Archive for September, 2016
A curve in the road to grade inflation
The New York Times Sunday Review features an opinion by Wharton School Professor Adam Grant as to Why We Should Stop Grading Students on a Curve. He asserts that his peers now give over 40% of their grades at A level—a percentage that has grown steadily for the last 30 years as detailed in this March 2016 report by GradeInflation.com. I am not surprised to see my alma mater the University of Minnesota near the top on the chart of Long Term Grade Inflation by Institution, because, after all, we pride ourselves on being nice.
During my years at the “U” most classes were graded on the curve, which Prof. Grant abhors for creating too much competition between students. However, it worked for me. I especially liked this system in my statistical thermodynamics class where my final score of 15 out of 100 came out second highest out of all the students, that is, grade A. Ha ha. This last week President Obama chastised the U.S. press for giving Trump a pass based on grading on the curve. I see no problem with that. ; )
I do grant Grant an A for creativity in coming up with a lifeline for struggling students. He allows them to write down the name of a brighter classmate on one multiple choice question. If this presumably smarter student gets it right, that question earns full credit. My only suggestion is that whomever gets called in the most for providing lifelines should be graded A for being on top of the curve. But then I see nothing wrong with rewarding the best and the brightest.
The increasing oppression of soul-less algorithms
As I’ve blogged before*, algorithms for engineering and statistical use are near and dear to my heart, but not when they become tools of unscrupulous and naïve manipulators. Thus an essay** published on the first of this month by The Guardian about “How algorithms rule our working lives” gave me some concern. In this case the concern is that employers who rely on mathematically modelled ways of sifting through job applications tend to punish the poor.
“Like gods, these mathematical models are opaque, their workings invisible to all but the highest priests in their domain: mathematicians and computer scientists. Their verdicts, even when wrong or harmful, are beyond dispute or appeal. And they tend to punish the poor and the oppressed in our society, while making the rich richer.”
– Cathy O’Neil
Of course we mustn’t blame algorithms per se, but those who write them and/or put them to wrong use. The University of Oxford advises that mathematicians don’t write evil algorithms. This October 2015 post passes along seven utopian principles for ethical code. Good luck with that!
P.S. A tidbit of trivia that I report in my book RSM Simplified: “algorithm” is an eponym for Al-Khwarizm, a ninth century Persian mathematician who wrote the book on “al-jabr” (i.e., algebra). It may turn out to be the most destructive weapon for oppression ever to emerge from the Middle East.
* Rock on with algorithms? October 2, 2012
** Adapted from Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy — a new book on business statistics coming out tomorrow by “Math Babe” Cathy O’Neil.