Connectionists: Scientific Integrity, the 2021 Turing Lecture, etc.

[Li Zhaoping]

I would find it hard to enter a scientific community if it is not scholarly.

Each of us can do our bit to be scholarly, to set an example, if not a 
warning, to the next generation.

Zhaoping

On 28/10/2021 15:27, Stephen José Hanson wrote:
>
> Well, to  popularize is not to invent.
>
> Many of Juergen's concerns could be solved with some scholarship, such 
> that authors look sometime before 2006 for other relevant references.
>
> This isn't a social issue.. good science writers know they didn't 
> invent the algorithms they are describing for AI applications.
>
> OTOH, Dave Rumelhart, who introduction of the backprop learning 
> methods, often gets confused for gradient descent and
> consequently, Newton *should* be referenced for gosh sakes!
>
>  But keep in mind:  Context matters.   The PDP framework was pretty 
> exclusively about Cognitive Science not about how to solve 
> multivariable engineering problems.     The real value of Dave and 
> PDP, was framing associative learning in networks and how that might 
> provide a foot-hold in understanding cognitive function in the 
> brain.   It was no accident that before Dave became very ill, he was 
> working in Cognitive Neuroscience and doing Brain scanning research.
>
> Sure, if we work at it everything is connected to everything, but 
> other then historical exegesis, this is useless for paradigm change 
> and scientific forward motion.
>
> Steve
>
> On 10/28/21 8:49 AM, Jonathan D. Cohen wrote:
>> As a friendly amendment to both Randy and Danko’s comments, it is 
>> also worth noting that science is an *intrinsically social* endeavor, 
>> and therefore communication is a fundamental factor.  This may help 
>> explain why the *last* person to invent or discover something is the 
>> one who gets the [social] credit.  That is, giving credit to those 
>> who disseminate may even have normative value.  After all, if a tree 
>> falls in the forrest… As for those who care more about discovery and 
>> invention than dissemination, well, for them credit assignment may 
>> not be as important ;^).
>>
>> jdc
>>
>>> On Oct 28, 2021, at 4:23 AM, Danko Nikolic <danko.nikolic at gmail.com 
>>> <mailto:danko.nikolic at gmail.com>> wrote:
>>>
>>> Yes Randall, sadly so. I have seen similar examples in neuroscience 
>>> and philosophy of mind. Often, (but not always), you have to be the 
>>> one who popularizes the thing to get the credit. Sometimes, you can 
>>> get away, you just do the hard conceptual work and others doing for 
>>> you the (also hard) marketing work. The best bet is doing both by 
>>> yourself. Still no guarantee.
>>>
>>> Danko
>>>
>>>
>>> On Thu, 28 Oct 2021, 10:13 Randall O'Reilly <oreilly at ucdavis.edu 
>>> <mailto:oreilly at ucdavis.edu>> wrote:
>>>
>>>     I vaguely remember someone making an interesting case a while
>>>     back that it is the *last* person to invent something that gets
>>>     all the credit.  This is almost by definition: once it is
>>>     sufficiently widely known, nobody can successfully reinvent it; 
>>>     conversely, if it can be successfully reinvented, then the
>>>     previous attempts failed for one reason or another (which may
>>>     have nothing to do with the merit of the work in question).
>>>
>>>     For example, I remember being surprised how little Einstein
>>>     added to what was already established by Lorentz and others, at
>>>     the mathematical level, in the theory of special relativity. 
>>>     But he put those equations into a conceptual framework that
>>>     obviously changed our understanding of basic physical concepts.
>>>     Sometimes, it is not the basic equations etc that matter: it is
>>>     the big picture vision.
>>>
>>>     Cheers,
>>>     - Randy
>>>
>>>     > On Oct 27, 2021, at 12:52 AM, Schmidhuber Juergen
>>>     <juergen at idsia.ch <mailto:juergen at idsia.ch>> wrote:
>>>     >
>>>     > Hi, fellow artificial neural network enthusiasts!
>>>     >
>>>     > The connectionists mailing list is perhaps the oldest mailing
>>>     list on ANNs, and many neural net pioneers are still subscribed
>>>     to it. I am hoping that some of them - as well as their
>>>     contemporaries - might be able to provide additional valuable
>>>     insights into the history of the field.
>>>     >
>>>     > Following the great success of massive open online peer review
>>>     (MOOR) for my 2015 survey of deep learning (now the most cited
>>>     article ever published in the journal Neural Networks), I've
>>>     decided to put forward another piece for MOOR. I want to thank
>>>     the many experts who have already provided me with comments on
>>>     it. Please send additional relevant references and suggestions
>>>     for improvements for the following draft directly to me at
>>>     juergen at idsia.ch <mailto:juergen at idsia.ch>:
>>>     >
>>>     >
>>>     https://people.idsia.ch/~juergen/scientific-integrity-turing-award-deep-learning.html
>>>     <https://people.idsia.ch/~juergen/scientific-integrity-turing-award-deep-learning.html>
>>>     >
>>>     > The above is a point-for-point critique of factual errors in
>>>     ACM's justification of the ACM A. M. Turing Award for deep
>>>     learning and a critique of the Turing Lecture published by ACM
>>>     in July 2021. This work can also be seen as a short history of
>>>     deep learning, at least as far as ACM's errors and the Turing
>>>     Lecture are concerned.
>>>     >
>>>     > I know that some view this as a controversial topic. However,
>>>     it is the very nature of science to resolve controversies
>>>     through facts. Credit assignment is as core to scientific
>>>     history as it is to machine learning. My aim is to ensure that
>>>     the true history of our field is preserved for posterity.
>>>     >
>>>     > Thank you all in advance for your help!
>>>     >
>>>     > Jürgen Schmidhuber
>>>     >
>>>     >
>>>     >
>>>     >
>>>     >
>>>     >
>>>     >
>>>     >
>>>
>>>
>>
> -- 

-- 
Li Zhaoping, Ph.D.
Prof. of Cognitive Science, University of Tuebingen
Head of Department of Sensory and Sensorimotor Systems,
Max Planck Institute for Biological Cybernetics
Author of "Understanding vision: theory, models, and data", Oxford University Press, 2014
www.lizhaoping.org

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20211028/da98059a/attachment.html>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: signature.png
Type: image/png
Size: 19957 bytes
Desc: not available
URL: <http://mailman.srv.cs.cmu.edu/pipermail/connectionists/attachments/20211028/da98059a/attachment.png>