How Big Data Increases Inequality and Threatens Democracy

The Film Archives

Published on Mar 23, 2021

Read more:

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,[1][2][3] 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.

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]…

Catherine (“Cathy”) Helen O’Neil is an American mathematician, data scientist, and author. She is the founder of the blog and has written books on data science, including the New York Times best-seller Weapons of Math Destruction. Her opinion columns are published in Bloomberg View. She is a former Director of the Lede Program in Data Practices at Columbia University Graduate School of Journalism’s Tow Center.

She lives in New York City and was active in the Occupy movement.[1]

O’Neil attended UC Berkeley as an undergraduate,[1] received a Ph.D. in mathematics from Harvard University in 1999,[2][3] and afterward held positions in the mathematics departments of MIT and Barnard College,[4] doing research in arithmetic algebraic geometry.[5] She left academia in 2007, and worked for four years in the finance industry, including two years at the hedge fund D. E. Shaw.[6] After becoming disenchanted with the world of finance, O’Neil became involved with the Occupy Wall Street movement,[7][1] participating in its Alternative Banking Group.[8]

She is the founder of the blog[9][10]

Her first book, Doing Data Science, was written with Rachel Schutt and published in 2013.[9] In 2014 she launched the Lede Program in Data Journalism at Columbia.[11]

In 2016, her book Weapons of Math Destruction was published, long-listed for the National Book Award for Nonfiction [12][13] and became a New York Times best-seller.[4]

When the US Department of Housing and Urban Development proposed a revision to the “disparate impact” rule regarding housing discrimination claims in 2019, she collaborated with Harvard Law School’s CyberLaw Clinic comment in their response to the proposal, which used her work to show “how the rule would cause and reinforce harm.”[14]

She is the founder of O’Neil Risk Consulting & Algorithmic Auditing (ORCAA), an algorithmic auditing company.[3][15]

She is currently on the advisory board of the Harvard Data Science Review.[16]

She is a contributor to Bloomberg View.[11]…

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s