
Machine Intelligence will supercharge recruiting - lucdudler
https://medium.com/@lucdudler/machine-intelligence-will-supercharge-recruiting-2fd340bec612#.tnixc0e9a
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dmreedy
> A major advantage of employing machine intelligence early in the recruitment
> process is zero bias; candidates are judged purely on their merits.

I am reminded* of the AI Koan [1]:

In the days when Sussman was a novice, Minsky once came to him as he sat
hacking at the PDP-6.

“What are you doing?”, asked Minsky.

“I am training a randomly wired neural net to play Tic-Tac-Toe” Sussman
replied.

“Why is the net wired randomly?”, asked Minsky.

“I do not want it to have any preconceptions of how to play”, Sussman said.

Minsky then shut his eyes.

“Why do you close your eyes?”, Sussman asked his teacher.

“So that the room will be empty.”

At that moment, Sussman was enlightened.

These kinds of systems terrify me; there was the article yesterday about the
mythos of model interpretability, and how ill-defined the term is. I am
equally concerned about its complement, model auditability; how well can the
system explain its decisions, or have them explained. How opaque is the
reasoning of the system behind a given decisions. I agree that there's a fair
argument to be made that useful models are often sufficiently complex such as
to not be understandable in their whole, but I'm not convinced that that's
sufficient reasoning to abandon the cause entirely; it just provides an upper
limit on what can be accomplished.

I know this is, functionally, just an ad, but there are an awful lot of ads
lately with the same breathless enthusiasm for these kinds of poorly-
understood systems.

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* Yes, I know this is tantamount to posting "relevant XKCD" or whatever; the default call/response.

[1]
[http://catb.org/jargon/html/koans.html](http://catb.org/jargon/html/koans.html)

~~~
laxatives
I first heard this koan in high school and dismissed it as nonsense, but it
makes a lot more sense now.

Anyways, in most cases, this sort of thing just scales well. It wont do a
great job in some cases, but it can do well in many, and if you're hiring tens
or hundreds of thousands, thats good enough.

~~~
Smerity
> Anyways, in most cases, this sort of thing just scales well. It wont do a
> great job in some cases, but it can do well in many, and if you're hiring
> tens or hundreds of thousands, thats good enough.

That is a hugely concerning comment. The cases it is least likely do well in
are cases involving minorities or existing prejudice. If we're not wary,
machine learning powered filtering and scoring of resumes could feed in to all
the worst of our existing biases.

