BY PAUL-OLIVIER DEHAYE
Guest blogger Paul-Olivier Dehaye is a former assistant professor of mathematics at the University of Zurich.
Surveillance capitalism, described by Shoshana Zuboff, is the logic of accumulation of data leading to commodification of a facet of the global digital life. As remarked by Oliver Stone, Pokemon Go fits in this logic, as it encourages everyone to map the public space. It can then slowly alter the reality around the players by introducing “pokestops” and lures near sponsoring businesses.
Likewise, MOOC platforms have played on university rankings and a misplaced sense of competition among universities to lure them all in the same places. In my September–October Academe article, “MOOC Platforms, Surveillance, and Control,” I try to deconstruct the precise dynamics that have now been initiated in online education.
It is certainly understandable that kids would not read terms and conditions before joining their friends on virtual hunts. On the other hand, could university counsels not have insisted on more transparency for students on MOOC platforms? If universities themselves did not have a choice before forming MOOC partnerships, did they leave it to instructors to defend the students’ rights? We suddenly offered a free education to eager students, many with poor digital literacy. Didn’t we help lure them to a watering point, where they will be trapped by a complex chain of coercive consent forms, exploitative of their educational data for years to come?
These trends are of course pervasive and extend beyond education, creating needs for new ethical standards. I do think academia can offer a powerful and positive response. The dominant paradigm is currently for one entity to try to trap the whole “Big Data” value chain. That value is mostly dependent on two variables: volume and variety (academics don’t have much of the constraint of… velocity). While it is merely an execution challenge to scale volume, variety requires more handicraft, since the process merges data from different sources that need to be understood.
This aggregation also runs directly against common expectations of privacy and is, conversely, harder to achieve within constraints of institutional boundaries since the data is siloed.
This means universities, with their loose networks of trust and skills, have a tremendous opportunity to reaffirm their value: the first personal data cooperative has been formed in Zürich, mostly around health data. There is space for many around educational data.
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