Why Nobel-Winning Scientists Are Getting Older
priceonomics.com
priceonomics.com
I wonder what hypotheses there are for why scientists a century ago were able to be productive earlier. The paper has a few hypotheses that they think are plausible:
(1) Distance to the knowledge frontier is rising. Older scientists only needed to know fields A, B, and C to attack D, but to attack E, newer scientists needed to know A, B, C, and D. This is the hypothesis they think is most likely, and they give evidence showing that the age of patent holders and the team size involved in patents has also been increasing.
(2) May be harder to get resources to do research now. One has to establish a reputation to win grants to do innovative research, and that takes time. Did research cost less a century ago?
My own question: How often does the student that does the Nobel prize winning work win the prize versus it only going to the PI? The involvement of the PI varies wildly. For example, Jocelyn Bell and Antony Hewish wrote the paper that revealed pulsars, but only Hewish (Bell's advisor) won the Nobel prize, although Bell made the initial discovery (Hewish had her looking for quasars with the radio telescope).
I mean specifically the fact that earning a PHD takes longer now and postdoc programs eat up quite a few more years. And both are trending up.
This was mentioned in an article a couple months ago pointing out that many of the best & brightest miss the common childrearing years in favor of their professional development.
The whole "publish-or-perish" game, the difficulty to get a foot in the door at all levels, etc.
Still, there is hope. “New ideas sometimes serve as revolutions,” Jones and Weinberg comment. Revolutions tend to favor the young. The average age-at-discovery, in physics, took a dip at the beginning of the century. This is where Einstein came in, who published his general theory of relativity at 26, and Dirac, who wrote the “fever chill” poem. They attribute this to the impact of quantum mechanics at the beginning of the century, when “the entire worldview of physics changed”
There's a highly recommended books, Thirty Years that Shook Physics: The Story of Quantum Theory (http://www.amazon.com/Thirty-Years-that-Shook-Physics/dp/048...) that in part explains what's happened in the last century and a quarter or so. That amazing 30 years of course produced a rash of Nobels, and in the other Nobel fields then enabled further Noble research, e.g. the 20th Century's preeminent chemist, Linus Pauling, got his Ph.D. at an opportune time for him to do his postdoc work in Europe, and then apply the developing quantum theory to his field.
Molecular genetics, particularly the elucidation of DNA, also resulted in a truly wild ride for a few decades, something I got a feel of when I started doing it in 1977.
Now, a lot of scientists are in Feynman's position, in a time where there's lots of known stuff out there, but achievable Nobel worthy research is less obvious to everyone, including those awarding the prizes.
EDIT: I have put in first 10 Turing awards in the sheet: https://docs.google.com/spreadsheets/d/1fTaSlme8EBJAAYWWjBh_... In case someone wants to join to complete the rest :)
Doesn't it follow naturally that there will come a point where science will practically be limited by the human lifespan? As in, there is so much one has to learn before being a productive researcher that there simply isn't enough time to learn it?
http://en.wikipedia.org/wiki/The_Structure_of_Scientific_Rev...
His finding was that science works by accretion of facts, except that over time, a number of facts that don't fit the established theory build up. Eventually, this reaches a crisis point where you realize that the current models are unable to explain reality, and then they get thrown out (a "paradigm shift") and everything needs to be figured out again from first principles. At this point, younger scientists have the advantage, because the "knowledge frontier" contracts back to nothing (almost...the new theory still has to account for old experimental results).
The last major paradigm shift in physics was a century ago, with the twin discoveries of relativity and quantum mechanics. You could probably argue that we're due for another one soon - the weight of evidence that our understanding of the universe is flawed has been building up, with unexplained results around dark matter/dark energy/cosmology and the failure of superstring theory to make accurate testable predictions. It's pretty likely that within our lifetime physics may become a hot place for brilliant 20-somethings again.
But in the meantime, most of the action has been in computing. The field of practical applications of computer science has been undergoing a paradigm shift approximately every 10 years (wasn't yesterday's top Hacker News story about that?), hence why we see so many young tech billionaires.
How much of that is done by Musk himself is debatable. One of my pet peeves about the Musk fan-club is that he tends to partner with some very brilliant engineers and then get all the credit for the work they do. However, people high up in his companies (more than one of them) have said that he involves himself very extensively in discovering the technology itself, and his bachelors and the first couple years of his Ph.D were both in physics, so it seems likely that he does at least know the science behind what his companies do.
Also, he dropped out of his Ph.D. on the first week. So it appears that he didn't learn too much physics in academia. Rocketry and electric cars don't involve too much advanced physics and he has top notch experts working for him in all the relevant fields.
It already happens and I think this is where AI and robotics play a big part. They will essentially evolve us in thinking as our lives will become too short to gain all the knowledge needed and they will pass the information better while connecting many more dots that can only be seen from a higher macro perspective from a longer life.
A 500 year old AI knowledge bank and study (evolving with time) will be no match for a 70-80 year life in the field. AI will be the great thinking age even though we won't be doing most of it. Yes we have this now with records and digital data but correlation will get more difficult and so much gets lost from age to age. Additionally, a single lifetime will be throttled with AI that can really match or exceed human capability. AI and smarter computers will be our turbo button on science.
We also have to keep in mind that once something has been discovered, it generally takes a lot less time to learn than it did for the person discovering it.
1) With more scientific advances we will hopefully be able to live longer 2) The better we understand a field, the more we can compress and simplify it and have an easier time teaching it. At least this appears to be the case in mathematics, where I can only imagine many years ago something like trigonometry was not well understood and the greatest mathematicians of the time did research to further our understanding of it, but now it's something we're expected to learn in high school. I can only imagine this will happen as well to the current topics of research as well.
Also, being better at predicting talent will help in the sense that more people will manage to reach the frontier of science. Having some strong driving force that forces children to take the necessary tests and follow their predictions will further increase that number.
However, neither would help to lengthen one's career substantially. The best one can win is 25% or so (20 years on a 80 year life span)