New essay from @patrickc and myself, arguing that science has suffered from greatly diminishing returns over the past century:https://www.theatlantic.com/science/archive/2018/11/diminishing-returns-science/575665/ …
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What's being plotted: the probability a discovery made in that decade is ranked above discoveries made in other decades.
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The kicker is: the amount we're investing in science has gone up enormously (think 10-100x) over the same time period, whether you look at $, number of scientists, or number of publicationspic.twitter.com/9gBu2FREw0
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We're in an age of diminishing returns to scientific efforthttps://www.theatlantic.com/science/archive/2018/11/diminishing-returns-science/575665/ …
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Lots of disclaimers: this is just one metric, there's plenty of shortcomings of the metric. We're very aware of that and discuss this in the essay.https://www.theatlantic.com/science/archive/2018/11/diminishing-returns-science/575665/ …
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Nonetheless, the conclusion should be taken seriously, not dismissed lightly. This is in some sense a collective judgement from scientists themselves: science is getting vastly more expensive, and far from accelerating, progress is at best constant (by this metric).
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There's lots of corroborating evidence: e.g., the rise in ages at which scientists make key discoveries. Here are the average ages of discovery for early versus recent Nobel prizewinning discoveries. (Jones and Weinberg: http://www.pnas.org/content/108/47/18910 … )pic.twitter.com/vCsj7UNjhU
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The rise in size of scientific research teams also suggests it’s getting harder to make discoveries. (Fortunato et al: http://barabasi.com/f/939.pdf )pic.twitter.com/MPtSlh36IL
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There's also the massive decline in the growth of economic productivity since the 1950s, as documented by people such as Robert Gordon https://www.amazon.com/Rise-Fall-American-Growth-Princeton-ebook/dp/B071W7JCKW/ref=sr_1_1?ie=UTF8&qid=1542218574&sr=8-1&keywords=robert+gordon+rise+and+fall+of+american+growth … and
@tylercowen https://www.amazon.com/Great-Stagnation-Low-Hanging-Eventually-eSpecial-ebook/dp/B004H0M8QS/ref=sr_1_7?ie=UTF8&qid=1542218607&sr=8-7&keywords=tyler+cowen …pic.twitter.com/1ECYsSIQwv
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In a similar vein, there’s the recent work by Bloom, Jones, Van Reenen, and Webb, suggesting that ideas are getting harder to find: https://web.stanford.edu/~chadj/IdeaPF.pdf …pic.twitter.com/cbrao49xf0
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This all suggests it's getting much, much harder to make progress.
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One response is to say "Well, it's inevitable that things get harder", and to shrug and continue on your way. But if something is requiring ~100 times the investment as formerly, it's a good idea to seriously consider whether it's possible to do better!
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As far as we know there's no serious, large-scale, organized institutional response to the challenge of diminishing returns in science. And given that science is a principal driver of our civilization's progress, a high-order bit for humanity, that's a problem.
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So, what to do? That's a subject for another essay (or multiple lifetimes of building). But I can't resist a few thoughts.
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One huge success of science is how good it is at displacing ideas. If an individual or group has a new, genuinely better idea about the world, it can rapidly grow and displace old ideas. Evolution! General relativity! Etc.
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It's mirrored in the business world: one person can start a business, and with skill and luck that business may grow to outcompete billion-dollar incumbents.
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But suppose an individual starts a grant agency or university in their proverbial garage. They simply can’t grow it to outcompete incumbents ("We're replacing the NIH!" “We’re replacing Harvard!”), even if their approach is vastly better.
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That is: there is no strong growth model or notion of competitive displacement for scientific institutions. And this means stasis and homogeneity and monoculture, a lack of organizational change and learning. This is terrible for science.
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Indeed, it creates a sense that science _must_ be done this way. We must have PIs, a group is composed in such-and-such a way, scientists have a particular career path, are of a particular age, have a certain type of mentoring, produce a certain kind of output, etc.
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But we could change each (or every!) one of these in radical ways.
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Furthermore, it produces apathy. Every scientist has ideas for how to do things differently at the institutional level. But without a growth model for the best ideas, it's easy to feel it's not worth it, that things are forever stuck.
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If you start a better grant agency, it's not going to displace the NIH. But perhaps it should.
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A few ideas I like (no implied endorsement by Patrick, or originality on my part). Very telegraphic & incomplete - lots of nuance missing, and obvious problems that need to be addressed.
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Figure out how new fields are produced. At the moment there's a _lot_ of inhibitory forces that slow the rate of production of new fields. Can we programmatically 2x or 10x or 100x the rate of new field production?
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Far more varied funding strategies: eg by golden ticket (where 1 reviewer can ok a project, https://www.nature.com/articles/d41586-018-02743-2 … ); by variance in reviewer scores, using high variance (loved by some, hated by others) as a positive signal; or randomized allocationhttps://mbio.asm.org/content/7/2/e00422-16 …
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Tenure insurance. For a relatively small additional piece of the benefits package, tenure-track faculty are guaranteed a large payout should they fail to get tenure. It's a cheap way to de-risk the tenure process, and to encourage more risk-taking.
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Almost every funder talks about supporting high-risk research. But that is often just talk. A genuinely high-risk program would evaluate failure rates for past grants, and if the failure rate was _too low_ (below 60%, say), the program officer's job would be on the line.
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Finally, technology: What’s going to be the impact of AI on science? Of intelligence augmentation? Of ideas like open science? Might one or more of these dramatically speed up scientific progress?
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Of course, these are just a few ideas. I believe humanity has barely begun to explore the space of possible approaches to doing science. What are the high-order bits in how we do science? What new approaches can we take to discovery?
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We’re both very, very optimistic that we can do vastly better than today. But it needs new ideas, lots of experiments, and lots of imagination!
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End of conversation
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