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

[Tsvi Achler]

Ultimately this controversy and others around corruption in academia arises
from the fact that academia is governed by self-selected committees (a
system established in the middle ages) thereby putting oneself in position
to govern is more important than research.

The issue with the ACM is the tip of a greater problem that includes a high
rate of non-replicability, early innovators being ignored and not properly
cited and where popularization gets priority over novelty.

Statements like “they were ahead of their time” is a way of saying the
academic egos at the time would not accept it.  Those that were ultimately
able to popularize new ideas may simply have had the fortune of being alive
at the right time.

Moreover this continues to happen today and in this group.

I think in order to really change things the root cause needs to change.
Otherwise some may perceive this work as just an exercise of
academics jostling for governing positions and ultimately having very
little to do with moving research forward.

The National Bureau of Economics quantified mechanisms of how politics in
academia affect the ability to publish and popularize within two articles
that I referenced in a previous message.

Moreover I think even more costly than crediting the wrong people as in the
ACM, is the inhibition of novel ideas and in that vein it seems no one is
immune.

I noticed Jürgen dismissed my claim of a novel approach by saying it must
be an RNN even though I specifically wrote that those in the field simply
assume it is a recurrent network and that this is part of the difficulty of
presenting novel ideas in today’s environment.

But admittedly discussing my approach on this thread is off topic and
furthermore I have been specifically asked by Jürgen not to write about it,
so I respectfully will not elaborate here.

However, a discussion of how to avoid this problem today would greatly tie
this article together and make it relevant to the present day.  We live in
the information age where companies such as Google, Wikipedia and others
have demonstrated for us alternate ways to rate, digest and present
information through less political methods. (and even fund)

Thus I think without a discussion about the continuing situation today or
committment to modify current trajectories, this article may become just
another snapshot of the academic egos of the time, and we will need a new
article discussing what went wrong for the next phase of research that will
eventually materialize.

Sincerely,

-Tsvi

PS. Also see my video list on ideas to improve Academia for more details
https://www.youtube.com/playlist?list=PLM3bZImI0fj3rM3ZrzSYbfozkf8m4102j

On Tue, Nov 16, 2021 at 11:53 PM Schmidhuber Juergen <juergen at idsia.ch>
wrote:

> In a mature field like math we’d never have such a discussion.
>
> It is well-known that plagiarism may be unintentional (e.g.,
> https://www.ox.ac.uk/students/academic/guidance/skills/plagiarism).
> However, since nobody can read the minds and intentions of others, science
> & tech came up with a _formal_ way of establishing priority: the time
> stamps of publications and patents. If you file your patent one day after
> your competitor, you are scooped, no matter whether you are the original
> inventor, a re-inventor, a great popularizer, or whatever. (In the present
> context, however, we are mostly talking about decades rather than days.)
>
> Randy wrote: "For example, I cite Rumelhart et al (1986) for backprop,
> because that is how I and most other people in the modern field learned
> about this idea, and we know for a fact that they genuinely reinvented it
> and conveyed its implications in a very compelling way.  If I might be
> writing a paper on the history of backprop, or some comprehensive review,
> then yes it would be appropriate to cite older versions that had limited
> impact, being careful to characterize the relationship as one of
> reinvention."
>
> See Sec. XVII of the report: "The deontology of science requires: If one
> `re-invents' something that was already known, and only becomes aware of it
> later, one must at least clarify it later, and correctly give credit in all
> follow-up papers and presentations."
>
> In particular, along the lines of Randy's remarks on historic surveys:
> from a survey like the 2021 Turing lecture you'd expect correct credit
> assignment instead of additional attempts at getting credit for work done
> by others. See Sec. 2 of the report:
> https://people.idsia.ch/~juergen/scientific-integrity-turing-award-deep-learning.html#lbhacm
>
> I also agree with what Barak Pearlmutter wrote on the example of
> backpropagation: "So if you want to cite, say, Seppo Linnainmaa for Reverse
> Mode Automatic Differentiation, you need to have actually read it yourself.
> Otherwise you need to do a bounce citation: `Linnainmaa (1982) described by
> Schmidhuber (2021) as exhibiting a Fortran implementation of Reverse Mode
> Automatic Differentiation' or something like that.'" Indeed, you don't have
> to read Linnainmaa's original 1970 paper on what's now called
> backpropagation, you can read his 1976 journal paper (in English), or
> Griewank's 2012 paper "Who invented the reverse mode of differentiation?"
> in Documenta Mathematica, or other papers on this famous subject, some of
> them cited in my report, which also cites Werbos, who first applied the
> method to NNs in 1982 (but not yet in his 1974 thesis). The report
> continues: "By 1985, compute had become about 1,000 times cheaper than in
> 1970, and the first desktop computers had just become!
>   accessible in wealthier academic labs. Computational experiments then
> demonstrated that backpropagation can yield useful internal representations
> in hidden layers of NNs.[RUM] But this was essentially just an experimental
> analysis of a known method.[BP1-2] And the authors did not cite the prior
> art - not even in later surveys.[DL3,DL3a][DLC]"
>
> I find it interesting what Asim Roy wrote: "In 1975 Tjalling Koopmans and
> Leonid Kantorovich were awarded the Nobel Prize in Economics for their
> contribution in resource allocation and linear programming. Many
> professionals, Koopmans and Kantorovich included, were surprised at
> Dantzig’s exclusion as an honoree. Most individuals familiar with the
> situation considered him to be just as worthy of the prize. [...]
> (Unbeknownst to Dantzig and most other operations researchers in the West,
> a similar method was derived eight years prior by Soviet mathematician
> Leonid V. Kantorovich)." Let's not forget, however, that there is no "Nobel
> Prize in Economics!" (See also this 2010 paper:
> https://people.idsia.ch/~juergen/nobelshare.html)
>
> Jürgen
>
>
>
>
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