
Machine Learning Gender and Racial Biases from Language - mayava
http://spectrum.ieee.org/tech-talk/robotics/artificial-intelligence/ai-learns-gender-and-racial-biases-from-language
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sbierwagen

      The idea of AI picking up the biases within the language 
      texts it trained on may not sound like an earth-
      shattering revelation. But the study helps put the nail 
      in the coffin of the old argument about AI automatically 
      being more objective than humans
    

Was... _anyone_ arguing that a model trained on a natural-language corpus
would be entirely unbiased? What a magnificent strawman.

~~~
zepto
Google has argued that for years.

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sbierwagen
Where?

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mkrum
Breaking News: Algortihm designed to learn how humans use words learns how
humans use words

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mayava
Touche

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mrcactu5
this NLP might be missing perceptions on parts of different groups of
listeners. Different cultures may correlate language and race / gender
differently

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soyiuz
Arrgh. Where is the link to the paper?

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bionsuba
First off, this isn't AI, it's machine learning.

> The idea of AI picking up the biases within the language texts it trained on
> may not sound like an earth-shattering revelation

That's an understatement.

> But the study helps put the nail in the coffin of the old argument about AI
> automatically being more objective than humans

Again, this isn't AI, and anyone with knowledge on the subject has always
known that a traditional machine learning algorithm is only as good as its
training data.

This also seems like a case where the researchers are simply unhappy with the
results they received, rather than being able to show that the results are
wrong.

~~~
TheSpiceIsLife
This is how I like to think about it: the term _Artificial Intelligence_ is
like artificial sweetener. It isn't sugar.

Machine Learning is _artificial intelligence_. When / if computers (or
whatever they evolve in to) actually become _intelligent_ we'll have to drop
the the word _artificial_.

Artificial, adjective:

1\. made by human skill; produced by humans (opposed to natural ). eg.
artificial flowers.

2\. imitation; simulated; sham. eg. artificial vanilla flavouring.

3\. lacking naturalness or spontaneity; forced; contrived; feigned. eg. an
artificial smile.

~~~
x1798DE
_Artificial_ in this context means "man-made", not "fake" or something. If we
create intelligence, it is artificial intelligence.

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Banthum
The word 'bias' implies that the belief is incorrect. If the information is
correct, it shouldn't be called a bias. It is simply a conclusion.

For example: "It also tended to associate "woman" and "girl" with the arts
rather than with mathematics."

This is a correct and valid conclusion. In all societies, women tend to engage
in artistic activity more, while men engage in mathematical/systemic study
more. (This is even more true in places which are more free like Scandinavia,
than it is in less-free places like Iran. Iran has more women in tech
studies.)

An AI learning this is a success, not a 'bias'. It doesn't mean no women
should study these things; it's not a statement about what _should_ be at all.
It's simply an observation about the physical configuration of the world.

II

What these researchers are really discovering is that AI thinks without
morals, and that this reveals the barriers that their own moral convictions
and ideologies have placed in their minds.

An AI has no fear, so it's not afraid of reaching contrarian or politically-
incorrect conclusions. It doesn't know social pressure, so it doesn't know to
manipulate its impressions to follow the socially-acceptable beliefs. It
doesn't know about the Overton window. It has no concept that its conclusions
might lead to some undesirable outcome. It doesn't do motivated reasoning. It
doesn't understand the concept of _should_. It simply describes the world
(through the lens of the data available to it). What they've discovered is not
that the AI is becoming biased, but that they are biased since they're not
willing to reach morally-forbidden facts.

Their own bias appears because they've signed up to the reprehensible idea
that the only reason people should be treated equally is because people are
the same. Which is absurd. The correct morality here is: people are different
and we should treat them equally anyway.

III

"To understand the possible implications, one only need look at the Pulitzer
Prize finalist "Machine Bias" series by ProPublica that showed how a computer
program designed to predict future criminals is biased against black people."

Of course it is. Black people are more likely to commit crimes. Therefore,
like being male or being young, being black is a factor that one can apply
predictively to an estimate of someone's likelihood to commit crimes. This is
definitely true, it's just that people 'mindkill' themselves into not seeing
it because most people are willing to blind their minds to fit into a
socially-accepted morality and thus achieve personal benefit. What's the point
in believing the truth if it doesn't benefit you?

Of course, being male or young are both just as inherent and unchangeable as
being black. But nobody is going to complain when the machine realizes that
youth and maleness predict criminality. We all know which facts are
permissible and which facts are immoral, and thus forbidden.

Religion never went away, it just became non-theistic. If medieval Christians
invented and AI that concluded there was no God, you can be sure they'd want
to 'fix' its 'bias' too.

IV

Language lesson of the day!

Fact: A piece of knowledge which is morally acceptable. Bias: A piece of
knowledge which is morally unacceptable.

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dragonwriter
> Black people are more likely to commit crimes.

Given the existing biases is the systems involved, black people are more
likely to be identified by the existing biased system as having committed a
crime, because they are more likely to be investigated if suspected (or even
without a reasonable basis I of suspicion) of having committed a crime, more
likely to be prosecuted given the same degree of evidence, more likely to be
convicted given the same degree of evidence, and (as a result of all that)
more likely to have a criminal history which subjects them to additional law
enforcement scrutiny and systematic bias on top of that more directly due to
race.

The degree, if any, to which black people are more likely to _actually_ commit
crimes is difficult to tease out since all statistics on this area are
affected, directly and indirectly, by these systematic biases.

(On top of that, there's the bias from the fact that things have been made
crimes, or more sever crimes, _specifically_ , in whole or in part, because
black people were, at the time, more likely to do them.)

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nnfy
Why are people so adamant in denying the potential that blacks on average may
in fact commit more crimes? Even considering that the system is biased, is it
really so difficult to accept that there really IS more crime in poor,
minority neighborhoods?

It is as if those who kowtow to political correctness don't understand that
bias can exist in both directions, and when it comes to making decisions that
affect society in general, both types of bias cause problems.

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dragonwriter
> Why are people so adamant in denying the potential that blacks on average
> may in fact commit more crimes?

If you read GP again, you'll note I never sent the _potential_ at all. I just
note that all the bases for the claim—made in the post it responds to—that
that is a _fact_ and not a _potential_ rests on data affected by known sources
of bias whose magnitude cannot be independently measured and corrected for.

