
Face recognition, bad people and bad data - void_nill
https://www.ben-evans.com/benedictevans/2019/9/6/face-recognition
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SemiTom
Clean data is essential to good results in AI and machine learning, but data
can become biased and less accurate at multiple stages in its lifetime—from
moment it is generated all the way through to when it is processed—and it can
happen in ways that are not always obvious and often difficult to discern
[https://semiengineering.com/where-data-gets-
biased/](https://semiengineering.com/where-data-gets-biased/)

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jszymborski
> Clean data is essential to good results in AI

Your not wrong, but I think this is worth taking a second to clarify.

See, when I think of "clean" data, I think of a set of crisp, noiseless
images, or text without typos, or DNA sequences w/o sequencing errors or low-
quality reads.

For AI purposes, you want a set of representative noise... w/o it, you'll be
building a very brittle model. The key is, as you've mentioned, to assure that
the method of data collection/generation/processing is either (1) unbiased
throughout or (2) is done using various methods ideally performed by different
entities.

So, there is certainly a distinction between bias and noise (the opposite of
which I would probably call "cleanliness").

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xrisxcris
Corporations are slowly integrating this technology and sell these off as
features on newer generation phones like face recognition or finger print
unlocking without the average Joe not knowing the potential threat it might
pose.

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awgneo
When the right to be forgotten becomes plastic surgery.

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shadowprofile77
I don't see why this was downvoted. We really are heading towards exactly such
a future, in which the only psuedo-chance of recapturing privacy will be
through surgeries that modify biometric indicators.

