
Machines Beat Humans on a Reading Test - howard941
https://www.quantamagazine.org/machines-beat-humans-on-a-reading-test-but-do-they-understand-20191017
======
chongli
The problem with all of these tests is that they are predefined tasks with an
objective measure. If you can spend a bunch of time optimizing your system
against the measure, you’ll eventually beat humans. Does that mean you’ve
created superhuman intelligence? No!

A human can sit down in front of any of these sorts of tests and do reasonably
well given no prior training whatsoever. None of these systems are capable of
that.

Here is a challenge for an AI researcher: create a system that can beat an
arbitrary, unknown console video game considered easy[1] for humans. You are
not allowed to train your system by having it play video games, since this
test is supposed to measure the ability to learn to play video games for the
first time. Additionally, your system only has access to the I/O that a human
has access to (gamepad inputs, sound and video outputs), no direct access to
console memory by any means.

[1] I consider a video game easy if humans finish it more than 80% of the time
on their first attempt, having never played a video game before in their life.

~~~
rojobuffalo
DeepMind's AlphaZero?

I think it's an incoherent premise to suggest that you could have a human with
no contextual knowledge or experience that pertains to playing an arbitrary
game. There's no blank-slate human that you could test like that. Even the act
of finding food and eating, walking around and avoiding hazards, observing the
movement and behavior of other people and animals..those experiences shape a
person's ability to interpret an environment and model the agents within it.
Those priors would be useful for any first-attempt at a game.

~~~
chongli
Oh, feel free to have your AI read all the books and watch all the films you
want. Heck, you can even let your system read the game’s manual, just as a kid
would do if they got stuck in the game. The only restriction is that it can’t
play any video games as training.

The point of my challenge is to demonstrate understanding by being able to
translate cultural and contextual information into a new medium. So rather
than just making connections between different texts, you need to be able to
take a text and leverage it to understand what’s happening on the screen in a
video game.

~~~
doctorpangloss
Maybe you've already learned this from the replies, but it's not really
possible to have an intellectual dialog about the meaning or limitations of
this research.

So while I get what you're saying and I'm sympathetic to your point of view,
it's too late. The cloud bucks and 5x VC multiples that can be made on this
stuff is too good. Even academics, whose whole advantage is that they can
resist market forces, have very lucrative careers awaiting them if they
publish the right stuff.

Then there's all the adjacent benefits. Like what good does it to be publicly
skeptical of DeepMind? Google is everywhere in tech and science. Or even some
random guy's paper, like where is he going to work? I can count the number of
opportunities on my hand, and they all have a lot of influence in technology
broadly. You don't even have to be doing AI for it to be rational to simply
say, "Wow what an Amazing Discovery" and move along.

There's literally no forum that profits from skepticism. Nobody wins when
"AI," whatever it is attached to, loses.

------
sebringj
I really like this article because it exposes the notion of computation vs.
consciousness. We don't really understand consciousness but have a feeling for
what it means. It could be that approximating consciousness so close, similar
to the concept of limits in calculus would render it the same as what we have
in terms of our inability to ever tell the difference if we cannot define it
in the first place. The behavior of consciousness would be akin to approaching
infinity.

~~~
klodolph
If you don’t know what consciousness means, is that because the word
“consciousness” is vague, or is that because reality itself is vague? It is
the word that is vague. By trying to build artificial consciousness, we are
exploring, and creating machines that challenge our definition and
understanding of the word “consciousness”.

Usually we discover that the machine does not have consciousness and our
definition for “consciousness” was wrong. Sometimes we discover that our
definition of “consciousness” is so bad that we have to go back to the drawing
board and come up with a completely new definition. Same thing happens with
the word “intelligence”.

~~~
Retric
It’s not that consciousness is really vague, it’s more that people use vastly
different definitions for the same word. Medically consciousness has a
relatively low bar, but philosophy loves to overload it with implied meanings.

~~~
semiotagonal
Even medically, you're not evaluating anything about consciousness (i.e.
subjective experience) directly. You're just measuring things that we think
imply consciousness.

~~~
Retric
This is where it get's tricky, some people take consciousness to imply
sentience which requires subjective experience others are happy to with just
awareness.

A venus fly trap is aware of it's environment and has a useful response. In
many peoples books that's consciousness others want to limit things to just
say it's aware but lacks consciousness.

IMO, that's the kind of divide that's prevents meaningful discussions.

~~~
Shorel
> IMO, that's the kind of divide that's prevents meaningful discussions.

It doesn't prevent discussions for the sake of it. It's simply that we don't
know.

Any position you take in this matter is nothing more than unfounded
speculation.

~~~
Retric
These are arbitrary definitions not knowable facts. People can agree that a
standard red laser pointer is red, but exactly what frequency does light
become or stop being red out to 7 decimal places? That’s not something
everyone agrees on and arguing about it is not going to change people’s
opinions.

------
zitterbewegung
Machines perform tasks that require reasoning the same way airplanes fly
without flapping their wings.

This philosophical question keeps on being asked . From my understanding right
now I think it should be approached the same way Feynman approached quantum
physics.

Just train your models.

------
klodolph
At some point we’re going to start asking the same questions about humans. Do
humans really understand what we read, or have we just picked up weird tricks
that happen to work?

(When you read a novel, the experience of reading the novel is different for
everyone. It’s like being on a rollercoaster or amusement park ride. Everyone
has roughly the same stimulus but a different mental landscape and a different
reaction. Our response to the book is largely a response to our own experience
of reading the book, and only partly a response to the content of the book
itself. This distinction isn’t just sophistry. Are we prepared for machines
that react to books in ways that are completely alien to our own reactions?)

~~~
pmoriarty
_" At some point we're going to start asking the same questions about humans.
Do humans really understand what we read, or have we just picked up weird
tricks that happen to work?"_

That question has been asked by philosophers and psychologists for a long
time. There's a branch of philosophy called epistemology -- the study of how
we know what we know -- where questions about whether we even know what we
claim to know (or understand what we claim to understand) belong. In addition,
nearly a hundred years ago behaviorist psychologists were positing that all we
can see is other people's behavior, so making claims about their supposed mind
states, understanding, etc, were unwarranted and effectively off-limits... and
then psychology, cognitive science and linguistics had a backlash against
behaviorists, rejecting their approach and assumptions, with mental states,
thought, and understanding being admissible in the field for many decades now.
So none of this is really new, and mountains of books and papers have been
written discussing and debating such issues for at least a hundred years.

The Chinese Room thought experiment discussed in the article has been a staple
of many Philosophy 101 courses, where the obvious followup question to ask
(even for students just getting their first exposure to philosophy) is whether
humans understand what they read to begin with. Pick up any related philosophy
book and they'll discuss such questions ad nauseum.

Taking a much further step back in to history, more than 2000 years ago, the
Skeptics were questioning whether we can know anything, and some were denying
that anything can be known. Philosophers in the West have been debating such
questions ever since. In Eastern philosophy and religion, such concerns are
also very old, with a variety of people asserting the illusory nature of
worldly knowledge, and positing that true reality is unknowable, or at least
not accessible or limited by rational thought. Similar themes are echoed in
Western mysticism.

Jumping forward yet again (forgive the rambling nature of this response), we
have Descartes Duck[1], and the popular Enlightenment and Post-Enlightenment
view that "man is just a machine". Questions about whether we really
understand or are really doing no more than a sophisticated version of what
the Chinese Room or "dumb" neural networks do could be seen as modern
restatements of that view.

[1] -
[https://en.wikipedia.org/wiki/Digesting_Duck](https://en.wikipedia.org/wiki/Digesting_Duck)

~~~
klodolph
The Chinese room thought experiment is based on logically unsound reasoning
and I don’t understand why it has taken hold as widely as it has. The logical
argument is that a composite object of a book, room, and person following
directions cannot understand Chinese, but there is no justification for this
claim—it is, as far as I can tell, a complete non-sequitur. Perhaps I just
misunderstand it?

Because the logic underlying the Chinese room argument is unsound, it
naturally leads to some bizarre conclusions. I think it’s a bit of a tragedy
that it’s a staple of philosophy 101 courses, unless you use it as an example
for teaching logic by dissecting it and showing how it is unsound.

Personally my view is that as much as we need our scientists and ML
researchers to study epistemology, we need our epistemologists to study
science and mathematics. Any coherent and comprehensive epistemological system
in the future will have to somehow synthesize things like substance monism,
post-Fisherian / post-Bayesian statistics, post-Popper science, and
computational complexity theory. Just as too many ML researchers are reluctant
to dip into philosophy and reinvent a poorer version of old philosohpical
arguments, there are too many philosophers that would rather e.g. rehash some
ideas of Hegel rather than step outside their own field long enough to
synthesize new ideas.

~~~
kthejoker2
Yes, you misunderstand it.

The Chinese Room is a refutation of the Turing Test and similar claims on AGI.
It has nothing to do with the person in the room, but with the outside
observer.

You, the observer, could be convinced by the evidence that a Chinese speaker
is in the room despite that not being the case.

So you can't use outcomes to infer intelligence, and formal computaion of
symbols is not thought. A neural network is still just an extremely fancy,
well tuned lookup table.

------
glofish
I can go to my Google photos, type a query for a: car, bike, chair.

It will produce many images that do contain the object in question. It is
amazing how well it works.

But then it will also produce photos that have nothing even similar to what I
or anyone else would consider "a chair", "a bike" etc.

If the question is now: does Google AI understand what a chair is?

The answer is: obviously it does not. It does something completely different
than "understanding" what a chair is. That method does work well, but it is
not the "chair" we all know about.

~~~
riku_iki
I think your example demonstrates pattern recognition imperfection.

Understanding will start with questions like "cat sitting on the chair".

------
asdfman123
> Machines Beat Humans on a Reading Test. But Do They Understand?

I mean, I was so thoroughly trained to take standardized tests that I really
_didn 't_ understand what I was reading. Through speed-skimming, selective
underlining and recognizing the most probable answers, I was able to speed
through reading tests without doing any normal reading.

Oh, you're talking about machines?

~~~
ppod
>Machines beat humans on a reading test. But do they understand?

I can't link directly to the result, but if you select "co-reference" from the
dropdown, and enter the above text, this demo correctly links "they" to
"Machines".

[https://corenlp.run/](https://corenlp.run/)

------
armitron
"The question of whether machines can think is about as relevant as the
question of whether submarines can swim."

------
carapace
Q: "What can a human do that a machine cannot?"

A: "Answer that question."

Mark Miller pointed out, "A Computer's Perspective on Moore's Law: Humans are
getting more expensive at an exponential rate."

[https://web.archive.org/web/20160316014939/http://www.caplet...](https://web.archive.org/web/20160316014939/http://www.caplet.com/adages.html)

If there's _nothing_ we can do that they can't..?

~~~
Veedrac
> What can a human do that a machine cannot?

The ability to think like a human. The ability to see and recognize the world
around you. The ability to change your behavior. The ability to communicate.
The ability to be free in a society driven by fear and self interest. The
ability to look for love and trust in others. The ability to learn how to love
yourself. The ability to be independent. The ability to be successful by your
own choice.

A human can make you laugh, cry, scream, and cry again.

A human can design, analyze, execute, innovate, understand and apply new
technology. A machine cannot do that.

\- GPT-2 774M (cherry-picked samples)

~~~
carapace
Technically correct, yes, but in a way that misses the point I was trying to
make. (A way that I'm finding very difficult to articulate... Which in itself
is interesting.)

If you want to know the difference between a machine and a human you need a
human to compare to. (That's not quite it either, I think, but perhaps is a
little less obscure?)

------
phaedryx
Whenever I see claims of computers "understanding" I immediately think of the
"Chinese Room" argument.

[https://plato.stanford.edu/entries/chinese-
room/](https://plato.stanford.edu/entries/chinese-room/)

[https://en.wikipedia.org/wiki/Chinese_room](https://en.wikipedia.org/wiki/Chinese_room)

------
catalogia
I find it interesting that so many people are having defensive reactions to
this, trying to explain why they think this 'doesn't count', isn't important
or significant in some way, etc. Perhaps this is rooted in some fear of
obsolescence? I'm not sure.

Rather than thinking _" this machine can't do it as good as me"_, why not
think of ways you could use the machine to enhance your own abilities? I think
it would be really interesting to have a system at my disposal that can "read"
a book and generate book reports/digests. This could allow me to spend less
time reading speculatively and focus more of my (finite) reading time on books
I am already reasonably confident contain what I'm after.

(Edit: maybe it's because the headline frames it as a competition, setting
people to think of themselves competing with the machine, rather than
collaborating with it.)

------
ilaksh
Deep understanding will not come from these methods that are only trained on
text. It will require multi-modal input such as images or video in addition to
text.

