STEM academia serves two closely intertwined purposes: the production of high quality science and the production of human capital. These two purposes feed into each other. The obvious direction is that we develop human capital by paying people to produce science.
What is perhaps less obvious is that the very fact that human labor is used to produce science has historically been an important input to its quality. The goal of science is not simply to produce papers, but rather to produce good work--that a person is willing to spend months working on a paper is a (weak) witness to the fact that it has some minimum quality. If someone has a record of producing high quality work, that they wrote a paper is a stronger witness, since it was worth the opportunity cost to write it. If many people engage with it substantially, that is even stronger evidence. This is not to say that there isn't lots of low-quality work--there is, in fact a huge amount--but we have strong sorting mechanisms, admittedly using imperfect proxies (all depending on costly human labor!), to find high-quality stuff. Arguably the paper itself is not the primary product here; in many cases the primary product is actually the expertise developed over the course of producing it, which can then be applied to other questions.
If you believe, as I do, that producing high quality science should be one of our fundamental goals, I think you’re obligated to embrace new tools that help one do so. Refusing to is a declaration that these outputs are not important. But I worry that we are not on track to automate the production of good work; rather, we are on track to automate the production of papers. We need new mechanisms to ensure that we are also producing good work, and to ensure that we are developing the human capital to engage with it.
@littmath this def seems like the skill set that will lead to the early wins for AI math, from Bloom: "combining superhuman levels of patience with familiarity with a vast array of technical machinery."
Interesting blog post by @wtgowers on (training to do) mathematics and AI. His conclusions hold equally well for computational biology. https://t.co/0d6qfZPK7i
Open constructive post-preprint community wide review is the only way forward. Anonymity can still be implemented but reviews need to be in the open so others in the community can push back on abuse of anonymity or personal attacks on authors.
enjoy that sunset while you can—soon a swarm of superintelligent AI agents will be able to appreciate it more rapidly and efficiently than you ever could
I continue to be happy with my decision two months ago to cancel my ChatGPT account.
There's no indication OpenAI is being run carefully, or with any moral compass. It seems irresponsible to support them.
I'm participating in the economic blackout today; I hope you will too. We have a poorly trained paramilitary group being sent by the federal government to intimidate perceived political opponents, and they are killing citizens with impunity.
This is what tyranny looks like.
🚨BREAKING: I have filed a lawsuit against Cornell University in federal district court in New York for their secret and illegal plot for an evolutionary biologist "diversity hire" that explicitly excluded qualified white candidates like me.
https://t.co/RsG4HbRDEq
Every month brings a new "with large enough n's you don't need randomization" guy. A few more months and we will surely be able to determine what causes them.
New #mimulus preprint! We found grandparental environments exhibit strong effects on the fitness of their grand-offspring and whether this was positive or negative depended on the historical environment, showing TGP is locally adaptive
I really need a data analyst job based in SF. I know SQL well + some Python. I’ve done a variety of types of data analytics over the course of my career but my primary experience is in RevOps/BI. If you can’t hire me, could you please RT for visibility?
https://t.co/8FMqC5kJ5K
We're pleased to share the final version of our paper, 'Confounding fuels misinterpretation in human genetics'
(w/ Jed Carlson, Olivia Smith, Ruth Shaw, and Arbel Harpak) 🧵👇
Study of the genetics underlying human behavior and social outcomes, with its fraught history and potential for misappropriation, requires rigorous science. The failure to fully reckon with confounding fuels misinterpretation of genetics research and impedes scientific progress.