Not specifically on data-driven errors, per se, but more generally about systems that either are dysfunctional or create dysfunctionalities, partly based on hwo they are designed, but also on who benefits or suffers from the problems, and what factors reinforce, propagate, and embed those dysfunctions: Rice, R. E. & Cooper, S. (2010). *Organizations and unusual routines: A systems analysis of dysfunctional feedback processes*. Cambridge, UK: Cambridge University Press. On Mon, May 14, 2018 at 3:17 PM, Deborah Lupton <deborah.lupton@gmail.com> wrote:
The Australian Government's social services stuff-up 'robo-debt' is a good example:
https://www.smh.com.au/politics/federal/robo-debt-an- unlawful-exercise-former-appeals-tribunal-member-says-20180405-p4z7x9.html
On Tue, May 15, 2018 at 7:28 AM, Sheryl Grant <sherylgrant@gmail.com> wrote:
I apologize in advance that this is an imperfectly phrased query.
In short, I'm looking for literature about terrible data governance and related issues. Basically, what happens when there are errors in automated data systems, how those errors might have occurred, and what institutions do (or don't) when they discover those errors. Ideally, cases would describe the technical bits as well as the human choices made.
Another way to say it is that my colleagues and I are looking for investigations into data-driven decision-making gone awry.
I've read Kathy O'Neill's Weapons of Math Destruction, which was excellent, and now I'm looking for more specific cases, if they exist.
Thanks,
Sheryl Grant _______________________________________________ The Air-L@listserv.aoir.org mailing list is provided by the Association of Internet Researchers http://aoir.org Subscribe, change options or unsubscribe at: http://listserv.aoir.org/ listinfo.cgi/air-l-aoir.org
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