How Data is Driving Inequality

[kalibex]

It's no surprise that inequality in the U.S. is on the rise. But what you might not know is that math is partly to blame.

In a new book, "Weapons of Math Destruction," Cathy O'Neil details all the ways that math is essentially being used for evil (my word, not hers).
From targeted advertising and insurance to education and policing, O'Neil looks at how algorithms and big data are targeting the poor, reinforcing racism and amplifying inequality.

These "WMDs," as she calls them, have three key features: They are opaque, scalable and unfair.

Denied a job because of a personality test? Too bad -- the algorithm said you wouldn't be a good fit. Charged a higher rate for a loan? Well, people in your zip code tend to be riskier borrowers. Received a harsher prison sentence? Here's the thing: Your friends and family have criminal records too, so you're likely to be a repeat offender. (Spoiler: The people on the receiving end of these messages don't actually get an explanation.)

_http://money.cnn.com/2016/09/06/technology/weapons-of-math-destruction/index.html_

 

[mkrnhr]

Yes, "Big Data" is actually the big thing and its techno-priests present it as something infallible and miraculous. The author's blog has many interesting entries and a except from the book was apparently published here: _https://www.theguardian.com/science/2016/sep/01/how-algorithms-rule-our-working-lives

 

[Arwenn]

Just read the articles on both the links posted above. Thank you for posting this kalibex, it is very interesting. Every job my niece applied for recently, including McDonalds and KFC involved creating an account online, and undertaking what seemed to be a profiling or personality test. That was even before you got a chance to interview. It used to be that getting a job was based on your résumé, referees and qualifications/specific skill set.

McDonald’s, for example, recently asked prospective workers to choose which of the following best described them: “It is difficult to be cheerful when there are many problems to take care of” or “Sometimes, I need a push to get started on my work.” In 2014, the Wall Street Journal asked a psychologist who studies behaviour in the workplace, Tomas Chamorro-Premuzic, to analyse thorny questions like these. The first of the two answers to the question from McDonald’s, Chamorro-Premuzic said, captured “individual differences in neuroticism and conscientiousness”; the second, “low ambition and drive”. So the prospective worker is pleading guilty to being either high-strung or lazy. ...Consequently, many of the tests used today force applicants to make difficult choices, likely to leave them with a sinking feeling of “Damned if I do, damned if I don’t”.

_https://www.theguardian.com/science/2016/sep/01/how-algorithms-rule-our-working-lives

These algorithms appear to be locking people who may actually be very well suited to the job from getting them based on answers to these obscure questions. The whole process is totally opaque, as the article says candidates are never told their score or where they went 'wrong'. So sad to see maths or big data being used this way.