> An alternative image is that the scientific fruit-pickers are building a scaffold, so that more fruit is always within arm’s reach. Unless we’re arguing that the scaffold is nearing the top of the tree of knowledge, there’s always low-hanging fruit to be picked. Somebody will pick it, and whether or not they become a legendary figure depends on factors other than just how juicy their apple turned out to be. The reaching-for-fruit action is always equally effortful, but the act of scaffold-building gets more efficient every year. In literal terms, previous scientific discoveries and capital investments permit achievements that would have been inaccessible to earlier researchers, and we’re getting better at it all the time.
I don’t agree with this, for reasons discussed here. I think that empirically, it seems to get harder over time (at least per capita) to produce acclaimed works. I agree that there are other factors in who ends up “legendary,” but I think that’s one of them.
> Consider also that either this heuristic was either false at one point (i.e. it used to be the right decision to go into science to achieve “greatness,” but isn’t anymore), or else the heuristic is itself wrong (because so many obvious candidates for “great innovator” were all in academic science and working in established fields with fairly clear career tracks). If it used to be true that going into academic science was the right move to achieve scientific greatness, but isn’t anymore, then when and why did that stop being true? How do we know?
The heuristic is “to match the greats, don’t follow in their footsteps.” I think the most acclaimed scientists disproportionately followed this general heuristic—they disproportionately asked important/interesting questions that hadn’t gotten much attention, rather than working on the kinds of things that had well-established and -understood traditions and could easily impress their acquaintances. For much of the history of science, this was consistent with doing traditional academic science (which wasn’t yet particularly traditional); today, I think it is much less so.
As science progresses, it unlocks engineering possibilities combinatorially. This induces demand for and creates a supply of a healthier/more educated population with a larger number of researchers, many of whom are employed in building and managing our infrastructure rather than finding seminal ideas.
So what we’re witnessing isn’t scientific innovations becoming harder to find. Instead, scientific innovations produce so many engineering opportunities that they induce demand for an enormous number of engineers. The result is that an ever-decreasing fraction of the population is working in science, and science has to compete with an ever-larger and more lucrative engineering industry to attract the best and brightest.
In support of this, notice that the decline you find in scientific progress roughly begins in the early days of the industrial revolution (mid-late 1700s).
On top of that, I think we have to consider the tech-tree narrative of science history writing. Do you imagine that, even if you’d found that science today was becoming apparently more efficient relative to effective population, that scientific history writers would say “we’re going to have to cut out some of those Enlightenment figures to make room for all this amazing stuff going on in biotech!”?
It’s not that historians are biased in favor of the past, and give short shrift to the greatness of modern science and technology. It’s that their approach to historiography is one of tracing the development of ideas over time.
Page limits are page limits, and they’re not going to compress the past indefinitely in order to give adequate room for the present. They’re writing histories, after all. The end result, though, is that Murray’s sources will simply run out of room to cover modern science in the depth it deserves. This isn’t about “bad taste,” but about page limits and historiographical traditions.
These two forces explain both the numerator and the denominator in your charts of scientific efficiency.
This isn’t a story of bias, decline, or “peak science.” It’s a story of how ever-accelerating investment in engineering, along with histories written to educate about the history of ideas rather than to make a time-neutral quantification of eminence, combine to give a superficial impression of stagnation.
If anything, under this thesis, scientific progress and the academy is suffering precisely because of the perception you’re articulating here. The excitement and lucre associated with industry steers investment and talent away from investment in basic academic science. The faster this happens, the more stagnant the university looks as an ever-larger fraction of technical progress (including both engineering and science) happens outside the academy. And the world eats its seedcorn.
> An alternative image is that the scientific fruit-pickers are building a scaffold, so that more fruit is always within arm’s reach. Unless we’re arguing that the scaffold is nearing the top of the tree of knowledge, there’s always low-hanging fruit to be picked. Somebody will pick it, and whether or not they become a legendary figure depends on factors other than just how juicy their apple turned out to be. The reaching-for-fruit action is always equally effortful, but the act of scaffold-building gets more efficient every year. In literal terms, previous scientific discoveries and capital investments permit achievements that would have been inaccessible to earlier researchers, and we’re getting better at it all the time.
I don’t agree with this, for reasons discussed here. I think that empirically, it seems to get harder over time (at least per capita) to produce acclaimed works. I agree that there are other factors in who ends up “legendary,” but I think that’s one of them.
> Consider also that either this heuristic was either false at one point (i.e. it used to be the right decision to go into science to achieve “greatness,” but isn’t anymore), or else the heuristic is itself wrong (because so many obvious candidates for “great innovator” were all in academic science and working in established fields with fairly clear career tracks). If it used to be true that going into academic science was the right move to achieve scientific greatness, but isn’t anymore, then when and why did that stop being true? How do we know?
The heuristic is “to match the greats, don’t follow in their footsteps.” I think the most acclaimed scientists disproportionately followed this general heuristic—they disproportionately asked important/interesting questions that hadn’t gotten much attention, rather than working on the kinds of things that had well-established and -understood traditions and could easily impress their acquaintances. For much of the history of science, this was consistent with doing traditional academic science (which wasn’t yet particularly traditional); today, I think it is much less so.
As science progresses, it unlocks engineering possibilities combinatorially. This induces demand for and creates a supply of a healthier/more educated population with a larger number of researchers, many of whom are employed in building and managing our infrastructure rather than finding seminal ideas.
So what we’re witnessing isn’t scientific innovations becoming harder to find. Instead, scientific innovations produce so many engineering opportunities that they induce demand for an enormous number of engineers. The result is that an ever-decreasing fraction of the population is working in science, and science has to compete with an ever-larger and more lucrative engineering industry to attract the best and brightest.
In support of this, notice that the decline you find in scientific progress roughly begins in the early days of the industrial revolution (mid-late 1700s).
On top of that, I think we have to consider the tech-tree narrative of science history writing. Do you imagine that, even if you’d found that science today was becoming apparently more efficient relative to effective population, that scientific history writers would say “we’re going to have to cut out some of those Enlightenment figures to make room for all this amazing stuff going on in biotech!”?
It’s not that historians are biased in favor of the past, and give short shrift to the greatness of modern science and technology. It’s that their approach to historiography is one of tracing the development of ideas over time.
Page limits are page limits, and they’re not going to compress the past indefinitely in order to give adequate room for the present. They’re writing histories, after all. The end result, though, is that Murray’s sources will simply run out of room to cover modern science in the depth it deserves. This isn’t about “bad taste,” but about page limits and historiographical traditions.
These two forces explain both the numerator and the denominator in your charts of scientific efficiency.
This isn’t a story of bias, decline, or “peak science.” It’s a story of how ever-accelerating investment in engineering, along with histories written to educate about the history of ideas rather than to make a time-neutral quantification of eminence, combine to give a superficial impression of stagnation.
If anything, under this thesis, scientific progress and the academy is suffering precisely because of the perception you’re articulating here. The excitement and lucre associated with industry steers investment and talent away from investment in basic academic science. The faster this happens, the more stagnant the university looks as an ever-larger fraction of technical progress (including both engineering and science) happens outside the academy. And the world eats its seedcorn.