As conversations around ethics of data usage grow, both on-and-off campus, different lines are being drawn in the sand. But it really is still a new frontier in that there are no standardized rules, and companies and organizations are encountering new dilemmas every day.
Although, that might slowly be changing. In March of this year, New America released a set of guidelines for the ethical use of data in higher education. Using data analysis to record and track university students has been a controversial topic, especially in the face of Trump’s immigration policies, as these data could potentially be used to out un-documented students. However, even before that there were concerns about how universities could and couldn’t use student data, and where the line was between their own gain and the students’ personal freedoms.
New America is a company that focuses on how America exists in the “Digital Age.” Their initial goal upon creation in 1999 was to help guide American politics in times of change. They are certainly up to their ears in this challenge now, not just in the more traditional political sphere but in attempting to “bridge the gap between technology and policy.”
New America’s guidelines focus less on the usage of personal student data but rather academic performance data. For state schools especially, there has been growing pressure for the majority of students who enroll in a university to actually receive a degree. Meaning, universities should try to minimize the number of students who drop out. The guidelines state that as a result of these pressures, “institutions have begun analyzing demographic and performance data to predict whether a student will enroll at an institution, stay on track in her courses, or require support so that she does not fall behind.”
Their five-point plan, as shown in the infographic above, addresses some big topics, and even covers some ground that we have also covered here on DataCrunch. Point number 4 states: “Design predictive models and algorithms that avoid bias.” This is, of course, a big topic in data analysis, but it could have especially high consequences here. “Without ethical practices, student data could be used to curtail academic success rather than help ensure it,” the guidelines state. And here the concerns circle back around to personal data, specifically knowledge of a student’s income level.
These guidelines were released almost exactly a year from the last time the use of student data in higher education made headlines. In mid-2016, a slew of articles were released debating how universities could benefit from their students’ data without infringing on their privacy. One such article began: “Imagine if a college, using learning analytics, has determined that students of a specific ethnic background who live in a handful of zip codes and score a certain way on standardized tests are highly likely to earn a low grade in an important course — potentially jeopardizing their chances of graduating on time. Should the college actively prevent those students from enrolling in the course?”
New America has stated that there is a gap between technology and policy. However, the above situation would certainly seem prejudicial if someone came to that conclusion by reading a student’s application. So why do the rules seem so different once the information becomes digital data? Are these dilemmas really new? We should think about why these conversations about data ethics are happening at such a large scale, when the connotation seems to be that maybe society’s sense of ethics will land differently once we are working with data. New America’s guidelines are definitely an important and valuable step, but they do not bridge this gap. In the meantime, it is especially important that we try to minimize harmful results when they end up hurting some of the populations of students that are already most vulnerable within a higher institution.