There is no academic field that is free from the liberal social agenda. If you made the assumption that math was void from racial bias, think again. Now the straightforward, strictly data driven field of mathematics is being accused of aiding inequality and racism.

Yup, now data and numbers are being labeled as foes of social justice.

CNN Money reports mathematician Cathy O’Neil concludes in her book “Weapon of Math Destruction” that algorithms and big data are targeting the poor, reinforcing racism and amplifying inequality. O’Neil is a graduate of Harvard University and is also a member of the Occupy Movement. She claims discriminatory algorithms are everywhere including academia, criminal justice system, policing, advertising, and hiring practices.

Or as CNN Money put it:

Math is racist: How data is driving inequality

In an obsequious Time magazine  profile on O’Neil’s book, this alleged insidiousness in math is explored further:

Her work makes particularly disturbing points about how being on the wrong side of an algorithmic decision can snowball in incredibly destructive ways—a young black man, for example, who lives in an area targeted by crime fighting algorithms that add more police to his neighborhood because of higher violent crime rates will necessarily be more likely to be targeted for any petty violation, which adds to a digital profile that could subsequently limit his credit, his job prospects, and so on.

“I worried about the separation between technical models and real people, and about the moral repercussions of that separation,” O’Neil later squawked.

This logic is full of holes. It starts with police being sent to higher crime rate areas determined by data gathered. First, that’s where police should be; where the crime is.  And what type of “petty violations” is she talking about? Police aren’t interested in wasting their time on petty stuff. Comply with the law, and more often than not, you’ll be left alone by law enforcement.

Secondly, suggesting that the use of data is inherently biased ignores the real issue in her hypothetical scenario: crime in minority neighborhoods, which is substantially higher than crime in other communities. We’re talking about seven to ten timeshigher!

Let’s solve the crime problem, not the math problem. Ideas about how to solve the crime epidemic vary greatly. That’s where the discussion should begin; not algorithms.

According to O’Neil, credit scores are another example of racism. Credit scores can be a data point some prospective employers use in making hiring decisions. Some employers use the information to gauge how their job candidate handles money and responsibility. But to O’Neil, the use of credit reports “creates a dangerous poverty cycle. If you can’t get a job because of your credit record, that record will likely get worse, making it even harder to work.”

Her argument can be explained like this: since there is a wealth gap between whites and blacks in America, and blacks are more likely to have poor credit scores due to the disparity, it’s unfair for prospective employers to use the data.

Data are data. There is nothing inherently discriminatory with numbers. In fact, they are very useful to landlords when deciding whom to rent to or with employers in whom to hire, especially when there are many applicants. Of course, employers or landlords are free to use their personal discretion to minimize a poor credit score if he thinks the person is impressive in other areas.

But instead of lamenting the use algorithms in its different forms, perhaps it would be better to analyze the data for what it suggests about our society and our culture. Rather than viewing individuals as victims of their own life choices, it’s important to use so-called big data to help them improve their lot in life.

Personal responsibility would be a good first step.

http://dailysurge.com/2016/09/new-book-weapon-math-destruction-claims-math-racist/