[HN Gopher] Dilution of expertise in the rise and fall of collec...
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Dilution of expertise in the rise and fall of collective innovation
 
Author : geox
Score  : 64 points
Date   : 2023-01-09 17:36 UTC (5 hours ago)
 
web link (www.nature.com)
w3m dump (www.nature.com)
 
| svilen_dobrev wrote:
| mmmh.. Paving the way for ML-generated/immitated stuff.. IMO same
| thing in music, recent years. It's easier and easier to produce
| yet-another-immmitation.
 
| 082349872349872 wrote:
| This pattern can be seen in golden age vs current CS papers: the
| former[0] contain multiple ideas per paper, derived from a
| short[1] list of references; the latter often spend pages upon a
| single idea, derived from a huge list of references.
| 
| [0] at least: the classics which still have attention drawn to
| them today
| 
| [1] to be fair, they didn't have much literature from which to
| draw -- maybe a fairer comparison would be "references as
| percentage of literature extant"?
 
  | delusional wrote:
  | [0] is extremely important here, maybe too important to be left
  | in a footnote. When you look back at history it's all too easy
  | to only recall a select few gems and discard the rest. It's
  | possible that the vast majority of research published today
  | will go by the wayside as dead ends or insignificant, while the
  | stuff that ends up having world changing impact will also
  | contain "multiple ideas" and a "short list of references".
  | 
  | I don't have any proof to disagree with you, not even an
  | anecdote, but be cautious of making claims such as these
  | without data. Now will almost always seem uninteresting and
  | pedestrian while the past will seem mysterious and interesting.
 
    | zdw wrote:
    | I tend to agree with this - one time I tried reading through
    | all the Internet RFCs starting at the first one and I would
    | say that probably 80% of the ideas in first 1000 were
    | abandoned quickly, and after that that the % of abandoned
    | went up to 90-95 percent, with a high quantity of vendors
    | trying to push their own solution a standard.
    | 
    | Very pareto principle/sturgeons law there.
 
    | maicro wrote:
    | With respect, in case you or anyone else wasn't aware - this
    | is an example of "survivorship bias":
    | https://en.wikipedia.org/wiki/Survivorship_bias .
 
  | PartiallyTyped wrote:
  | Isn't what you describe simply the consequence of picking low
  | hanging fruits?
  | 
  | it's only seminal papers that involve multiple ideas together,
  | and even those have a lot of mathematics involved to make them
  | stand up to scrutiny tests.
  | 
  | I'd even go as far as to argue that if you took any of the
  | highly cited papers of the last 5 years in ML, 20 years or so
  | back, they'd be even more groundbreaking than that time's
  | seminal work.
 
  | bjornsing wrote:
  | I think you see the same in physics. The extreme example is
  | probably Einstein's "On the electrodynamics of moving bodies"
  | [1], where he laid out the special theory of relativity. It has
  | some incredibly original ideas, and not a single reference. :)
  | 
  | 1. https://www.fourmilab.ch/etexts/einstein/specrel/specrel.pdf
 
  | pnathan wrote:
  | I noticed the same thing when doing my Master's (graduated
  | 2012, work in embedded debuggers), for which I read a heck of a
  | lot of early papers, both the better and the worse (Sturgeon's
  | Law is very real). My SWAG is that a lot of early CS papers
  | were being written by people doing very serious programming;
  | they often did a few years in industry (or they were doing very
  | focused Physics coding) before coming back for the PhD. Too,
  | they were not worried about working within the dominant
  | operating system framework - such things didn't quite exist. So
  | they could give things a fresh go by the simple virtue of
  | starting out on a new computer.
  | 
  | I think the straight BS->PhD pipeline has introduced an
  | "academic" bias, in the bad sense of the word. I also think
  | that the dominance of Linux, Windows, etc have put blinkers on
  | our research.
  | 
  | In any case, you can trace the evolution I describe in the
  | journal https://onlinelibrary.wiley.com/journal/1097024x which
  | has been around for decades.
 
    | RealityVoid wrote:
    | > work in embedded debuggers
    | 
    | That is extremely interesting. I always thought that the
    | debugging tools we have are cool... but we could do _so much
    | more_ to observe the systems we develop. And the scripting
    | languages in most of the embedded debuggers I had worked with
    | sucked.
 
| Barrin92 wrote:
| It reminds me of a chapter in Alex Pentland's book _Social
| Physics_ where he looked at the performance of IIRC eToro traders
| and the degree to which ideas spread among traders and the
| collective returns on investment.
| 
| When there was extreme levels of connectivity and copying between
| traders collective returns went down because diversity of trading
| strategies went down, when there was too little connectivity the
| same thing happened as optimal strategies could not spread
| effectively.
| 
| The maximum returns were achieved somewhere in the middle when
| there was both room for individual new strategies to emerge but
| enough connectivity for good strategies to spread avoiding both a
| sort of herd dynamic and isolation.
 
| pvaldes wrote:
| big words, obscure results
 
  | Enginerrrd wrote:
  | Honestly, I think this is just an academic phrasing of the
  | Eternal September concept. Which... is observed all over. The
  | paper is a bit more general than that though and applies the
  | concept to other social domains.
 
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