

"Steep Learning Curve" is an Erroneous Metaphor - ckuehne
http://yann.lecun.com/ex/fun/index.html#steep

======
richardw
The original meaning of a steep learning curve was exactly as he says. It's
been changed in popular use from "easy" to "hard".

(Rummage rummage rummage...):

"Early uses of the metaphor focused on the pattern's positive aspect, namely
the potential for quick progress in learning ... Over time, however, the
metaphor has become more commonly used to focus on the pattern's negative
aspect, namely the difficulty of learning once one gets beyond the basics of a
subject."

<http://en.wikipedia.org/wiki/Learning_curve>

"One natural interpretation of such a curve, which was the predominant early
usage (according to Wikipedia) and still exists in some technical circles, is
that the thing being learnt is easy — a great amount of learning happens in a
small amount of time. This is the opposite of the popular usage."

[http://english.stackexchange.com/questions/6209/steep-
learni...](http://english.stackexchange.com/questions/6209/steep-learning-
curve)

"The phrase everyone gets wrong. Outside experimental psychology, where the
term originated, I have never seen a correct usage. Learning curves show
performance (e.g., percent correct) as a function of amount of training (e.g.,
number of trials). A steep learning curve means the organization, person, or
animal quickly went from low to high performance — in other words, learning
was fast."

<http://blog.sethroberts.net/2008/08/18/steep-learning-curve/>

alt.english.usage:

"The learning curve for bridge is not steep - on the contrary. But I have seen
other examples of this confusing of "steep curve" with something that is hard
to learn. The association is probably that it is hard to get uphill, but the
true meaning is that with a steep learning curve a given effort will take you
high up the curve and thus corresponds to something that is easy."

[https://groups.google.com/forum/?hl=en#!topic/alt.usage.engl...](https://groups.google.com/forum/?hl=en#!topic/alt.usage.english/vp1DB6nqj0c)

Definition:

"a graphic representation of progress in learning measured against the time
required to achieve mastery."

...

'The phrase "steep learning curve" is sometimes used incorrectly to mean "hard
to learn" whereas of course it implies rapid learning.'

<http://dictionary.reference.com/browse/learning+curve>

~~~
ckuehne
Thanks. I had seen the Wikipedia entry (but not the stackexchange and the Seth
Roberts post) as well but did not post it because I found it interesting to
see everyone come up with rationalizations for why their usage of the phrase
is 'the correct one'. :)

~~~
richardw
We use it 'wrongly', and will continue to (unless you want to not be
understood), but hey - it's interesting that somehow it got mixed up! I wonder
who got it backwards first?

Similarly, Joel has an article on Hungarian Notation that says common usage is
wrong. Would those who defend the (current, wrong) usage of "steep learning
curve" not find it interesting that the proper H Notation was a lot more
useful than current usage?

<http://www.joelonsoftware.com/articles/Wrong.html>

------
ramanujan
The concept of a "steep curve" is the physical analogy to a steep hill, in
which forward progress/learning requires significant effort. Thus x is
progress and y is the cumulative effort required to achieve that level of
progress.

~~~
ckuehne
"The concept of a 'steep curve' is the physical analogy to a steep hill"

Of course it is. That is likely the reason why the meaning got mixed up in the
first place. The rest of your comment is rationalization (Otherwise, people
would call it cumulative effort curve.). See richardw's sister comment.

------
sixtofour
I understand the objection, but like most idioms the intent is understood, and
like most idioms I've always accepted this one for its intent.

However, you can make it work logically. Look at his graph and imagine the two
curves as hills, both going to the same altitude. X is time, Y is altitude.
You'd have to work much harder in a short time to get to the same altitude as
the shallow hill.

~~~
bradleyland
And unlike a machine, where the y-axis learning value is assumed to be
achievable by any machine of a specific class, humans have a much higher
degree of variability. Some will not reach the top of the curve where things
level off. Thus a steep learning curve means that a greater percentage of
individuals will give up as a result of the more compressed learning
requirements.

------
StavrosK
In related news, scientists discover idioms not mathematically accurate. Movie
at 11.

~~~
sp332
It's "film at 11," which used to mean that the news team actually had footage
of the news, back before it was assumed that everyone had already seen it on
YouTube.

:P

~~~
StavrosK
Really? I always thought that was what TV anchors said after wrapping the
daily news up, i.e. a movie was what was coming up next. However, Wikipedia
agrees with you, so thanks for teaching me something!

------
lilspikey
Or you have your axis the wrong way round...

~~~
billswift
That's what I noticed. If you label the horizontal axis for the amount learned
(more or less equivalent to his "Performance" that he has on the vertical
axis) and the vertical axis for effort required, it would fit standard usage
just fine.

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karamazov
Steepness doesn't have to refer to a graph of time versus skill, and at any
rate the metaphor certainly predates machine learning curves. As others have
pointed out, it's meant to evoke the difficulty of climbing a steep hill
versus one that's flatter. This person is mixing concepts and etymologies
amidst an insufferable air of superiority.

------
dodo53
I think steep learning curves are used in two contexts -

1\. for example at your job - steep learning curve is good, it means learning
/ time is high.

2\. for example programming languages - steep learning curve is (possibly)
bad, it means learning or aptitude /effort is high - lots of effort to gain
aptitude. Somewhat confused by the fact that the reason it's hard is possibly
because the final achievement is more useful (but not necessarily - you can
have hard-to-learn interfaces/processes, that are just badly designed, so
you've only learned to jump silly hoops).

------
rimantas
Metaphor (if it is really a metaphor) is OK for me. I always understood it
this way: time on X, stuff to learn (not some performance) on Y. Somewhere on
that Y is the threshold point and by passing it you cross from "still
learning" to "doing actual work" area.

I admit, time on X may look ambiguous but I kind of look at it as "some
reasonable time interval".

That way something complex will require to learn more going from 0 to
threshold point and hence steeper curve (line) than simpler stuff.

------
smackay
The real problem with this, apart from the inherent ambiguity of English, is
that the axes are never defined so the graph can take any form you want. Steep
(as in climbing) usually denotes effort or adversity - a point which may be
missed by non-native speakers - hence the apparent contradiction when you add
your own labels/axes and interpretation to the graph.

------
simonhamp
What happens when you break "learning" down into specific tasks? Is the
compound learning of lots of simple tasks accurately represented by the
generic "learning" graphs for complex tasks?

Steep may not be the correct word. Complex may be better.

~~~
billswift
That is actually the complaint I have seen most often with command lines - you
need to learn so many commands at the very beginning to do anything useful;
thus producing a steep curve. Once you have the absolutely necessary basic
commands down (cd, pwd, ls, mkdir, chmod, and so on) you can easily add more
commands gradually, as you need them.

------
danielrm26
The progress is the x axis, and the difficulty is the y axis.

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pbreit
It's only erroneous if you define the axes as such.

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pflats
I feel like the graph is a poor choice in illustrating this idea. As it's
central to the argument, the rest of the article falls apart, in my eyes.

First - why do both graphs start the user with 0% performance? Humans come
into a new program/context/etc with prior experience. Put a child who's used
Word before in front of ed, and he'll probably do well. Put him in front of
vim, and he'll probably struggle to write a sentence.

Second, not all performances are created equal. The dependent axis should
probably be some measurable output. Typically, something with a "steep
learning curve" takes longer to master, but has much greater payout in the
end. (If it doesn't, people generally don't learn it.) Compare making TV
Dinner with cooking a family meal. The TV dinner is easier to learn, easier to
master, but having "100% performance" in making TV Dinners is still not on the
level of being even a good cook.

~~~
ckuehne
"I feel like the graph is a poor choice in illustrating this idea. As it's
central to the argument, the rest of the article falls apart, in my eyes."

What, in your eyes, does the word "curve" refer to then?

~~~
notsosteep
I've always pictured a steep learning curve as this -
<http://imgur.com/8Wfih>. One doesn't learn much at first until the "aha"
moment. So I think the metaphor is still correct.

