The results suggest that outsiders to a specific scientific field are reluctant to challenge a research star who is viewed as a leader within that field.
I don't think this is how it works at all. I think people are unable to challenge stars in their field.
When everyone is celebrating some star, good luck getting heard if you disagree with them. It is worse if, like so many people, this star will defend their territory by following the maxim "A good offense is the best defense."
My observation of behavior in online forums is that a typical pattern of behavior is that everyone seeks to either align themselves with one of the "stars" of the forum or position themselves as being "against" anything that person says. It is very much about pecking order, not truth, and if you have two or three really popular people, then you get camps that revolve around each person. All conversation tends to default into a polarizing back and forth of "I am for STAR!" and "I am against STAR!"
Since all conversation is framed as either for or against STAR, no conversation can occur that genuinely diverges from the framing given. Even if you genuinely try to diverge from this framing of for or against the idea set that this star individual represents, people will actively paint you into a corner as being in either the for or against camp. Good luck with saying "Yeah, no. That isn't what I am saying At All."
This only stops when that person exits the picture. Dying is the most final and absolute means to exit the picture.
As a specific example look at evolutionary optimization. It's existed for decades, has a bit of a non mainstream cult following, but now the leaders of the field are finding they can beat the fanciest deep reinforcement learning approaches with it.
https://blog.openai.com/evolution-strategies/
How does that fit in this discussion? The stars of deep reinforcement learning haven't exited the picture. Have there been polarized discussions here between the two camps?
Up until the last sentence of the grandparents post, the point was "I think people are unable to challenge stars in their field."
The fact that an alternative perspective that proves simple, effective, and popular in alternative communities is now popularized from stars in the field of deep learning rather than the alternative communities is exactly this.
In fact, the resources available to the stars is much different than what these other communities may have access to such that they may never be able to demonstrate value themselves. It's not very often you have a 720 core machine to run these tests. Resource constrained science exists all over from chemistry, physics, and biotech to computer science. The rich get richer as they say.
However it's also a great instance of solid science to test alternative approaches and I don't mean to take anything away from anyone, but simply to point to a case where that it is extremely difficult for people to challenge stars in the field.
Reminds me of the old Max Planck quote: "A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it."
That would be because that quote inspired the research. However the mechanism that they discovered is actually somewhat more subtle; it is that "rockstar scientists", intentionally or not, suppress radical new ideas coming into their disciplines. Since radical innovation is by and large something that the community-as-a-whole has (in the sense that each person has a tiny probability of coming up with the radical idea so the actual idea-havers are kind of randomly selected from the community), either implicit effects of "oh things are moving so fast in that field, these people are so smart, I will never measure up" or explicit effects of people in the field saying "why the heck would you pursue that path, it's obviously bonkers and we're doing so much better with this other approach..." convince those community members to not come forward with their radical innovation, even as it's sorely needed. Rather than the opponents of the idea dying, they are interested in the cases where the supporters of an idea die, which allows these radical ideas to come out of the woodwork.
One of our group leaders in our research institute learned physics at the dawn of quantum mechanics, saw theory translate into practical applications (e.g. laser technology), and then boost and transform theory again. She is 90+ now.
It was great to hear from her how long it took for the right theories to overcome the barriers of adoption, how fashion works in science, and how many things we think as new are actually really old stuff in new clothes.
Can't believe they didn't cite/discuss the book "The Structure of Scientific Revolutions" (1962) written by philosopher of science, Thomas Kuhn. From the wikipedia article about the book:
"Kuhn challenged the then prevailing view of progress in "normal science". Normal scientific progress was viewed as "development-by-accumulation" of accepted facts and theories. Kuhn argued for an episodic model in which periods of such conceptual continuity in normal science were interrupted by periods of revolutionary science. "
In the paper (see Sci-Hub link comment elsewhere):
Philosophers and historians have long debated the extent to which the pragmatic success of a scientific theory determines how quickly it gains adherents, or its longevity (e.g., Kuhn [1970], Laudan [1977], and their many detractors).
The quote is mostly tongue-in-cheek, but it does occasionally come up as a real issue. I have an anecdote on it:
A former fellow grad student was expressing their dis-belief that though there was a lot of work done in the brain with electrical signals, there is effectively no work done on measuring the magnetic properties of the brain or neurons. The much older and much more esteemed PI that was also present simply shut the student down, to the point of telling them to 'shut up'. "There are no magnetic fields in the brain", I think was the quote. The student, misunderstanding the situation, pressed onward and challenged the PI on fMRI and the like. The discussion turned into a 1-sided argument where the PI basically told the student that they were an idiot and that things like fMRI were useless (actually a debatable point at the time, re: the dead salmon experiments). I'll say I never quite trusted PIs after that dressing-down, they seem to be more concerned about their mortgages than their legacies.
When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong.
As someone who's published in Bayesian inference, that quote has always struck a cord.
I've met countless young researchers who embraced Bayesian practices. And all the opposition seems to come from older hands. It's finally turning a corner... Because of retirement!
I'm guessing what you're talking about is using Bayesian techniques to compute something useful, which nobody will stop you from doing.
The part that has opposition is using a Bayesian justification for the experimental results in a paper -- presenting a conclusion about how we should update our beliefs because of the experiment, instead of a p-value.
Right now it seems pretty common to translate Bayesian experimental results sloppily into frequentist ones to get them past reviewers.
> Right now it seems pretty common to translate Bayesian experimental results sloppily into frequentist ones to get them past reviewers.
This is interesting. I'm glad for a different perspective. I chalk this up to differences across fields, because my experience is so different. My advisor learned Bayesian statistics from Arnold Zellner a few decades ago, and his synopsis of the class was: "It was great in theory, but we could't implement it." Once computers made if more possible, it seems to have spread rather quickly, possibly because computing power was the last piece of a mostly complete puzzle.
It's almost to the point that reviewers prefer the Bayesian approach, in my neck of the academic woods.
This is pretty much my experience as well - accessible Bayesian methods (and now accessible causal inference models) were a major portion in those methods being adopted.
Well if they do not understand Bayesian inference, then they may feel that there needs to good reason to move on from frequentist models...and I'll tell you that case has not been made except for certain specialized disciplines.
Consistent with previous research, the flow of articles by collaborators into affected fields decreases precipitously after the death of a star scientist (relative to control fields). In contrast, we find that the flow of articles by non-collaborators increases by 8% on average.
I haven't read the paper, and maybe this is just completely wrong, but wouldn't we expect the number of published papers by non-collaborators to rise no matter what?
I mean, a star scientist is dead now. There are no more papers coming from that person. Of course other people's papers fill the gap. The number of journals didn't change. The number of articles in an issue of each journal didn't change. These journals need to get articles from someone.
Reminds me of a Douglas Crockford presentation (which is obviously referencing this idea) where he talks about computer science progress, and having to wait for people to die or retire before practices change: "Are they gone yet? Can we stop doing X now?"
Also, "X" for me is OOP as the sine qua non of programming practice. I mean, the concepts of Simula 67 were promoted endlessly in the 80s, but I'm tired of being stuck with that as the primary design mechanism.
"COBOL with separate compilation and parameters" is what we seem to be stuck with, even though the advances in hardware and garbage collection software have made FP type stuff practical now, rather than something that was scoffed at back in the 80s with the advent of microprocessors posing as general purpose computers :-)
Let's not. Let's go ahead and assume such things matter in the here and now and are actively in the way of getting to clinical immortality (assuming clinical immortality is even possible).
I've seen firsthand evidence that jumping between subfields of a given discipline can have great results. A couple of the seminal papers in our field came from super senior researchers moving into simply different areas.
Correlation doesn't imply causation. Maybe they got a very promising idea and chased it into a different subfield? Or maybe there is a filter effect where only the brightest and most ambitious can be bothered to change fields.
Cross pollination of disciplines also seems to bring out great ideas, which makes your (obviously first) proposal sound even better.
Unfortunately, I feel this is similar to that one dessert on the front page of the menu at an expensive restaurant. It looks delicious and tastes even better, but as soon as the bill comes you wondered what in the world you were thinking.
It's not an out-for-good approach, necessarily. But it is a proposal to get you out of your headspace.
The established institution of a sabbatical year (every 7 or so years) fits into this. China also tried a ... not entirely unrelated approach in the 1960s. With mixed results.
The idea that science advances only when old scientists die is used to promote the idea that science has nothing over politics. It is anti-science propaganda.
I will say this though. Young scientists are hungry and there not enough positions for them. Every department has that old rockstar or two who doesn't really push the boundaries of science anymore, but takes up available positions. When they retire or die, new people come in who are still young and full of energy.
> The idea that science advances only when old scientists die is used to promote the idea that science has nothing over politics. It is anti-science propaganda.
Sounds to me like you believe that science proceeds without politics.
> Young scientists are hungry and there not enough positions for them. Every department has that old rockstar or two who doesn't really push the boundaries of science anymore, but takes up available positions. When they retire or die, new people come in who are still young and full of energy.
This process you've described here resembles the political process we observe in government (or any human social system that involves a competitive hierarchy), with the exception that in government the problem of 'taking up available positions' is attenuated by the existence of term limits for most leadership positions.
Of course there are politics in research. But that is moving the goal post. The question is whether politics and science are equivalently grounded, and they are not.
The question is whether politics and science
are equivalently grounded...
Maybe that's how you most frequently encounter this topic, but it's a gross overstatement to say that's the only question here. Was Planck was motivated by anti-science sentiment when he said that? I suspect not.
No one seriously debates whether politics is a factor in science. AFAICT, the the question is entirely to what degree politics influences the progress of science. In my experience, even people with relatively radical views understand this.
Why do you go through the act of arguing when we agree that scientific progress is a mix of politics and science?
My first claim in great grandparent was that the argument that science on progresses when scientists die is used to argue that politics and science are equivalent, that science is reducible to politics. Since we agree that is not so reducible to politics, let us agree that we agree and move on.
You're moving the goalpost. Your initial claim was that the idea was promoted "to prove that science has nothing over politics".
None of the major exponents or scholars of this concept of whom I'm aware -- Bohr, Kuhn, Oreskes, and others -- have as their primary motivation any desire to demote or debunk science. If you're going to make that claim, you'll have to substantiate it. You've failed to do so. Twice.
Yes my claim is that this idea is promoted to demote science to mere politics, but left unsaid by me was that I was targeting my complaint to the leaders of anti-science movements (climate change denial) who seek to claim moral equivalency so that they might push policies that benefit them politically and financially. I did not offer evidence to support this claim, except as a claim from memory, and don't want to be bothered to look for quotes.
So my argument was underspecified, which led you to believe I was referring to the like of Bohr, Kuhn, Oreskes and other serious thinkers, which I was not.
I'll offer as an excellent case study in development and establishment of new scientific theory, the emergence of plate tectonics (or continental drift theory). Naomi Oreskes, a tireless advocate of real science, and debunker of pseudoscience and disinformation (see Merchants of Doubt) documents the four-century-long battle to establish the concept in her books PLATE TECTONICS: The Insiders’ History of the Modern Theory of the Earth and The Rejection of Continental Drift, along with several further articles on the topic.
"Every department has that old rockstar or two who doesn't really push the boundaries of science anymore, but takes up available positions. When they retire or die, new people come in who are still young and full of energy."
Which is basically the norm for a lot of industries. I'm not even sure I mind this sort of thing so long as they are still contributing and producing. I just wish there were enough space for the young folks to do their stuff too.
Given that new ideas in a field often get reviewed by incumbents in said field (due to the requirements of pre-publication peer review) this can certainly delay their uptake or even full examination.
This kind of ingrained conservatism can delay progress both of a field and those examining it. It is a catch-22 as you want qualified reviewers to examine a paper so it isn't bunkum but equally those reviewers may slow it down because it is a valid advance in contrary to their position.
Perhaps a move to post-publication peer review and greater pre-print deposition would help, but that would take a deep cultural shift.
But as always it doesn't have to be that way, it has arrived at this point due to a combination of sometimes perverse incentives and natural human tendencies.
I was thinking for a while that having a mandatory retirement age could be a good idea, but retirement is becoming obsolete for economic reasons, and scientists are now employed in so many different ways by so many different institutions that I don't think it is possible.
Alternative explanation: Star scientists are just highly productive scientists. After they die, their not-as-productive collaborators can't keep up with the amount of publication as high as before. Naturally collaborators publication percentage falls while Non-collaborators' rise.
Maybe it is all about funding, the established scientists will receive the greatest chance of getting a grant because they have their previous work to support their ability and direction. Challenging scientists may not be able to contest the established scientists because of this
Using CC-BY would be an improvement, though the intent here is at least relatively clear.
I've seen worse. Went a few rounds back in the 2000s with a developer who'd claimed simply "this has no copyright". I pointed out the several problems with that claim, and the (almost wholly) trivial approaches to fixing them.
It is, legally, difficult to divest yourself of copyright. Some people say it's possible, some people say it isn't.
It's not difficult to divest yourself of your exclusive rights under copyright. Which is what the WTFPL accomplishes. It's a subtle but significant distinction.
Similarly, you could:
1. Simply disclaim any copyright interest. "I disclaim all copyright interest in this work."
2. Disclaim any exclusive rights: "I disclaim all rights under copyright in this work."
3. Allow others any exclusive rights: "I grant to all parties any exclusive right under copyright."
Etc.
The fundamental problem is that under Berne Convention copyright, which dates to the early 20th / late 19th century (I'd have to check) in at least some jurisdictions, copyright is manifest at creation in any work. Which means these very words as I'm writing them. And there's no procedure for disclaiming those rights.
The Berne Convention rules have been adopted widely particularly since the 1970s.
Again: there are those who disagree that you can't claim a work is "uncopyrighted", but the ambiguity of such a comment (and the trivial means by which that ambiguity is removed) makes certain uses highly imprudent.
It happens over a shorter timeframe than funerals are needed to explain. The past decade or decade and a half has been long enough to see outsiders having significant influence in the aging research community, steering it from determined non-intervention to greater willingness to work towards therapies capable of addressing the causes of aging. All of the players are the same at the start and the end, aside from the new faces coming in from outside.
You're failing to consider any number of reasons this wouldn't fix the problem:
1. Future-value discounting. Even an immortal may well value present experiences over future ones.
2. Consolidation of power. There's little evidence that any system based on perpetuities won't result in the accumulation of wealth and/or power in a limited set of hands.
3. Strategic intentional long-term power consolidation. If you live forever, you'll be concerned forever about upstarts seeking to claim / disrupt your space / power base.
I'm trying to access the source paper for this study, and am finding that despite NBER and SSRN, both generally open-access sites, as hosts, the PDF itself is paywalled on SSRN.
The backstory here is that SSRN, a site for open dissemination of largely pre-publication papers, was bought by Elsevier in 2013, to the loud dismay of the open-access community.
It seems that the predictions of what would transpire are being fully born out.
I don't know if I agree with this. We're having a revolution in NN-based statistical modeling and machine learning, not AI. And it's not happening because Minsky was holding back the field, it's happening because GPUs improved to the point where these models could work and investing in them made economic sense.
I think you may be kidding (and if so, hats off, because citing Hawkins as a sage, and misspelling his name, is some choice dry humor). But in case you aren't:
The whole "Minsky and Papert killed the perceptron" lesson-in-a-nutshell was a historical anecdote at the time the connectionist resurgence started in the 1980s with backprop. I.e., Minsky was already in the distant past by the 1990s, having no influence on connectionism or the NIPS crowd, from which large-scale machine learning eventually sprung.
I don't think this is how it works at all. I think people are unable to challenge stars in their field.
When everyone is celebrating some star, good luck getting heard if you disagree with them. It is worse if, like so many people, this star will defend their territory by following the maxim "A good offense is the best defense."
My observation of behavior in online forums is that a typical pattern of behavior is that everyone seeks to either align themselves with one of the "stars" of the forum or position themselves as being "against" anything that person says. It is very much about pecking order, not truth, and if you have two or three really popular people, then you get camps that revolve around each person. All conversation tends to default into a polarizing back and forth of "I am for STAR!" and "I am against STAR!"
Since all conversation is framed as either for or against STAR, no conversation can occur that genuinely diverges from the framing given. Even if you genuinely try to diverge from this framing of for or against the idea set that this star individual represents, people will actively paint you into a corner as being in either the for or against camp. Good luck with saying "Yeah, no. That isn't what I am saying At All."
This only stops when that person exits the picture. Dying is the most final and absolute means to exit the picture.