It All Depends on the Objectives We Choose

WMDs

Weapons of Math Destruction by Cathy O’Neil

Since the first of the year I have been on a tear when it comes to reading.  It is amazing what the winter blues can lead to, when you decide you want to change your habits!

While the books weren’t perfect by any stretch – and I was upset that a couple took up so much of my time – all had things worth highlighting and I can highly recommend two of those on my list.

I wrote about the best of the group earlier on More to Come….  Paul Kalanithi’s beautiful memoir, When Breath Becomes Air, remains with me today, an indication of a work’s ability to go deep into the psyche.

When I posted that review, I mentioned that there were two recent books where I would say, “You should read this.”  So let’s take a look at the second.

Weapons of Math Destruction:  How Big Data Increases Inequality and Threatens Democracy by Cathy O’Neil is the serious non-fiction work that manages to tackle an academic subject – math algorithms – in an enlightening and easy-to-understand fashion. In this 2016 work, O’Neil shows how our lives are being increasingly decided by mathematical models that substitute proxies – such as credit scores – for such hard-to-quantify factors as employee worth.  O’Neil goes through the arc of a person’s life to show how these opaque and unregulated algorithms slot us into types, classes, and levels of potential that have little to do with reality.  As O’Neil states in her introduction, “Profits end up serving as a stand-in, or proxy, for truth.”

Not all mathematical models are bad.  O’Neil notes that baseball represents a healthy case study, in that in comparison to the toxic models seen throughout our lives, baseball models are fair, in part, because they are transparent.

“Baseball also has statistical rigor.  Its gurus have an immense data set at hand, almost all of it directly related to the performance of players in the game.  Moreover, their data is highly relevant to the outcomes they are trying to predict.  This may sound obvious, but as we’ll see throughout the book, the folks building WMDs routinely lack data for the behaviors they’re most interested in.  So they substitute statistical stand-in data, or proxies.  They draw statistical correlation between a person’s zip code or language patterns and her potential to pay back a loan or handle a job.  These correlations are discriminatory, and some of them are illegal.  Baseball models, for the most part, don’t use proxies because they use pertinent inputs like balls, strikes, and hits.”

O’Neil cites three elements of a WMD:  Opacity, Scale, and Damage.  Mathematical models, while often cited as impartial, reflect goals and ideology.  In the fields of finance and big data, part of the goal is wealth, and one outcome is that wealth becomes directly tied to self-worth.  As she saw a growing inequality in the field of Big Data, O’Neil quit her job as a Wall Street quant and began to investigate the issue in earnest.  She found algorithms that “would make sure that those deemed losers would remain that way. A lucky minority would gain ever more control over the data economy, raking in outrageous fortunes and convincing themselves all the while that they deserved it.”

That sounds very familiar in today’s world, with the privileged claiming that they “earned” that privilege, when – in many cases – they were simply born on third base.

Each chapter of this 200 page book looks at a different element of life today.  Interested in going to college?  Welcome to the WMDs that have totally changed our educational system.  Wonder how those particular ads show up on your Facebook feed, and not sure why yours differ from others?  Learn about online propaganda and predatory advertising.

“In 2010, one effective ad featured a photo of President Obama and said: ‘Obama Asks Moms to Return to School: Finish Your Degree—Financial Aid Available to Those Who Qualify.” The ad suggested that the president had signed a new bill aimed at getting mothers back to school. This was a lie. But if it spurred people to click, it served its purpose.

Behind this misleading headline, an entire dirty industry was beavering away.  When a consumer clicked on the ad, according to a ProPublica investigation, she was asked a few questions, including her age and phone number, and was immediately contacted by a for-profit school.  These callers didn’t give her any more information about President Obama’s new bill, because it never existed. Instead they offered to help her borrow money for enrollment.”

O’Neil also looks at justice in the age of Big Data, and how WMDs are working to criminalize poverty. Once you are in the criminal justice system, Big Data makes it very difficult to get a job.  If you land a job, WMDs like scheduling software are designed to increase profits, not support workers.  WMDs frame debt as a moral issue, although almost everyone (beyond the 1 percenters) goes through periods of debt.  In the targeted world of WMDs, insurance companies no longer help society balance its risks but can charge for anticipated costs, hurting the poor most of all.  O’Neil’s final chapter – The Targeted Citizen – is the scariest of all.  If you are on Facebook (and I’m not) you should read this and then decide that you want to stay connected. If you want some insights into why Donald Trump is now president, read this chapter.

This is a book that everyone should read.  The way out of this mess isn’t clear, but O’Neil offers some options:

“We’ve seen time and again that mathematical models can sift through data to locate people who are likely to face great challenges, whether from crime, poverty, or education.  It’s up to society whether to use that intelligence to reject and punish them – or to reach out to them with the resources they need.  We can use the scale and efficiency that make WMDs so pernicious in order to help people.  It all depends on the objectives we choose.”

We are quickly moving from a civilized society to a winner take all, dog eat dog world.  It all depends on our choice.

More to come…

DJB

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