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Three proposed priorities for science in the age of AI

A post recommends tackling problems that are fast and easy to verify, removing verification bottlenecks, and gathering data for problems that are hard to check.

Kosta DerpanisKD
Jason CrawfordJC
10 Sources, 20d ago, first seen 20d ago

TLDR

A post argues that problems that are fast and easy to verify represent a small subset of scientific problems but will be most affected by AI. Alongside tackling those, it recommends making verification easier through faster small-molecule synthesis, new assays, new biomarkers, and accelerated clinical trials. For problems that cannot be verified easily, it recommends gathering data. The author adds that many other kinds of work remain important and valuable, but predicts they will benefit less from AI.

Combined views

2K

10 Sources, first seen 20d ago

6 likes2 comments17 reposts

Combined views

2K

10 Sources, first seen 20d ago

6 likes2 comments17 reposts

Sentiment

Positive42.4%57.6%Negative

Summary

Positive replies welcomed AI speeding up scientific work like drug discovery while keeping human oversight central, while negative replies dismissed AI claims as nonexistent hype or feared job loss and data theft.

Based on 178 sentiment-bearing replies from 155 accounts across 4 conversations.

Featured Source

Sentiment

Positive42.4%57.6%Negative

Summary

Positive replies welcomed AI speeding up scientific work like drug discovery while keeping human oversight central, while negative replies dismissed AI claims as nonexistent hype or feared job loss and data theft.

Based on 178 sentiment-bearing replies from 155 accounts across 4 conversations.

10 Sources

Sam Rodriques@SGRodriquesIf you are wondering how AI will change science and what it makes sense to do right now, there are essentially three things: 1. You can work on solving the problems that are fast and easy to verify. This is a small subset of all problems, but these are the problems that will be most impacted by AI. The Millennium Problems we published are an example. 2. You can work on solving the problems that make other problems hard to verify. For example, one of the slow parts for solving many problems is small molecule synthesis. Make small molecule synthesis fast, and we will solve many more problems. Other things that fall into this category include creating new assays, finding new biomarkers, and accelerating clinical trials. 3. You can go and gather data for the really hard problems (i.e., the ones that are impossible to verify easily). In the age of AI, data is king. There are many other extremely important and valuable things to be done as well. But they will not benefit from AI nearly to the same extent.20d
Jason Crawford@jasoncrawfordRT @SGRodriques: If you are wondering how AI will change science and what it makes sense to do right now, there are essentially three thing…19d
Gael Varoquaux 🦋@GaelVaroquauxRT @simonmaechling: I’m a scientist. I need to say this because the AI hype is getting ridiculous. AI can design a molecule in seconds. Th…17d
Stephan Hoyer@shoyerThis post isn't wrong, but why do people keep on posting slop on Twitter? Especially when complaining about AI! Half the point of the short-form medium it should lower the effort to post content. (The other half is that it lowers the effort to read, too!)17d
nature@NatureArtificial-intelligence systems can generate hypotheses, design experiments and analyse data — but humans still need to decide what makes sense https://go.nature.com/4rPJHYl16d
Irina Rish@irinarishRT @Nature: Artificial-intelligence systems can generate hypotheses, design experiments and analyse data — but humans still need to decide…16d
shyamal@shyamalanadkatRT @xennygrimmato_: Science is bottlenecked by the latency of physical verification. Unlocking high-velocity breakthroughs demands dedicate…15d
Andrew White 🐦‍⬛@andrewwhite01Millennium problems for bio #4 lasted 9 days? I think activity is too low, but incredible specificity. Way to go! https://www.biorxiv.org/content/10.64898/2026.09.04.749267v1.full.pdf14d
Kosta Derpanis@CSProfKGD@liuzhuang1234 Shhh, don’t say it too loudly. The AIs are listening and might solve it 🤓13d
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    10 Sources

    Sam Rodriques@SGRodriquesIf you are wondering how AI will change science and what it makes sense to do right now, there are essentially three things: 1. You can work on solving the problems that are fast and easy to verify. This is a small subset of all problems, but these are the problems that will be most impacted by AI. The Millennium Problems we published are an example. 2. You can work on solving the problems that make other problems hard to verify. For example, one of the slow parts for solving many problems is small molecule synthesis. Make small molecule synthesis fast, and we will solve many more problems. Other things that fall into this category include creating new assays, finding new biomarkers, and accelerating clinical trials. 3. You can go and gather data for the really hard problems (i.e., the ones that are impossible to verify easily). In the age of AI, data is king. There are many other extremely important and valuable things to be done as well. But they will not benefit from AI nearly to the same extent.20d
    Jason Crawford@jasoncrawfordRT @SGRodriques: If you are wondering how AI will change science and what it makes sense to do right now, there are essentially three thing…19d
    Gael Varoquaux 🦋@GaelVaroquauxRT @simonmaechling: I’m a scientist. I need to say this because the AI hype is getting ridiculous. AI can design a molecule in seconds. Th…17d
    Stephan Hoyer@shoyerThis post isn't wrong, but why do people keep on posting slop on Twitter? Especially when complaining about AI! Half the point of the short-form medium it should lower the effort to post content. (The other half is that it lowers the effort to read, too!)17d
    nature@NatureArtificial-intelligence systems can generate hypotheses, design experiments and analyse data — but humans still need to decide what makes sense https://go.nature.com/4rPJHYl16d
    Irina Rish@irinarishRT @Nature: Artificial-intelligence systems can generate hypotheses, design experiments and analyse data — but humans still need to decide…16d
    shyamal@shyamalanadkatRT @xennygrimmato_: Science is bottlenecked by the latency of physical verification. Unlocking high-velocity breakthroughs demands dedicate…15d
    Andrew White 🐦‍⬛@andrewwhite01Millennium problems for bio #4 lasted 9 days? I think activity is too low, but incredible specificity. Way to go! https://www.biorxiv.org/content/10.64898/2026.09.04.749267v1.full.pdf14d
    Kosta Derpanis@CSProfKGD@liuzhuang1234 Shhh, don’t say it too loudly. The AIs are listening and might solve it 🤓13d
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