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The official blog of @SCHEVResearch at the State Council of Higher Education for Virginia. Discussions about our work, national higher education data policy, and highlights about the data we publish.

 

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Things to Read, May 2017

by Tod Massa 12. May 2017 16:42

If your institution is delving into the use of predictive analytics, I hope you have read this excellent brief from New America (https://www.newamerica.org/education-policy/policy-papers/predictive-analytics-higher-education/#guiding-practice-5-meet-institutional-goals-and-improve-student-outcomes-by-intervening-with-care) about the ethical use of predictive analytics in higher education. Some of you may recall that I raised this issue two years ago during the institutional meetings and wrote about it here. I suggested that institutions should develop a statement of ethical use regarding these tools. I think this document is a great starting point.

While you are doing that, you should also order a copy of Weapons of Math Destruction by Cathy O’Neal (https://www.amazon.com/Weapons-Math-Destruction-Increases-Inequality/dp/0553418815). You can find her blog at mathbabe.org. O’Neal is a former math professor and data scientist who has worked in the private sector in several capacities. She has enough inside experience and expertise to share what are essentially some very frightening concerns about Big Data and the algorithms that manipulate it.

As readers of this blog, you are likely to be particularly interested in chapter three “Arms Race: Going to College.” O’Neal uses the America’s Best Colleges surveys and reports from US News and World Report to show the consequences of an algorithm even when it does not rely on Big Data. Algorithms lacking in full transparency, data that directly measure inputs, outputs, and processes, can be destructive in their unintended consequences. I think you will find it marvelously relevant to our work. When you consider these effects in after reading chapter five, “Civilian Casualties: Criminal Justice in the Age of Big Data,” you will become particularly sensitive to the risks of improper use of Big Data and/or predictive analytics, if you aren’t already.

 

Weapons of Math Destruction is an easy, non-technical read with plenty of stories and examples that allow the reader to see the problems clearly.

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