

The Rise of Computer-Aided Explanation - ernesto95
https://www.quantamagazine.org/20150723-computer-explanation/

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uint32
_Better than either approach is to take both the objections and the computer-
assisted explanations seriously. Then we might ask the following: What
qualities do traditional explanations have that aren’t currently shared by
computer-assisted explanations? And how can we improve computer-assisted
explanations so that they have those qualities?_

I am interested in this line of reasoning. Can anyone point me to relevant
discussion (preferably scholarly)?

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Animats
We haven't had the rise of computer-aided explanation yet. The article is more
about the problem of not having it. It's needed; "Why did the classifier do
_that_ " is starting to become a big problem. Google is having PR problems
because their image classifier labeled black people as gorillas.

They can probably use their classifier in feedback mode to generate a
canonical image of what the gorilla recognizer is looking for. Publishing that
image would create worse PR problems. But at least there's some way to get
insight into what's happening. That's been a big problem with ANNs - you get a
matrix of values out, but there's no "meaning" associated with it.

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markbnj
>> Chomsky compares the approach to a statistical model of insect behavior.
Given enough video of swarming bees, for example, researchers might devise a
statistical model that allows them to predict what the bees might do next. But
in Chomsky’s opinion it doesn’t impart any true understanding of why the bees
dance in the way that they do.

Chomsky is at liberty to pursue an understanding of bee behavior. The
engineers and scientists who created the system were interested in
translating, not understanding. It seems to me that any system, whether based
on a statistical model or some other approach, that achieves a valid
translation is clearly a success. For all we know the brains of human
translators work similarly.

~~~
fenomas
Indeed. It's easy to intuitively claim that "just" being able to accurately
predict the behavior of a system isn't the same thing as having a "true
understanding" of it, but are there any observable, tangible differences? I
wonder why Chomsky drew the distinction.

One is reminded of Dijkstra's line about how asking whether computers can
think is like asking whether submarines can swim.

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fbrusch
Claiming there's no difference between prediction and understanding reminds me
to what philosophers of science call "instrumentalism": theories are only to
be judged by how well they work in predicting facts. But imagine a world in
which Newton, instead of formulating the law of universal gravitation and the
laws of motion, built a complex machine that, given the relative positions of
a set of planets, could work out their subsequent trajectories, with
astonishing precision. Nobody would be able to explain why it works in any
"deeper" way. Would that world be undistinguishable by ours? If anything,
would have Einstein had the same chances of devising general relativity? And
Schwarzschild of deriving from it that black holes should exist? Doesn't the
fact that we care whether black holes exist, despite how little they
admittedly influence the set of mundane phenomena we observe everyday, imply
that this world is distinguishably different from that with the accurate,
hypothetical Newton black box?

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fenomas
> But imagine a world in which Newton ... built a complex machine that, given
> the relative positions of a set of planets, could work out their subsequent
> trajectories..

Thanks for the reply, I see what you're saying. Just to get metaphysical
though, can't one argue that that's essentially what Newton did? Granted the
machine he made was mathematically elegant, and the study of its components
has been fruitful, but nonetheless it's the nature of physics that one never
knows whether a formalism is really describing what's going on, or whether it
might someday be superseded. Can we not imagine, say, a future where the art
of warping spacetime is so well-understood that Newton's theories about a
gravitational "force" are seen as just a bit of predictive machinery - useful
for making approximations, but bearing no connection to the "truth"
underneath?

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fbrusch
I guess that that's what happened, and what's happening everyday... Newton
action at a distance wasn't convincing enough, so others sought other,
"deeper" explanations, among which most notable is of course general
relativity. (And it's probably noteworthy that, from an "instrumental" point
of view, its benefits were initially marginal...) The difference to me is
between saying "the explanatory power of this current theory can (and will
eventually) be outdone" and "being able to explain is a dimension of no
importance in a scientific theory". Maybe that is Chomsky's concern, even
though this instrumentalist attitude is far from new or unknown (think of
Copenhagen (lack of) interpretation of quantum mechanics, and its (in)famous
motto: "Shut up and calculate"!) If you are interested in this line of
reasoning, I found David Deutsch ("The beginning of infinity") and Karl Popper
("Conjectures and Refutations") two passionate (and opinionated) voices!

~~~
fenomas
Thanks for the recommendations. Admittedly I'm just being perverse in applying
this to fundamental physical laws but the distinction feels very important in
areas like linguistics (where researchers' ideas of "truth" tend not to be
expressible in calculus).

That is, I picture an exchange where a deep-learning researcher says "our
clustering algorithms found that languages A & B share characteristic C", and
a linguistics professor replies "Aha, but the underlying truth is that A & B
belong to the X class of languages, and X-like languages always have C".
Intuitively the latter version somehow feels more robust, but in practice
they're basically equivalent, and the first version arguably carries less
baggage.

