Ask HN: Which jobs are getting replaced by machine learning? - KernelDoge
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sospep
Here's an Oxford study of 702 jobs and the probability they'll be
automated.(PDF) [0]

List of jobs table is page 57.

[0]
[http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Futu...](http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf)

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mtdewcmu
Tasks for ML are relatively narrow and specific, so it's hard to see how that
one task, or even a collection of tasks, could be identical to somebody's job.
Jobs are ordinarily not restricted to performing one repetitive mental task
over and over. However, ML could potentially make some jobs easier by speeding
up some tasks, and allow them to be handled by fewer people.

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webmaven
Machine Translation will soon start taking a big bite out of generic
professional translation work (we've already seen Google Translate replace the
sort of translate-by-dictionary-lookup tasks often used by small businesses in
the absence of better options), but will also serve as a productivity tool for
more specialized (usually industry-specific) services.

I don't think this will cut into the translation work of longer prose (fiction
or non-fiction) just yet, but we will see some pressure on some translators to
up their game in terms of translating between cultural contexts, the sort of
thing that makes these so amusing:

[http://www.oxfamblogs.org/fp2p/?p=5672](http://www.oxfamblogs.org/fp2p/?p=5672)
[http://www.lifehack.org/articles/lifestyle/25-things-
british...](http://www.lifehack.org/articles/lifestyle/25-things-british-say-
what-they-actually-mean-that-you-never-knew.html)

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mtdewcmu
As far as I know, machine translations still come back as a jumble of phrases
that you have to figure out like a puzzle. I am skeptical that machine
translation will ever seriously approach professional translation. To
effectively translate, you have to consider the idea being communicated and
make sure that idea comes through, even if you have to creatively substitute
different​ words and phrasing. A machine being able to understand what it's
reading at multiple levels and anticipate possible misunderstandings seems
hopelessly difficult.

~~~
webmaven
Neural Machine Translation has recently passed beyond that "jumble of phrases"
stage, at least for some languages:
[https://www.nytimes.com/2016/12/14/magazine/the-great-ai-
awa...](https://www.nytimes.com/2016/12/14/magazine/the-great-ai-
awakening.html)

It still isn't _quite_ there yet, but the writing seems to be on the wall.

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am_i_down
Professional Tetris players and people who classify pictures of cats and dogs.

Machine learning is not a mature or robust field. Real world applications are
brittle and extremely narrow in scope. The past few years has seen a burst
funding and hype, as a result of deep learning advancements, but that will
gradually wane as all the low hanging fruit is picked. Many applications that
are promising (like self-drive cars and medical classification) will face
major regulatory hurdles. It will take a much more radical (and, frankly,
unexpected) breakthrough before most humans have to worry.

I love to hear an alternate viewpoint.

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techjuice
Stock trading, management, fast food menu pricing and inventory ordering,
delivery route designers, and many more jobs.

Seems there are a large depth of jobs that can be replaced by automation
across all industries at all levels. Not sure what the end goal is for those
moving to automation (save money, speed up production, increase expansion,
etc.) as there could be many good and negative.

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xiaoma
All of them, except "pet".

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bsvalley
Developer.

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id122015
Politician ?

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cJ0th
Sometimes I do wonder whether there are areas in politics where decisions made
by random number generators could lead to better outcomes. Obviously, they
can't make informed decisions. However, they don't get swayed by all those
biases humans are susceptible to.

