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<p>Besides plagiarism, this community would be well-served by taking
a frank look at the remarkable levels of cronyism, collusion, and
subtle--but very real--manipulation that have permeated it for
several decades. In addition to self- , cross-, and suppressive
citation issues, there are many other metrics to look at. To get
started, one could ask the following simple questions and compute
the corresponding statistics:<br>
<br>
1) Over the past four decades, how often has the leadership of any
relevant machine learning foundation changed?<br>
</p>
<p>2) Over the past four decades, what is the degree of
over-representation by members of any particular organization in
things like:<br>
a) organizing and program committees of major machine learning
conferences? b) AI/ML academic department and now also AI/ML
corporate departments? c) editorial boards and other centers of
power and dissemination? <br>
</p>
<p>3) What is the degree of over-representation of any particular
organization in invited talks, workshops, tutorials, or other
"special events", such as official birthday celebrations or
on-stage Q&A sessions with rich and famous people, at major
machine learning scientific conferences? <br>
</p>
<p>Cronyism and collusion are nothing new in human affairs,
including science, and most of the time they are even legal. But
how well do these serve science or society?</p>
<p>The tip of the iceberg.</p>
<p>--Pierre Baldi<br>
</p>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">Subject:
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<td>Re: Connectionists: Scientific Integrity, the 2021
Turing Lecture, etc.</td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">Date: </th>
<td>Wed, 27 Oct 2021 07:52:09 +0000</td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">From: </th>
<td>Schmidhuber Juergen <a class="moz-txt-link-rfc2396E" href="mailto:juergen@idsia.ch"><juergen@idsia.ch></a></td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">To: </th>
<td><a class="moz-txt-link-abbreviated" href="mailto:connectionists@cs.cmu.edu">connectionists@cs.cmu.edu</a>
<a class="moz-txt-link-rfc2396E" href="mailto:connectionists@cs.cmu.edu"><connectionists@cs.cmu.edu></a></td>
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<br>
<br>
Hi, fellow artificial neural network enthusiasts!<br>
<br>
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.<br>
<br>
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
<a class="moz-txt-link-abbreviated" href="mailto:juergen@idsia.ch">juergen@idsia.ch</a>:<br>
<br>
<a class="moz-txt-link-freetext" href="https://people.idsia.ch/~juergen/scientific-integrity-turing-award-deep-learning.html">https://people.idsia.ch/~juergen/scientific-integrity-turing-award-deep-learning.html</a><br>
<br>
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.<br>
<br>
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.<br>
<br>
Thank you all in advance for your help! <br>
Jürgen Schmidhuber<br>
<br>
<br>
<br>
<br>
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