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

[Lina Dencik]

Hi Sheryl,

My colleague Joanna Redden at the Data Justice Lab has put together a Data Harm Record that might be of use: https://datajusticelab.org/data-harm-record/

Best,

Lina

--
Dr Lina Dencik
Senior Lecturer/Director MA Journalism, Media and Communication
Co-Founder Data Justice Lab
PI Data Justice: Understanding datafication in relation to social justice (DATAJUSTICE) ERC Starting Grant 2018-2023
School of Journalism, Media and Culture, Cardiff University
Bute Building, King Edward VII Avenue, Cardiff CF10 3NB
Email: DencikL at cardiff.ac.uk, Tel: +44 (0)29 208 75461
Twitter: @LinaDencik
Fellow, Center for Media, Data and Society, Central European University
________________________________
From: Air-L <air-l-bounces at listserv.aoir.org> on behalf of Sheryl Grant <sherylgrant at gmail.com>
Sent: 14 May 2018 22:28:51
To: air-l at listserv.aoir.org
Subject: [Air-L] cases in which data-driven decision-making went awry

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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