitable for loans or further development, which created great economic disparities between neighborhoods. The term was popularized by Dr. Chris Gilliard, a privacy scholar, who defines digital redlining as "the creation and maintenance of tech practices, policies, pedagogies, and investment decisions that enforce class boundaries and discriminate against specific groups".
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Government by algorithm is an alternative form of government or social ordering where the usage of computer algorithms is applied to regulations, law enforcement, and generally any aspect of everyday life such as transportation or land registration. The term "government by algorithm" has appeared in academic literature as an alternative for "algorithmic governance" in 2013. A related term, algorithmic regulation, is defined as setting the standard, monitoring and modifying behaviour by means of computational algorithms – automation of judiciary is in its scope. In the context of blockchain, it is also known as blockchain governance.
Ethics of quantification is the study of the ethical issues associated to different forms of visible or invisible forms of quantification. These could include algorithms, metrics/indicators, statistical and mathematical modelling, as noted in a review of various aspects of sociology of quantification.