Comment by YouWhy
6 months ago
Bell Labs grew to be a dominant player in an age that was characterized by an oversupply of a manageable number highly capable scientists who did not all have a chance for getting anything resembling funding.
Today we have a huge oversupply of scientists, however there's too many of them to allow judging for potential, and many are not actually capable of dramatic impact.
More generally, a standard critique for "reproducing a golden age" narratives are that the golden age existed within a vastly different ecosystem and indeed - stopped working due to systemic reasons, many of which still apply.
In particular, just blaming 'MBA Management' does little to explain why MBAs appeared in the first place, why they were a preferable alternative to other types of large scale management, and indeed how to avoid relapsing to it over a few years and personnel shifts.
Overall I am afraid this post, while evocative , did not convince me what makes 1517 specifically so different.
> Today we have a huge oversupply of scientists, however there's too many of them to allow judging for potential, and many are not actually capable of dramatic impact.
Realistically speaking it's also much harder to achieve the same level of impact back then as most, not just low-hanging, fruits have been plucked.
> not just low-hanging, fruits have been plucked.
Won't this always be the case?
I mean, if you look back 50 years, they look like low-hanging fruits, but at the time, they weren't, only with the benefit of hindsight do they look like low-hanging fruits.
Similarly people in 50 years will say we had all the low-hanging fruits available today in subject/area/topic X, although we don't see them, as we don't have hindsight yet.
50 years? Nah
Like, these things seem obvious in hindsight even now.
You already have the whole Internet of data. You already have GPUs. All you need to do is just use the GPUs to feed the scraped (and maybe not-so-legally downloaded) data into some artificial neural network and you'll get a rather intelligent AI! How could one possibly think otherwise?
They look high hanging fruits when you haven't yet reached them.
They look low hanging fruits when you have risen above them.
This seems written to sound like a profound piece of wisdom, but I find it difficult to not interperet it as a very flowery way of saying "git gud." If that is indeed what you mean then that is fine, but it is still worth acknowledging that the greater competition for funding of today means scientists of today are not playing the same game as scientists of Bell Labs's time.
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Put another, I think more accurate way: hindsight is always 20/20.
Very often, the thing that seemed impossible that suddenly wasn't anymore looks "obvious" when looking back at the completed solution.
>In particular, just blaming 'MBA Management' does little to explain why MBAs appeared in the first place
Whatever the reason it is definitely not because they are effective managers.
I suspect it's more of a social class phenomenon - they speak the language of the ownership class and that engenders trust.
My theory is when women and lower class men started working as bookkeepers and accountants in post war America a way was need to keep the plumb jobs reserved for the fail sons of the privilege classes.
I could be wrong but while 'business schools' existed before then the MBA as a upper class ivy league thing exactly dates to that time.
Do you have anything to back this up? Or are you looking for a story where none exists?
I ask because this comment seems completely backwards and mostly impossible to implement.
Wasn't it also a time of larger projects being started, which required more coordination? Not that your theory needs to be wrong, it could be amplified.
It's impossible to both maximise your knowledge in a particular field and climbing the organisational ladder. Both are full time jobs.
https://threadreaderapp.com/thread/1918279022032601399.html
There's no oversupply, it's decreasing numbers of "preferable" jobs (i.e. tenured professorships) which at least some people previously preferred to industry, inefficient boom-bust cycles in industry, and bad systems for matching work and people. Local minima and kinetic traps are also well-known to exist within the physical sciences, but apparently when we turn to studying societies, we lose this concept and decide that if MBAs exist, we should consider why rather than also whether they are this point preferable to other managers. I say this as a scientist who thinks a lot of my colleagues are intellectually less capable than I expected going in, who is also often shocked by my own stupidity. Scientists who do not make a dramatic impact are also still an integral part of science, Kuhn's ideas come to mind here. By definition, not everyone can be a top-tier researcher.
It will take you 5 minutes to compile (1) Table 1-1 from https://ncses.nsf.gov/surveys/earned-doctorates/2023 and (2) https://nces.ed.gov/programs/digest/d16/tables/dt16_101.10.a... to see that we produce science PhDs at the same rate we have for decades when normalizing for population. From there, I guess it comes down to considerations of whether the amount of scientific and engineering work as a proportion of total work modern societies need and/or do is going down or not, then whether we expect it should scale with population and/or societal advancement.
Considering the growing complexity of technology, number of productive fields, incoming crises our species faces while we simultaneously turn to more ambitious goals, and the amount of international students doing PhDs, one might actually think we underproduce scientists. Far, far, far more MBAs graduate every year than PhDs.
Thank you, that's a well stated and thorough critique.
A lot of your reaction is towards the notion of dramatic impact. Note that I tend to distinguish between an "intellectually capable" researcher and a "right stuff" researcher, which involves the ability to manage risks in self-led multi-year high-risk high-impact programs.
My icons are Katalin Karikó and James P. Allison, who are not necessarily the brightest people of their fields, and subpar at politics, but are actually very good at making impact (duh).
Circling back to the original thesis, setting up a Bell Labs necessitates spotting out the Karikós and Allisons out of a very large flock of (at best) diligent followers of current academic fashions or (worse) popularity contest winners, and I reckon that's not practically possible today.
>there's too many of them to allow judging
Agree with this in particular as a good symptom of the "tectonic shifts". I usually blame the Baumol effect, i.e., the increasing difficulty of the inherently human task: keeping science education/science educators up-to-date. Especially when faced with the returns on optimizing more "mechanical" processes (including the impressive short term returns on "merely" improving bean-counting or, in Bell Lab's/IBM's later eras, shifting info-processing away from paper)
I doubt AI or VCs* have any significant role to play in reducing the friction in the college-to-self-selling-breakthrough pipeline, but they should certainly channel most of their efforts to improving the "ecosystem" first
TFA has right ideas such as
>Make sure people talk to each other every day.
Which already happens here on HN! (Although it's mostly different daily sets of people but.. the same old sets of ideas?)
*Not if the main marketable usecase for college students is to game existing metrics. And I don't see no Edtech in the RFS either
Update: apologies! I see Edtech in YC's latest RFS. They probably think that Edtech targeted at (self-)teachers would be less controversial & more likely to gain organic traction as well!
Plus there was a lot of "low hanging fruit" from the war time that was yet to be "productify", as we say today.
Radars, computers (Enigma crushers), lasers, many less visible inventions that had a great impact in say, materials science - those barrels had to be durable, planes lighter and faster, etc this allowed do build fancier stuff. Whole nuclear industry and its surrounding.
Another factor: cold war, there was incentive to spend money if only there was some chance to win some advantage.
> Today we have a huge oversupply of scientists, however there's too many of them to allow judging for potential, and many are not actually capable of dramatic impact.
This is a fairly sweeping anti-science statement without any supporting evidence to back it up. Fairly typical of the HN anti-public research hive mind sadly.
Proper disclosure,
I have a graduate degree with a thesis in a STEM field from a university that's occasionally ranked worldwide top-100. I appreciate a lot of my former classmates on a personal level, but do think that a lot of them did not make it as high impact researchers.
Would that clarification qualify my opinion as held in good faith?
IMHO the problem is that "oversupply" is either a normative statement - it's a surplus relative to some idea of what it should be - or a nearly trivial statement - it's a surplus relative to demand and many scientists are thus underemployed. I agree with the latter as a matter of fact, but it is a trivial claim because financial demand (eg: funding and positions, under whatever structure, industrial or academic) is downstream of normative decisions like the former interpretation, rather than exogenous.
Anti-science? Speaking of failing to offer supporting evidence or arguments...
You can claim that dramatic impact is more difficult to attain without being anti-science. There is no iron law that says we must make dramatic impact, whatever that means.
There are a number of potential causes for the recession of progress that one could suggest. For example, someone suggested the absence of low-hanging fruit. This raises the question of what constitutes "dramatic impact". If it means "deepening of the state of knowledge", then I don't quite buy this one, since impact is measured relative to difficulty and the state of knowledge. A refinement or deepening of a good theory may be all you can hope for, which is a testament to the success of the theory. If it means "overturning old theories", then that seems silly. Science isn't about overturning theories. It is about refining our understanding of the world. We might overturn less accurate theories along the way, but that's not the goal. It's a side effect.
Another possibility is that deepening the state of knowledge is becoming more difficult and prohibitive. Still another is that education has become too homogenized, preventing a diversity of fresh perspectives from entering the discussion (Feynman remarked as much; he said he didn't expect any major advanced in science in the near future precisely for this reason).
In any case, none of these positions are "anti-science" or "anti-public research".
> This raises the question of what constitutes "dramatic impact"
That's a valid critique. What I had in mind is the overwhelming prevalence of researchers who in my opinion have never even carried out a high risk high reward project, regardless of impact (not every high risk high reward project is going to make impact, and that's fine).
As example of what I have in mind by high risk high reward, I'd like to point at the work of Katalin Karikó and James P. Allison, both highly untypical science practitioners who have been rejected and indeed denigrated during much of their careers.
There are two root causes that for the most part, grad student do not develop into a Karikó or an Allison:
(a) Most grad students are never put in a position where choosing a high risk high reward project is legitimate.
(b) Many grad student in the first place do not have the character such projects (tolerance to sparse rewards and inclination to long term project risk management)
Regardless of the root cause, I observe that a grad student who was never trained to properly manage a big bet project is not likely to succeed doing that after graduating.
To be clear, I do not blame anyone in that situation. The graduate school system selects candidates for being good underlings to the thesis advisor, and down the road for aligning into field/department politics. There's little wonder to me how this system perpetuates a meek research mentality.
> More generally, a standard critique for "reproducing a golden age" narratives are that the golden age existed within a vastly different ecosystem and indeed - stopped working due to systemic reasons, many of which still apply.
The lack of money to fund research isn't god given, it's a feature of capitalism. You get literally trillions of dollars worth of pension funds sloshing around in need for returns - but fundamental research isn't going to directly and imminently make billions of dollars, the timescale for ROI in basic research is usually measured in decades. So all that money went towards social networks, cryptocurrencies, AI or whatever else is promising the greatest ROI - and that can be argued to all be not to the betterment of society, but actually to its detriment.
It used to be the case that the government, mostly via the proxy "military-industrial complex" provided that money - out of that we got GPS, radar, microwaves, lasers, even the Internet itself - to counteract this. Unfortunately, Republican (or in other countries their respective Conservative equivalents) governments have only cut and cut public R&D spending. And now, here we are, with the entirety of the Western economy seeking to become rent-seekers with as little effort as possible...
And billionaires aren't the rescue either. Some of them prefer to spend their money on compensating for ED by engaging in a rat's race of "who has the bigger yacht/sports team", some of them (like Musk) invest on R&D (SpaceX, Tesla) but with a clear focus on personal goals and not necessarily society as a whole, some of them just love to hoard money like dragons in LoTR, and some try to make up for government cuts in social services and foreign development aid (Gates, Soros), but when was the last time you heard a billionaire just devoting even a small sliver of their wealth to basic R&D that doesn't come with expectations attached (like the ones described in TFA's "patronage" section)?
judging potential is an easy thing to do. anyone who works with a trainee for a month can be a fantastic judge of their potential. the problem is, as you allude to, a lack of funding and of jobs
You presume "works with ___ for a month" is easy.
It involves a month commitment of (trivially, overall) the temp's salary, and a month partial commitment of someone senior enough to make hiring decisions (even as a primary advisor).
I absolutely agree what you describe is both viable and useful, but it's easier to hire good-looking resumes and hope for the best.
we have a huge oversupply of people credentialed as scientists. a large proportion of them are not sciencing, and quite a few of them are contributing negative science.
> why MBAs appeared in the first place, why they were a preferable alternative to other types of large scale management
This is a whole topic of its own, intertwining with the rise of neoliberalism and short-termist managerial capitalism. I don't think we have to get into that every single time we point out a case where short-termist managerialism fails.
Golden age was a time when basic tinkering could bring you to groundbraking discovery. This is of course over now.
Groundbreaking, not "groundbraking".
And as someone else noted: the golden age is ALWAYS in the past, and often in the not-recent but not-ancient, poorly-remembered past.
We probably exist in some future's golden age.