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Dear Gemma,

one massive, glowing, example of bad data could be the recent "mixed 
biometrics" problem with Aadhaar's biometric data, affecting 20 million 
Indian people, mostly in rural areas.
See here:
<http://www.newindianexpress.com/specials/2018/jul/26/biometric-mix-up-affects-nearly-2-crore-aadhaar-holders-1848692.html> 

<https://www.thequint.com/news/india/aadhaar-biometric-data-mix-up>
<https://www.biometricupdate.com/201807/close-to-20-million-aadhaar-records-could-have-mixed-biometrics> 


Kind Regards,
Alberto

-
Alberto Cammozzo
TagMeNot project
http://tagmenot.info
@dontTag, https://twitter.com/dontTag


On 04/09/2018 17:43, Gemma Galdon Clavell wrote:
> Dear all,
>
> We have been working on a project on "Bad Data" for some time, trying 
> to understand what problems raw data can have that impact on people's 
> rights or the functioning of algorithms -thus impacting on everything 
> from fundamental rights (names in Arabic badly transcribed in visas, 
> outdated Schengen bans, etc.) to commercial profiling to everything in 
> between (life chances, jobs, etc.). We are specifically focusing on 
> data problems *before* algorithms kick in.
>
> Data may be corrupted, outdated, badly inputed, misplaced, contain 
> bias at collection, etc.
>
> If you are working or know anyone working on similar issues of have 
> examples, could you please let us know?
>
> Also, if we find a couple of similar projects maybe we could organise 
> a panel at CPDP or another relevant conference?
>
> Please let myself or Griselda know your thoughts!
>
> Kind regards,
>
> Gemma Galdon Clavell, PhD
>
> Eticas Research & Consulting - Barcelona office - 
> www.eticasconsulting.com <http://www.eticasconsulting.com>
>
> <https://www.eticasconsulting.com/>
>
>
> Universitat de Barcelona (UB) - Security, Technology & Society
>
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