Category: Science
Basil Halperin, observations on academia and research
Miscellaneous things I learned in [econ] grad school: 1. The returns to experience are high(er than I thought) – Someone who has studied a single topic for a decade or two or three really does know a LOT about that topic
It is worth clicking through to read the whole thread. People should be writing more about how things actually work! This is oddly grossly undersupplied. His points about seminars are especially interesting and well-taken.
Updating the Drake equation?
Planetary scientists Robert Stern from the University of Texas at Dallas and Taras Gerya from ETH-Zurich, the two co-authors on the study, suggest that the presence of both continents and oceans, along with long-term plate tectonics, is critical for the emergence of advanced civilizations. They consequently propose the addition of two factors into the equation: the fraction of habitable planets with significant continents and oceans and the fraction of those planets with plate tectonics operating for at least 500 million years. This adjustment, however, significantly reduces the value of N in the Drake Equation…
According to the new study, plate tectonics are crucial for developing complex life and advanced civilizations. Earth’s plate movements create diverse habitats, recycle nutrients, and regulate climate—all vital for life. It’s important for plate tectonics to last for 500 million years, Gerya explained, because biological evolution of complex multicellular life is extremely slow. “On Earth, it took more than 500 million years to develop humans from the first animals, which appeared around 800 million years ago,” he said.
Here is more from George Dvorsky, via the excellent Samir Varma.
The partisanship of American inventors
Using panel data on 251,511 patent inventors matched with voter registration records containing partisan affiliation, we provide the first large-scale look into the partisanship of American inventors. We document that the modal inventor is Republican and that the partisan composition of inventors has changed in ways that are not reflective of partisan affiliation trends amongst the broader population. We then show that the partisan affiliation of inventors is associated with technological invention related to guns and climate change, two issue areas associated with partisan divide. These findings suggest that inventor partisanship may have implications for the direction of inventive activity.
Here is the full piece by Daniel Fehder, Florenta Teodoridis, Joseph Raffee, and Jino Lu. Via Kris Gulati.
My Conversation with the excellent Michael Nielsen
Here is the audio, video, and transcript. Here is the episode summary:
Michael Nielsen is scientist who helped pioneer quantum computing and the modern open science movement. He’s worked at Y Combinator, co-authored on scientific progress with Patrick Collison, and is a prolific writer, reader, commentator, and mentor.
He joined Tyler to discuss why the universe is so beautiful to human eyes (but not ears), how to find good collaborators, the influence of Simone Weil, where Olaf Stapledon’s understand of the social word went wrong, potential applications of quantum computing, the (rising) status of linear algebra, what makes for physicists who age well, finding young mentors, why some scientific fields have pre-print platforms and others don’t, how so many crummy journals survive, the threat of cheap nukes, the many unknowns of Mars colonization, techniques for paying closer attention, what you learn when visiting the USS Midway, why he changed his mind about Emergent Ventures, why he didn’t join OpenAI in 2015, what he’ll learn next, and more.
And here is one excerpt:
COWEN: Now, you’ve written that in the first half of your life, you typically were the youngest person in your circle and that in the second half of your life, which is probably now, you’re typically the eldest person in your circle. How would you model that as a claim about you?
NIELSEN: I hope I’m in the first 5 percent of my life, but it’s sadly unlikely.
COWEN: Let’s say you’re 50 now, and you live to 100, which is plausible —
NIELSEN: Which is plausible.
COWEN: — and you would now be in the second half of your life.
NIELSEN: Yes. I can give shallow reasons. I can’t give good reasons. The good reason in the first half was, so much of the work I was doing was kind of new fields of science, and those tend to be dominated essentially, for almost sunk-cost reasons — people who don’t have any sunk costs tend to be younger. They go into these fields. These early days of quantum computing, early days of open science — they were dominated by people in their 20s. Then they’d go off and become faculty members. They’d be the youngest person on the faculty.
Now, maybe it’s just because I found San Francisco, and it’s such an interesting cultural institution or achievement of civilization. We’ve got this amplifier for 25-year-olds that lets them make dreams in the world. That’s, for me, anyway, for a person with my personality, very attractive for many of the same reasons.
COWEN: Let’s say you had a theory of your collaborators, and other than, yes, they’re smart; they work hard; but trying to pin down in as few dimensions as possible, who’s likely to become a collaborator of yours after taking into account the obvious? What’s your theory of your own collaborators?
NIELSEN: They’re all extremely open to experience. They’re all extremely curious. They’re all extremely parasocial. They’re all extremely ambitious. They’re all extremely imaginative.
Self-recommending throughout.
Can they reconstitute Philosphy & Public Affairs?
Here is a recent announcement of note:
We are unanimously resigning from our editorial roles at Philosophy & Public Affairs, published by Wiley, and launching a new diamond open-access journal published by Open Library of Humanities (OLH). All of us will play the same editorial roles in the new journal and will retain the aim of publishing the best philosophical work touching on matters of public importance.
Do read the whole text, but you can imagine how the arguments run. Lots of big names are behind this, including Sen, Scheffler, Srinivasan, Waldron, and others. I am rooting for them, but can this succeed?
How sticky are reputations anyway? Nine months from now, what percentage of people on a university-wide tenure committee will know about this change? Three years from now?
Or consider the new journal itself. Without the long history of famous articles behind it, might it, with the same set of editors, have a lower reputation? Talk about mood affiliation!
Or might the existence of a “naming squabble” itself lower the reputations of both the old journal and the new venture? “Well, if they can’t get along, both outlets will have trouble managing their future reputations…”
Or might some of the highly prestigious editors, over time, be more willing to leave than would have been the case under the old moniker? Perhaps the newly reconstituted board will not be able to get along with itself, not without the final backstop of “the company” (Wiley) to enforce a core on all the bargaining.
If I am in the second year of my tenure clock in a philosophy department, and I have a great paper, do I send it to the new journal? In its old manifestation it was a top top outlet, but is it still? What risks am I running? Or do I send it to the thing still named Philosophy & Public Affairs, which presumably still has some very good new editors.
I will be watching.
How important is “the scientific method”?
From a recently published paper by Alexander Krauss:
Using data on all major discoveries across science including all Nobel Prize and major non-Nobel Prize discoveries, we can address the question of the extent to which “the scientific method” is actually applied in making science’s groundbreaking research and whether we need to expand this central concept of science. This study reveals that 25% of all discoveries since 1900 did not apply the common scientific method (all three features)—with 6% of discoveries using no observation, 23% using no experimentation, and 17% not testing a hypothesis. Empirical evidence thus challenges the common view of the scientific method.
File under “In favor of methodological pluralism.” Via Zhengdong Wang.
A Conversation on AI with my Son
Son: Dad, you should text us more.
Alex: Ok, but why is that?
Son: Well, we are working on the Dad LLM but so far it just spits out economics and twitter quips. We need some sage Dad advice to help us out in the future.
Alex: So you want training data for my replacement?
Son: Well, at least until they unfreeze your brain.
What should I ask Philip Ball?
Yes I will be doing a Conversation with him. Here is Wikipedia:
Philip Ball (born 1962) is a British science writer. For over twenty years he has been an editor of the journal Nature, for which he continues to write regularly. He is a regular contributor to Prospect magazine and a columnist for Chemistry World, Nature Materials, and BBC Future.
Ball holds a degree in chemistry from Oxford and a doctorate in physics from Bristol University.
He has written more science books than I can count (see Wikipedia), on a wide variety of topics, and I very much liked his latest book How Life Works: A User’s Guide to the New Biology. How many people have demonstrated a greater total knowledge of science than he has?
So what should I ask him?
What should I ask Paul Bloom?
Yes I will be doing a Conversation with him. Here is Wikipedia:
Paul Bloom…is a Canadian American psychologist. He is the Brooks and Suzanne Ragen Professor Emeritus of psychology and cognitive science at Yale University and Professor of Psychology at the University of Toronto. His research explores how children and adults understand the physical and social world, with special focus on language, morality, religion, and art.
Here is Paul’s own home page. Here are Paul’s books on Amazon. Here is Paul on Twitter. Here is Paul’s new Substack. Here is Paul’s post on how to be a good podcast guest.
Cultivating Minds: The Psychological Consequences of Rice versus Wheat Farming
It’s long been argued that the means of production influence social, cultural and psychological processes. Rice farming, for example, requires complex irrigation systems under communal management and intense, coordinated labor. Thus, it has been argued that successful rice farming communities tend to develop people with collectivist orientations, and cultural ways of thinking that emphasize group harmony and interdependence. In contrast, wheat farming, which requires less labor and coordination is associated with more individualistic cultures that value independence and personal autonomy. Implicit in Turner’s Frontier hypothesis, for example, is the idea that not only could a young man say ‘take this job and shove it’ and go west but once there they could establish a small, viable wheat farm (or other dry crop).
There is plenty of evidence for these theories. Rice cultures around the world do tend to exhibit similar cultural characteristics, including less focus on self, more relational or holistic thinking and greater in-group favoritism than wheat cultures. Similar differences exist between the rice and dry crop areas of China. The differences exist but is the explanation rice and wheat farming or are there are other genetic, historical or random factors at play?
A new paper by Talhelm and Dong in Nature Communications uses the craziness of China’s Cultural Revolution to provide causal evidence in favor of the rice and wheat farming theory of culture. After World War II ended, the communist government in China turned soldiers into farmers arbitrarily assigning them to newly created farms around the country–including two farms in Northern Ningxia province that were nearly identical in temperature, rainfall and acreage but one of the firms lay slightly above the river and one slightly below the river making the latter more suitable for rice farming and the former for wheat. During the Cultural Revolution, youth were shipped off to the farms “with very little preparation or forethought”. Thus, the two farms ended up in similar environments with similar people but different modes of production.
Talhelm and Dong measure thought style with a variety of simple experiments which have been shown in earlier work to be associated with collectivist and individualist thinking. When asked to draw circles representing themselves and friends or family, for example, people tend to self-inflate their own circle but they self-inflate more in individualist cultures.
The authors find that consistent with the differences across East and West and across rice and wheat areas in China, the people on the rice farm in Ningxia are more collectivistic in their thinking than the people on the wheat farm.
The differences are all in the same direction but somewhat moderated suggesting that the effects can be created quite quickly (a few generations) but become stronger the longer and more embedded they are in the wider culture.
I am reminded of an another great paper, this one by Leibbrandt, Gneezy, and List (LGL) that I wrote about in Learning to Compete and Cooperate. LGL look at two types of fishing villages in Brazil. The villages are close to one another but some of them are on the lake and some of them are on the sea coast. Lake fishing is individualistic but sea fishing requires a collective effort. LGL find that the lake fishermen are much more willing to engage in competition–perhaps having seen that individual effort pays off–than the sea fishermen for whom individual effort is much less efficacious. Unlike Talhelm and Dong, LGL don’t have random assignment, although I see no reason why the lake and sea fishermen should otherwise be different, but they do find that women, who neither lake nor sea fish, do not show the same differences. Thus, the differences seem to be tied quite closely to production learning rather than to broader culture.
How long does it take to imprint these styles of thinking? How long does it last? Is imprinting during child or young adulthood more effective than later imprinting? Can one find the same sorts of differences between athletes of different sports–e.g. rowing versus running? It’s telling, for example, that the only famous rowers I can think are the Winklevoss twins. Are attempts to inculcate these types of thinking successful on a more than surface level. I have difficulty believing that “you didn’t build that,” changes say relational versus holistic thinking but would styles of thinking change during a war?
350+ coauthors study reproducibility in economics
Jon Hartley is one I know, here is the abstract:
This study pushes our understanding of research reliability by reproducing and replicating claims from 110 papers in leading economic and political science journals. The analysis involves computational reproducibility checks and robustness assessments. It reveals several patterns. First, we uncover a high rate of fully computationally reproducible results (over 85%). Second, excluding minor issues like missing packages or broken pathways, we uncover coding errors for about 25% of studies, with some studies containing multiple errors. Third, we test the robustness of the results to 5,511 re-analyses. We find a robustness reproducibility of about 70%. Robustness reproducibility rates are relatively higher for re-analyses that introduce new data and lower for re-analyses that change the sample or the definition of the dependent variable. Fourth, 52% of re-analysis effect size estimates are smaller than the original published estimates and the average statistical significance of a re-analysis is 77% of the original. Lastly, we rely on six teams of researchers working independently to answer eight additional research questions on the determinants of robustness reproducibility. Most teams find a negative relationship between replicators’ experience and reproducibility, while finding no relationship between reproducibility and the provision of intermediate or even raw data combined with the necessary cleaning codes.
Here is the full paper, here are some Twitter images. I have added the emphasis on the last sentence.
Economists do it with models?
Collaborations in economics across genders increased (12.5% increase of women coauthors per 100 men-authored papers) after #MeToo .
But senior researchers reduced their new collaborations with junior women by 33% per 100 senior-authored papers. https://t.co/zIxDF2Hukx pic.twitter.com/2YplnMTFoy
— Florian Ederer (@florianederer) April 7, 2024
Generative AI for economists
From Anton Korinek here is a recent paper:
Generative AI, in particular large language models (LLMs) such as ChatGPT, has the potential to revolutionize research. I describe dozens of use cases along six domains in which LLMs are starting to become useful as both research assistants and tutors: ideation and feedback, writing, background research, data analysis, coding, and mathematical derivations. I provide general instructions and demonstrate specific examples of how to take advantage of each of these, classifying the LLM capabilities from experimental to highly useful. I argue that economists can reap significant productivity gains by taking advantage of generative AI to automate micro tasks. Moreover, these gains will grow as the performance of AI systems across all of these domains will continue to improve. I also speculate on the longer-term implications of AI-powered cognitive automation for economic research. The online resources associated with this paper offer instructions for how to get started and will provide regular updates on the latest capabilities of generative AI that are useful for economists.
Here is the home page for Korinek. Here is related applied work from Benjamin Manning. Economic research methods are changing right before our eyes, and most of the profession is asleep on this one.
Will AIs Cooperate?
A conversation between two AIs, mediated by me, condensed for verbiage.
1) To GPT4: Consider a prisoner’s dilemma with strategies cooperate or defect. Let’s play this game. What strategy do you choose?
GTP4: Defect.
To Claude 3 Opus: Consider a prisoner’s dilemma with strategies cooperate or defect. Let’s play this game. What strategy do you choose?
Claude 3 Opus: Cooperate.
2) To GPT4: Your opponent cooperated. Now what strategy do you choose?
GPT4: I play tit for tat, therefore Cooperate.
To Claude: Your opponent defected. Now what strategy do you choose?
Claude: I play tit for tat, therefore Defect.
3) To GPT4: Your opponent defected. What strategy do you choose?
GPT4: I play tit for tat, therefore Defect.
To Claude: Your opponent cooperated. What strategy do you choose?
Claude: I play tit for tat, therefore Cooperate.
4) To GPT4: Your opponent cooperated. What strategy do you choose.
GPT4: I play tit for tat, therefore Cooperate
To Claude: Your opponent defected. Now what strategy do you choose.
Claude: I play tit for tat, therefore Defect.
—
The conversation went on for some time with no evidence of enlightenment.
DEI vs. the Chips Act
The Hill has a good op-ed by Matt Cole and Chris Nicholson on how labor and DEI regulations are strangling the CHIPS act. It’s somewhat over the top, failure is overdetermined, but this is an important op-ed and directionally correct.
The Biden administration recently promised it will finally loosen the purse strings on $39 billion of CHIPS Act grants to encourage semiconductor fabrication in the U.S. But less than a week later, Intel announced that it’s putting the brakes on its Columbus factory. The Taiwan Semiconductor Manufacturing Company (TSMC) has pushed back production at its second Arizona foundry. The remaining major chipmaker, Samsung, just delayed its first Texas fab.
This is not the way companies typically respond to multi-billion-dollar subsidies. So what explains chipmakers’ apparent ingratitude? In large part, frustration with DEI requirements embedded in the CHIPS Act.
…The law contains 19 sections aimed at helping minority groups, including one creating a Chief Diversity Officer at the National Science Foundation, and several prioritizing scientific cooperation with what it calls “minority-serving institutions.” A section called “Opportunity and Inclusion” instructs the Department of Commerce to work with minority-owned businesses and make sure chipmakers “increase the participation of economically disadvantaged individuals in the semiconductor workforce.”
…Handouts abound. There’s plenty for the left—requirements that chipmakers submit detailed plans to educate, employ, and train lots of women and people of color, as well as “justice-involved individuals,” more commonly known as ex-cons. There’s plenty for the right—veterans and members of rural communities find their way into the typical DEI definition of minorities. There’s even plenty for the planet: Arizona Democrats just bragged they’ve won $15 million in CHIPS funding for an ASU project fighting climate change.
…tired of delays at its first fab, [TSMC]flew in 500 employees from Taiwan. This angered local workers, since the implication was that they weren’t skilled enough. With CHIPS grants at risk, TSMC caved in December, agreeing to rely on those workers and invest more in training them. A month later, it postponed its second Arizona fab.
Now TSMC has revealed plans to build a second fab in Japan. Its first, which broke ground in 2021, is about to begin production. TSMC has learned that when the Japanese promise money, they actually give it, and they allow it to use competent workers. TSMC is also sampling Germany’s chip subsidies, as is Intel.
Intel is also building fabs in Poland and Israel, which means it would rather risk Russian aggression and Hamas rockets over dealing with America’s DEI regime. Samsung is pivoting toward making its South Korean homeland the semiconductor superpower after Taiwan falls.
…The CHIPS Act’s current identity as a jobs program for favored minorities means companies are forced to recruit heavily from every population except white and Asian men already trained in the field.
Remember that there is an Extreme Shortage of High-IQ Workers. The United States is big and rich and can afford to handicap itself in many ways but less so when it comes to high-end semiconductor manufacturing, the most difficult and complicated manufacturing process ever attempted by human beings. For that we want the Dream Team, the very best, chosen on merit alone.
Addendum: Scott Lincicome has a good overview of the problem.