Algorithms affect your opportunities.

“Opportunity is what connects the politic and the economy; political policies affect people’s opportunities.” (1)

Nowadays, algorithms can also affect people’s economic opportunities.  I know about how algorithms can affect economic opportunities thanks mostly to Cathy O’Neil and her book, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2).  But there’s been mention of algorithms and their effect on people’s chances in two other books I’ve read since the Great Recession: All the Devils Are Here: The Hidden History of the Financial Crisisby Bethany McLean and Joe Nocera (3) and Who Owns the Future? by Jaron Lanier (4).  These books reveal that math formulas are being used to sort huge quantities of information, also called “big data”.  And these formulas can have uneven consequences to the wider economy when they are implemented.  That is to say that some groups will benefit from the use of these formulas and others might suffer.

Here are some examples:

Algorithms have affected everyone in big and small ways.  The Great Recession happened when risk model algorithms looked back only fifty years to estimate mortgage risk.  That fifty year window of time underestimated risk in subprime mortgages.  If the algorithm had gone back 100 years, there would have been a higher risk estimate.  Also, securitization had already moved risk from lenders to investors in the stock market (including municipal bond investors and retirement fund investors).  The Greenspan put was Greenspan’s promise to Wall Street that the Federal Reserve (and Treasury) would help in case of a stock market default on debt.  The Greenspan put spread Wall Street’s risk to Main Street.  But the risk was multiplied when derivatives were brought into existence.  And derivatives like credit default swaps had algorithms based on probability theory that assumed that more diversification was automatically less risky.  And that idea becomes bogus when unqualified buyers are provided loans that they can’t afford to pay.

Good American teachers have sometimes been fired when they couldn’t meet the No-Child-Left-Behind algorithm’s expectations of learning based on testing.  Some teachers have gamed the test, little realizing that they doomed the next teacher in line who couldn’t make up for an algorithm that had a wrong expectation that was based on a prior deception.  Many school districts have been subjected to these federal programs and they account for de-skilling in the teaching profession where teachers are expected to teach their students to pass tests instead of to think critically.  These algorithms may account for the shortages of teachers across the nation.

The Society for Human Resource Management claims in their report from October 12th, 2016, “Big data methods are being used in the employment setting.”  The report states “that 32% of HR professionals reported that their organization uses big data to support HR.”(5)  According to Cathy O’Neil, 60%-70% of prospective employees are subjected to personality testing when they apply for a job (2).

There are a lot of examples of how algorithms are affecting people’s economic opportunities.  From causing harm in the real estate market (30% loss of value initially and now lowest home ownership in 50 years) and banking sector (remember hundreds of failed banks during the Great Recession), to creating strife in the teaching profession, to evaluating employees based on hidden criteria that can disqualify a person and ruin their chance to get a job.  Parole boards can use algorithms to evaluate risk of re-offense.  Prisoners fill out a questionnaire and their answers tend to disqualify poor people in poor neighborhoods (2).

What’s so strange about avalanches of change caused by big data and algorithms is how little discussion is happening in the wake of catastrophies.  No one seems liable for the harms that algorithms are causing society or causing individuals.  Society is part of a grand experiment where algorithms are creating harms and no one is being blamed for them.  Algorithms can be stealthy ways to ruin people’s opportunity in the American landscape.

If you want to learn about how Americans find themselves in our current political and economic environment, there’s a book that outlines it for you: Political Catsup with Economy Fries, available at Amazon.com.

(1)     Mel Scanlan Stahl, Political Catsup with Economy Fries: Liberalism, Pragmatism, Opportunism, (Fast Car Publishing, Spokane, WA, 2015), 102.

(2)     Cathy O’Neil, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, (Crown Publishing Group, New York, 2016).

(3)     Bethany McLean and Joe Nocera, All the Devils Are Here: The Hidden History of the Financial Crisis, (Penguin Group, New York, 2010, 2011).

(4)     Jaron Lanier, Who Owns the Future?, (Simon and Schuster Paperbacks, New York, 2013).

(5)     Eric Dunleavy, Ph.D, Society for Human Resource Management, “Statement of Eric Dunleavy, Ph.D.,” October 12, 2016, http://www.shrm.org/hr-today/public-policy-issues/Documents/EEOC%20Testimony %20on%20Big%20in%20Employment.pdf, accessed Nov. 2016.