

How Robots and Algorithms Are Taking Over - jonathansizz
http://www.nybooks.com/articles/archives/2015/apr/02/how-robots-algorithms-are-taking-over/?insrc=toc

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jgable
"... In fact, this is already happening, in part because programmers
increasingly rely on 'self-correcting' code—that is, code that debugs and
rewrites itself ..."

What on earth is the author talking about? I've never heard of self-correcting
code, certainly never used it, and can't find a reasonable reference to it
with a google search. Is he mistakenly referring to "Error-Correcting Code",
that is, using redundancy in data storage or transmission to catch and correct
for random bit flips?

~~~
danso
Wow, my opinion of the editing process at the New York Review of Books has
just dropped, by a lot. It's not just that it's a bizarre claim, but that it's
also stated so matter-of-factly. Honestly, the writer probably talked to a
coder friend who uses an IDE, and the way the coder described auto-completion
and type-checking extensions sounded very much like "self-correcting" code.

No matter what you think of difficulties of the Turing halting problem, I'd
say that writers depend --and can benefit -- far more on "self-correcting"
writing (particularly auto-correct) than programmers do on self-correcting
code.

~~~
gtirloni
I think you're overreacting. The author could well be talking about neural
nets, deep learning, etc. We may choose to nitpick or discuss the overall
point.

~~~
arikrak
That could be the next part "machines that are able to learn on the job", but
that's not "code that debugs and rewrites itself".

~~~
ihsw
It's not a far stretch that laymen conflate "code" with "statistical learning
algorithms."

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fernly
It's a hodge-podge of semi-accurate statements about very minor trends (minor
in employment terms) and inaccurate statements that it's hard to critique.
Check this partial paragraph with my thoughts as I read it:

"Meanwhile, algorithms are writing most corporate reports [What? what kind of
reports are we talking about? At first I pictured those glossy end-of-year
things for analysts, but maybe not, anyway - citation needed!] analyzing
intelligence data for the NSA and CIA, [Analyzing? Or just winnowing hopefully
significant items from oceans of chaff for real analysts to look at?] reading
mammograms [OK, valid hit], grading tests [then why are teachers and
professors always still bitching about the time they spend grading?] , and
sniffing out plagiarism [valid, but only a minor adjunct to a professor's
grading life]. Computers fly planes—Nicholas Carr points out that the average
airline pilot is now at the helm of an airplane for about three minutes per
flight [False impression, there has to be an awake and alert trained pilot at
"the helm" 100% of the time regardless of the autopilot]—and they compose
music [BAD music that nobody but a few academics ever listen to and that
certainly does not sell] and pick which pop songs should be recorded based on
which chord progressions and riffs were hits in the past [? that would explain
a lot about current pop...]. Computers pursue drug development—a robot in the
UK named Eve may have just found a new compound to treat malaria [yes there
are interesting machines that try thousands of molecules to find ones that
might work, but that in no way displaces any human bodies; these are NEW
discoveries that wouldn't be made otherwise]—and fill pharmacy vials [as pick-
and-pack machinery has been doing for decades]...

This article is a mess.

~~~
cm127
Your comment is a mess. Most of your "criticisms" seem to follow the logic
that if you haven't personally seen it before, it doesn't exist.

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ZeroFries
Programming will probably look entirely different from what it looks like now
in two decades, but I doubt it will be entirely replaced as a profession in
that time. If it has, the singularity will have been started and everything
will be entirely different anyways.

~~~
hammerandtongs
I think it's pretty foolish that most programmers assume they will always be
"working above the api".

[http://rein.pk/replacing-middle-management-with-
apis/](http://rein.pk/replacing-middle-management-with-apis/)

edit: To clarify, I think AI is the wrong question it's a question of the
layers of abstraction and where it puts you in the labor force. Who cares what
inhuman force is telling you what to do or how fast to do it?

~~~
ZeroFries
I assume there will be no clear definition of where the API begins and where
it ends when this happens. The various systems which employ humans will
probably be mixture of AI and humans working together through multiple
interfaces.

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hugs
I have a hunch the author read someone's explanation of "machine learning
algorithm" and the author changed it to "self-correcting code" along the way.

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Animats
This is supposed to be a book review, but seems to be mostly uninformed
blithering by the reviewer.

Actual physical robots still aren't very good at dealing with the real world
and cost too much. Progress is being made, but it's slow. Having been in the
field, it's been discouraging how slow. Robot manipulation in unstructured
environments is still very weak. "Pick up thing and put it somewhere" works
reasonably well. Beyond that, performance is poor.

The robot cost problem is severe. Look at prices on industrial robots or
intelligent farming equipment.

On the other hand, jobs which involve sitting at a desk and dealing with
inputs and outputs which come in via wires (or paper, for retro outfits) are
looking vulnerable. If they haven't been automated already. Computers are just
so cheap now.

This leads to "Machines should think, people should work." Computers are
better at organization and scheduling than humans. Humans are better at the
grunt work, for now. Consider Uber. Or Amazon's order-fulfillment operations.
It's not clear how far that concept will reach. HouseCall tried to do it for
plumbers and repair services, but didn't get much traction. Uber is in a space
where the product is uniform and the pricing model is simple. HouseCall is
not.

After reading a review like this, it occurs to me that it's probably not too
hard to write a program to review popular non-fiction books. Grind through the
text. Run each chapter through a summarizer like the one that used to come
with Microsoft Word. From the summary, find key phrases and look them up with
Google. Find popular comments on the same subject from people with some
notability. Look at the Amazon sales statistics and generate some prose using
a modified business earnings story generator. Generate a clickbait title and
feed into the Demand Media or AOL content mills.

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b1daly
Articles like this, which I come across enough to have mental category for
them, are hard to take seriously.

It seems to me that of the great problems facing the world that that this is
not one of them. As opposed to vague hypothetical troubles down the road,
there is no shortage of vexing problems clamoring for attention right now.

I think improvements to our political and economic systems, which are under
direct human control, would pay big dividends.

To the extent automation is a malevolent force for humanity, it seems far more
likely that the people and institutions who control this technology will be
the ones who decide whether it is used for good or ill.

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robotresearcher
"While these machines cannot think, per se, ..."

The author appears to have no idea that this might be a controversial
statement.

