[Air-L] cases in which data-driven decision-making went awry

[Sheryl Grant]

Thanks for the replies, all. I'm working my way through them and having a
heyday.

This is what I am trying to drill into: The accuracy of big data
applications will be affected by the accuracy of small data.

And all the things that can go wrong in the data lifecycle that thwart
accuracy.

Many thanks for all your suggestions so I could articulate this better.

Sheryl

On Mon, May 14, 2018 at 7:10 PM, Paul Henman <p.henman at uq.edu.au> wrote:

> Re RoboDebt
>
> See my conference paper Henman, Paul. (2017, September 4). The computer
> says 'DEBT': Towards a critical sociology of algorithms and algorithmic
> governance. Data for Policy Conference 2017. Zenodo. 10.5281/zenodo.884116
> at https://zenodo.org/record/884117#.WcTlEsh97IU
>
> I'm happy to discuss technical bits further if required.
>
> Paul Henman
> Associate Professor of Digital Sociology and Social Policy
> Director, Bachelor of Social Science
> School of Social Science
> University of Queensland  QLD  4072
> T: +61 7 3365 2765 | E: P.Henman at uq.edu.au | W:
> www.digitalsocialpolicy.com
>
> UQ ALLY  - Supporting the diversity of sexuality and gender identity at UQ.
> CRICOS Provider Number: 00025B
> -----Original Message-----
> From: Air-L <air-l-bounces at listserv.aoir.org> On Behalf Of Deborah Lupton
> Sent: Tuesday, 15 May 2018 8:18 AM
> To: Sheryl Grant <sherylgrant at gmail.com>
> Cc: <air-l at listserv.aoir.org> <air-l at listserv.aoir.org>
> Subject: Re: [Air-L] cases in which data-driven decision-making went awry
>
> 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 at 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
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