[P2P-F] Fwd: Why so-called objective and unbiased algorithms might be actually racist

[Michel Bauwens]

---------- Forwarded message ----------
From: <dailydigest at piqd.com>
Date: Sat, Mar 25, 2017 at 8:00 AM
Subject: Why so-called objective and unbiased algorithms might be actually
racist
To: Michel Bauwens <michelsub2004 at gmail.com>


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Why so-called objective and unbiased algorithms might be actually racist
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In nineteenth century, a Viennese physician Franz Joseph Galland and his
theories gave foundation to *phrenology*, a defunct field of study, once
considered a science, in which conformation of the skull was believed to be
indicative of mental faculties and personality, and was used, for example,
to justify slavery (remember Django Unchained
<https://www.theguardian.com/science/blog/2013/feb/05/django-unchained-racist-science-phrenology>
?).

Now, according to Vocativ, we're faced with a "*computer-aided rehash of
phrenology, with computer vision and learning algorithms standing in for
cranial measurement tools.*"

Existing face recognition programs and their algorithms can predict whether
someone is a “pedophile”, a “terrorist”, or how likely they are to commit a
crime. All this based merely on their facial features.

As a result, as Vocativ points out, "*those who are already
disproportionately targeted by the criminal justice system (...) are again
disproportionately branded by the algorithm*". In other words, "*rather
than removing human biases, the algorithm creates a feedback loop that
reflects and amplifies them*."

Authorities see machine learning systems as useful tools for maintaining
homeland security, steadily increasing
<https://www.biometricupdate.com/201611/dhs-seeking-to-install-more-facial-recognition-system-in-airports>
the use of the facial recognition systems. But the algorithms can also be
dangerous. It particular they can be "*the perfect weapon for authoritarian
leaders because it lets them efficiently and opaquely enforce systems that
are already biased against oppositional and marginalized groups*".

Comprehensive, yet easy-to-read article investigates human impacts of big
data and seeks ways to make the algorithms more ethical. It's not just my
recommendation - Vocative journalists use data-mining technology to find
story leads and angles, so let's assume they know what they're doing.
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racist]
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Source: Joshua Kopstein vocativ.com
<https://www.piqd.com/tracking/technology-politics/why-so-called-objective-and-unbiased-algorithms-might-be-actually-racist/original?cid=627eed218b467b80645dd5ce5b66b877&source=DailyDigestEmail>
Image: R. A. Di Ieso
03/23/2017
How AI Can Aid Authoritarians-And How Humans Fight Back
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