
How Artificial Intelligence Is Changing Science - gameoflife
https://www.quantamagazine.org/how-artificial-intelligence-is-changing-science-20190311/
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throwawaywego
The article states positive impacts on science, but there are also negative
impacts on science. For instance, the hype of AI has caused a brain-drain on
related fields (such as cognitive science or applied mathematics). AI research
itself suffers from companies buying up the academic talent. And researchers
slap AI (which is usually deep learning) on a decade-old problem, without any
care for complexity/benchmarks, implementation/usage, and proper validation
methods, just to get published or receive funding.

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monocasa
I'm really afraid that ML is mainly just going to become automated p-hacking,
and bring about a dark age to much of science. In a publish or perish world,
how can you compete with someone with enough budget to set a bunch of models
looking for any specious correlations in data sets and publishing what comes
out the other end? Like we'll still have great breakthroughs from the top of
the field, but a lot of grunt work style studies are going to lose their
ability to be trusted.

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rramadass
>ML is mainly just going to become automated p-hacking, and bring about a dark
age to much of science

It is already happening. A lot of people who can contribute to actual Science
are moving into AI/ML field for the money and the industry/media hype are
reinforcing this. Everything is "Deep${NONSENSE}" nowadays whether it is
relevant or not. As a beginner, when i started to learn NNs, i couldn't get
past my initial hurdle on how to validate the results on actual real-world
data. What Statistical metrics do i use to "know" that the blackbox is working
correctly? What are the assumptions and limitations that i need to be aware of
to understand and have faith in the output? Most people don't seem to know or
care; it is "magic" to them. In a world awash with data, reckless application
of NN models to any and every problem is only going to drown us in spurious
results and muddying all Scientific endeavours.

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emiliobumachar
Here's my crackpot idea, in case anyone out there is willing and qualified to
put in the hard work:

Start with a detailed model of the solar system. Make a million copies of it.
In each copy, insert a planet in a random orbit, with random mass. Measure the
orbits of everything, perturbed by the new planet.

Feed the measurements of everything, except the new planet, to an A.I., and
have it estimate the position of the new planet. Give it feedback on how
accurate is was. Repeat a million times. It should learn to pinpoint ninth
planets in solar systems like ours, from the perturbations on orbits of known
bodies.

Then feed it the real measurement history from the real Solar System. It
should output the location of Planet Nine.

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

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starpilot
Orbital equations are straightforward and deterministic, I am wondering why an
AI would be needed for this? You could solve explicitly.

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opportune
Well, an unperturbed orbit is straightforward and deterministic. But three+
body problems (which I believe the original comment is describing) do not have
closed form solutions and are general simulated:
[https://en.wikipedia.org/wiki/Three-
body_problem](https://en.wikipedia.org/wiki/Three-body_problem).

The reason planet nine is suspected to exist is due to the commonalities in
the orbits of trans-neptunian objects. That is, there appears to be a large
gravitational influence on TNOs that causes the distribution of their orbits
to exhibit irregularities that don't make sense with only two factors
influencing their orbits.

~~~
analog31
Indeed, and it's worth generalizing that the vast majority of contemporary
problems do not yield themselves to closed form solutions. We are constantly
finding numerical solutions.

If you went to college when I did, first of all, you're eligible to join the
AARP, and second, the problems that you studied were overwhelmingly solved in
closed form. This was true in math as well, both in college and at the K-12
level.

Now, are ML algorithms worth adding to our tool belt of numerical methods? Oh,
probably. When the fad is over, some useful applications will remain. We
already use regression a lot, and that's a primitive form of ML.

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hadsed
The negative comments here are disappointing. ML is a fantastic tool for
science, where it can propose a model that works as a starting point for
getting to a model that works AND that you can understand.

This is quite common in physics, for example, where people are happy to build
elaborate experiments just to poke at the universe in weird ways. An ML
algorithm is a theorist's particle accelerator where they can treat it as
something to be explored to gain insight.

The reason people are pissed about this is that we're doing this breadth-
first, because the incentives make it that way. People are right to be
concerned if we never get back to deeper analyses, but I'm not at all
concerned.

At some point the low hanging fruit will be gone and every scientific
community will be better off having these new results. As we get better at
probing the black box, and we will because there's a lot of value behind doing
so, we will start to shift back to the deeper questions.

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cheez
It can't really propose a model that is understandable by most human means but
I agree that it can find new relations that we can explore.

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ngcc_hk
Very odd and may I say wrong article. The basic about AI provide a
breakthrough is ok. But I would not call newton law as simulation.

The real development is verbal non-maths theory. Not simulation. In fact this
kind of theory go first. If Aristotle etc. said ... sun must be revolving
about earth. Some basic maths (geometry and algebra).

Observation is the second approach. And a breakthrough. Kepler and later
Galilei watching juipter’s Moon.

Then maths as a tool. Not just simple verbal theory. Calculus, non-Euclid
geometry, wave mechanics, ... to these days physics is nothing but maths like.
The sad thing about social science is only data. Only economic has some maths.
Still data and verbal theory.

Then computer provide data analysis tool as well as simulation and
visualisation. This is an aid more.

Then data as a tool. And the new breakthrough is AI helping to suggest models.

Theory, Mathematical model, Data observation (to disprove, to hint, to post
question and to generate theory based on pattern)

then Various tool to assist above including AI.

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yters
Ever more algorithms and models and data, ever less understanding and
scientific theories.

Soon, instead of "theory of gravity" we'll have "generative DNN of science
papers and grant writing" that no one will understand, but can generate papers
that pass peer review and earn grants and pull in all the monies, effectively
monopolizing and halting all government funded scientific progress.

Meanwhile, actual science will continue on in the amateur ranks, from which
has always come the true breakthroughs.

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thrwayxyz
[[citation needed]]

What has been an amateur science breakthrough in the last century or two which
didn't have at it's base some billions of dollars of government funding.

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AnimalMuppet
The Special Theory of Relativity, from some moonlighting patent clerk.

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nradclif
That was over a century ago (although within the “century or two” limit
specified). But it’s not at all characteristic of the majority of scientific
discoveries made in the last century, which were largely made by professional
scientists and grad students on their way to becoming professionals. The list
of Nobel Prizes in various sciences over the past century I think demonstrates
this.

~~~
cheez
Maybe government money has squeezed out innovation a la Einstein.

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teekert
In my field of science the only thing that changed is that people started
calling algorithms ai. For marketing purposes.

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EGreg
Can we use this to make an app and figure out the optimal diets for everyone?
Or a GAN for generating the funniest jokes?

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jacquesm
> Or a GAN for generating the funniest jokes?

You _really_ want to be careful with that, Monty Python made an excellent
documentary about the weaponization of such high grades of humor and the
results, to put it mildly, weren't funny.

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EGreg
Sorry what? Can you offer us a link?

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D-Coder
More than you want to know:
[https://en.wikipedia.org/wiki/The_Funniest_Joke_in_the_World](https://en.wikipedia.org/wiki/The_Funniest_Joke_in_the_World)

Just the right amount:
[https://www.youtube.com/watch?v=_yo9WHrTvks](https://www.youtube.com/watch?v=_yo9WHrTvks)

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readhn
AI is only as good as the programmer who created it. We are really in the
stone age when it comes to AI.

