I thought you gave superb explanations for the intuitions underlying both the burden-of-knowledge thesis and the institutional decay thesis. But then you sort of just assert that the institutional decay thesis seems more plausible to you, even though it seemed from your own presentation like very strong arguments can be mustered on both sides with neither having a knock-down! Can you suggest some experiment or observational result that could clinch the matter one way or the other?
Someone (I thought Scott Alexander but I can't find it in his archives) proposed a model where researchers are foraging for ideas on a landscape, and as more and more ideas get discovered, you have to travel farther to find new ones. I think they originally thought of "traveling farther" as the burden of knowledge problem, but it doesn't have to be - you can think of it as just "you have to think for a really long time to come up with something genuinely new" or something like that.
If that's the case, you'd still have the ideas-getting-harder-to-find problem without any of the burden-of-knowledge indicators you mentioned, and without institutional decay playing a big role.
If you have not done so, I would recommend reading "Range" by Daniel Epstein. He makes some interesting observations as to how generalists can make real contributions in a world dominated by specialists. I think he conclusions are very applicable to Progress Studies.
I think much the same problems are going on in social science and history. I believe new fields of inquiry that build upon the findings of multiple disciplines are necessary. This enables us to see "old data" in new ways by making hither to unnoticed connections.
Given the current state of academia, however, this is unlikely to happen in universities. We need to find ways to do so via digital technologies.
I believe that is exactly what Progress Studies should be trying to do. Here is a series of posts on how we can do that:
Here is one models on how the burden can still show up: https://www.strangeloopcanon.com/p/innovation . The question of how much you need to learn before making a breakthrough is dependent on how quickly and well you can learn, and that "node capacity" can manifest as a burden of knowledge
I'm extremely attracted to the idea that university science is the barrier to success. It sucks. But if so why haven't drug compabies smashed progress out of the park? They have none of the same intitutional problems. Sure, there's been progress via these companies, like glp-1. But not as much as you'd expect.
I have occasionally thought that organisations should be subject to random accidents, as humans are. And/or, they should have a fixed but indeterminate lifespan, as humans do, with the chance of death increasing yearly after forty years or so. Incentives in academia would be a little different, I think.
I thought you gave superb explanations for the intuitions underlying both the burden-of-knowledge thesis and the institutional decay thesis. But then you sort of just assert that the institutional decay thesis seems more plausible to you, even though it seemed from your own presentation like very strong arguments can be mustered on both sides with neither having a knock-down! Can you suggest some experiment or observational result that could clinch the matter one way or the other?
Someone (I thought Scott Alexander but I can't find it in his archives) proposed a model where researchers are foraging for ideas on a landscape, and as more and more ideas get discovered, you have to travel farther to find new ones. I think they originally thought of "traveling farther" as the burden of knowledge problem, but it doesn't have to be - you can think of it as just "you have to think for a really long time to come up with something genuinely new" or something like that.
If that's the case, you'd still have the ideas-getting-harder-to-find problem without any of the burden-of-knowledge indicators you mentioned, and without institutional decay playing a big role.
Excellent article.
If you have not done so, I would recommend reading "Range" by Daniel Epstein. He makes some interesting observations as to how generalists can make real contributions in a world dominated by specialists. I think he conclusions are very applicable to Progress Studies.
Here is a summary of the book:
https://techratchet.com/2020/03/13/book-summary-range-why-generalist-triumph-in-a-specialized-world-by-daniel-epstein/
I think much the same problems are going on in social science and history. I believe new fields of inquiry that build upon the findings of multiple disciplines are necessary. This enables us to see "old data" in new ways by making hither to unnoticed connections.
Given the current state of academia, however, this is unlikely to happen in universities. We need to find ways to do so via digital technologies.
I believe that is exactly what Progress Studies should be trying to do. Here is a series of posts on how we can do that:
https://frompovertytoprogress.substack.com/p/what-is-progress-studies
Here is one models on how the burden can still show up: https://www.strangeloopcanon.com/p/innovation . The question of how much you need to learn before making a breakthrough is dependent on how quickly and well you can learn, and that "node capacity" can manifest as a burden of knowledge
I'm extremely attracted to the idea that university science is the barrier to success. It sucks. But if so why haven't drug compabies smashed progress out of the park? They have none of the same intitutional problems. Sure, there's been progress via these companies, like glp-1. But not as much as you'd expect.
Thanks for the great content Maxwell! Found your blog through Malcolm Cochran (https://antheros.blog/). I wrote a post largely as a response to this one: https://nematobe.substack.com/p/science-friction-is-the-burden-of
I have occasionally thought that organisations should be subject to random accidents, as humans are. And/or, they should have a fixed but indeterminate lifespan, as humans do, with the chance of death increasing yearly after forty years or so. Incentives in academia would be a little different, I think.