Patrick Collison: uncertainty

Transcript context

…I strongly agree that sort of there’s a lot of important work already happening across multiple disciplines that is relevant to these questions. Like the idea of there being “a new science of progress” — that was the headline placed on the article but not exactly what we’re saying. What we’re arguing is that the work that’s already happening should be receiving more attention and there should be much more of us. And just to give a couple of quick examples: there’s strongly suggested evidence that we can teach management practices so people can run firms more effectively, right? So there’s a couple of studies on this. There’s a good one from some folks at Stanford that did a randomized trial in India. And there’s a really neat one that came out last year from Michela Giorcelli looking at firms in Italy and showing that over 15 years after a management training program with some natural randomization, that those firms were employing more people, paying more wages, being more successful. And another randomized trial in Mexico conducted over the past couple years, again, 600 firms, ensuring that just teaching better management practices actually makes those companies much better off. If that’s true, that’s amazing low-hanging fruit, right? We should be investing much more in this area. We should be figuring out which kinds of management training work better or worse than others, is this generalized to all countries, how can we actually implement and execute this in the world more broadly? So that’s one. Second is, Tyler mentioned this point about geographic mobility, right? When you think about how do we grow GDP or how do we generate progress maybe housing policy’s not the first thing we’re naturally drawn to thinking about. However, if you look at the USA in 1980, 40% of people moved somewhere else when they took a new job. So those things went together much more. If you look last year, about one in ten people moved when they took a new job, right? So within the U.S., geographic mobility really declined. That is in large part because the costs of movement have enormously increased as housing costs have increased especially in our most productive regions over the past couple decades. Now if you look into that sort of more closely, there are economists who’ve been studying these questions quite closely for the past couple of years. These two guys Hsieh and Moretti published an updated version of a previous paper this summer putting forward a model showing that if you look at the zoning restrictions that existed in the Bay Area and New York between 1964 and 2009, and you imagine a counter-factual world where there was much more supply elasticity in these places and we built way more homes here in the Bay Area and in New York. In that counter-factual world, average U.S. income would be, in their model, $3,700 higher per person . Again, not just for people in those places, but across the country, right? That’s a huge effect size. at counter-factual world, average U.S. income would be, in their model, $3,700 higher per person . Again, not just for people in those places, but across the country, right? That’s a huge effect size. And so again, we should be studying these questions much more closely and we should be figuring out, okay, well, if that’s true, what are the policy prescriptions? How do we actually go act upon that? It’s amazing low-hanging fruit. And then to give a third one, as those two examples show, funding science is incredibly important. But there’s surprisingly little work about how we should be funding science and how could we do that most effectively? And actually, beneath the surface, it’s been changing a tremendous amount here in the U.S. over the past couple of decades, and whether that’s a good thing is an important policy question. So for example, in 1980 the NIH spent 12x more dollars on researchers under 40 than researchers over 50. So they predominately funded younger people. Today they spend 5x more dollars on people over 50 than under 40. And so it’s really inverted — it’s kind of gone from primarily funding these young investigators to this gerontocracy where they’re funding older scientists. Maybe that’s good, maybe that’s bad, I don’t know — but that seems like a very important question to answer. And so part of our point in arguing for progress studies is when you really look at kind of the expansive version of all the different things that can sort of, you know, influence our ability to discover new useful knowledge to generate economic growth, the set of questions is super-broad, and we should be trying to kind of synthesize this effectively. Yeah. So let’s go deep on medical research here for a second, because this is an area that you wrote this paper about before about how the progress in the field might be slowing. And like you mentioned, The Chan Zuckerberg Initiative, the philanthropy that I run with my wife, a big focus of it is on medical research and trying to — we have this aspirational goal that we wanna help build tools that can help scientists cure, prevent, or manage all diseases by the end of this century. And basically, the math of how you get there is, starting about 100 years ago there was really this uptick in medical research where we started doing randomized control experiments, treating it more like an experimental science. Since around that time, the average life expectancy has increased by a quarter of a year every year, relatively linearly. There’s no guarantee, of course, that that continues, but if we’re able to have that continue, then that would imply that by the end of the century we will generally have had to have either cured, prevented, or been able to manage most if not all of the diseases that we’re aware of now. So there’s some trend that suggests that this should be reasonable, and the approach that we’re taking in the work at CZI is largely about building tools to help compound the rate of science. And what we see is that, like you mentioned, the government is the largest and most important funder of science and it basically funds the whole establishment of scientists across the country. But the grants tend to be very spread out across a lot of people. They’re not typically put into big infrastructure projects. And that’s the niche that we felt through CZI that we can help to fill: instead of investing a million dollars in a lab, put $100 million or a couple hundred million dollars over time into building up really important scientific assets for the community. Like helping to fund scientists to go put together this Human Cell Atlas. Think about it as like the periodic table of elements but for biology — all the different kinds of cells in the human body. And the goal is just, if you look throughout the history of science, at least, most major scientific breakthroughs have been preceded by the invention of new tools that help people look at things in different ways. And so the theory is similar to what you’re going at of how you increase the compounding rate of progress. There are a couple of different directions that I think we could go in here. One is that I’m curious what you’ve seen in your studies in the space that suggest to you that the rate of progress is actually slowing. And I’m also curious about the examples you’ve seen overall of how the science around studying progress would potentially lead to a different approach or a different portfolio of how this kind of work gets done. So I don’t know where you want to start with that, but there’s a lot here to do.…

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