I would never trust an AI to make a scientific conclusion, but they're very good at some things:
- Plotting with natural language: "Create a scatter plot of column A versus column B, log scale Y and use stars sized by column C." Every plotting library (except maybe ggplot2 / plotnind) sucks, and the boilerplate never gets less tedius.
- Literature search, e.g. "Have there been any peer reviewed papers where they applied X method to Y domain"
- Complex visualization, e.g. "Make a self contained HTML file with a 3D interactive visualization of this graph. Add ball and spring position optimization and let me move nodes"
- Trying random stuff that would normally be too time consuming to be worth it, eg "Here is a dataset. Try regression methods A, B, and C and report a table." In this case, usually it will screw up and overfit, but it's a good smoke test.
Note how in all of these, it's being used for tedious things that provide some value, but ultimately they are only providing information to make a decision on.
Granted, I would like to have a research assistant I could train, but if your company will not create a position then there is not much you can do.
So: code + econ; researchers and organizations slated for overwhelm
Mostly quotes:
- 207K consumer user claude sessions (78K code, remainder chat+cowork) in Aug+Sep '26 classified per 7K SciNet taxonomy
- largest domains: computer science (11.9%), engineering (8.4%), and medicine (7.7%)
- higher ratio of usage/researcher: computer science, mathematics, statistics; social sciences
- "Usage is also high for the social sciences" ... "Relative usage is low in [...] the social sciences, with the exception of economics"
- Claude use and AI capability: "the top 20% of tasks also draw two to four times the expected use" "Health sciences researchers use Claude relatively little compared with the AI capability scores of their tasks"
- "Theoretical AI capability also predicts how much researchers allow Claude to work autonomously"
- "productivity gains tend to materialize only after organizations restructure around them (David 1990; Brynjolfsson, Rock, and Syverson 2021)"
- "A surge in new research papers could advance a field faster but also overwhelm scientists’ capacity to absorb or verify the results."
- "As AI becomes more capable and autonomous, AI systems could take the lead in verification, refereeing, and communicating important results, which would ease the absorption problem discussed above"
- "Fifth, more autonomous AI systems may increase the challenge of ensuring that AI-driven research remains aligned with human goals"
- "One effect may be a change in researchers’ job satisfaction."
Don't like this style of article where the "How" is "in what manner do they use it?" and not "what techniques do they use?". I would prefer to see specific lab setups, how they use and coordinate agents, what kind of protocol they have for asking questions and verifying information, and so on.
AI in science is a lot different than AI in progamming in some ways. It seems pretty harmless in programming a lot of the times because it's used to speed up rote tasks like writing boilerplate. But in science, if it does give scientists a boost in discovery, I think it's likely to lead to an even more cavalier attitude about the power that such discoveries can have, and thus lead to much more abuse of power by the wealthy and malicious actors.
> Using privacy-preserving methods, we study 207,000 Claude and Claude Code research sessions to understand how Claude is used across scientific fields and research tasks.
Did they get permission to use researchers' data or did they monitor and extract data without consent? Considering the kerfuffle OpenAI generated with their math proofs, you'd think Anthropic would take a hint and be clear that they did the research with consent, though that assumes they got consent.
Seriously, all the industry researchers at these companies went through IRB training during their PhD; have they just conveniently forgotten?
Using privacy-preserving methods, we study 207,000 Claude and Claude Code research sessions to understand how Claude is used across scientific fields and research tasks
Am I the only one who finds Claude overly assertive and confident for research? I tend to get more value out of other models (e.g. Gemini 4 Argon) even if they make mistakes, and then use Claude to revise and polish.
"less in the health and lab-based sciences"... Wow. Got to love how they report the intended effects of their biology/chemistry query censorship as if it was some neutral result, without any mention of its likely cause.
`In other news, we report that there seems to be significantly less cybersecurity research done on our platform than other areas of computer science` /s
AI for scientific discovery: How researchers use Claude
(anthropic.com)82 points by ersinesen 11 hours ago | 34 comments
Comments
I would never trust an AI to make a scientific conclusion, but they're very good at some things:
- Plotting with natural language: "Create a scatter plot of column A versus column B, log scale Y and use stars sized by column C." Every plotting library (except maybe ggplot2 / plotnind) sucks, and the boilerplate never gets less tedius.
- Literature search, e.g. "Have there been any peer reviewed papers where they applied X method to Y domain"
- Complex visualization, e.g. "Make a self contained HTML file with a 3D interactive visualization of this graph. Add ball and spring position optimization and let me move nodes"
- Trying random stuff that would normally be too time consuming to be worth it, eg "Here is a dataset. Try regression methods A, B, and C and report a table." In this case, usually it will screw up and overfit, but it's a good smoke test.
Note how in all of these, it's being used for tedious things that provide some value, but ultimately they are only providing information to make a decision on.
Granted, I would like to have a research assistant I could train, but if your company will not create a position then there is not much you can do.
Mostly quotes:
- 207K consumer user claude sessions (78K code, remainder chat+cowork) in Aug+Sep '26 classified per 7K SciNet taxonomy
- largest domains: computer science (11.9%), engineering (8.4%), and medicine (7.7%)
- higher ratio of usage/researcher: computer science, mathematics, statistics; social sciences
- "Usage is also high for the social sciences" ... "Relative usage is low in [...] the social sciences, with the exception of economics"
- Claude use and AI capability: "the top 20% of tasks also draw two to four times the expected use" "Health sciences researchers use Claude relatively little compared with the AI capability scores of their tasks"
- "Theoretical AI capability also predicts how much researchers allow Claude to work autonomously"
- "productivity gains tend to materialize only after organizations restructure around them (David 1990; Brynjolfsson, Rock, and Syverson 2021)"
- "A surge in new research papers could advance a field faster but also overwhelm scientists’ capacity to absorb or verify the results."
- "As AI becomes more capable and autonomous, AI systems could take the lead in verification, refereeing, and communicating important results, which would ease the absorption problem discussed above"
- "Fifth, more autonomous AI systems may increase the challenge of ensuring that AI-driven research remains aligned with human goals"
- "One effect may be a change in researchers’ job satisfaction."
As a hobby I run https://smalldocs.org / https://github.com/espressoplease/smalldocs an agent agnositc artifact layer, so I'm looking for feedback on artifact use in general.
Here are some sample scientific SmallDoc artifacts:
Palmer penguins: body mass, flipper length and species - https://smalldocs.org/s/YrJDCfCD8-6j_uRE0pNCbI#k=odJRxWOIySV...
AlphaFold 3: capabilities, evidence and operational limits - https://smalldocs.org/s/rRRuByQhmhZNBH_4RNCx1t#k=S0Jhyf72Q6M...
Did they get permission to use researchers' data or did they monitor and extract data without consent? Considering the kerfuffle OpenAI generated with their math proofs, you'd think Anthropic would take a hint and be clear that they did the research with consent, though that assumes they got consent.
Seriously, all the industry researchers at these companies went through IRB training during their PhD; have they just conveniently forgotten?
`In other news, we report that there seems to be significantly less cybersecurity research done on our platform than other areas of computer science` /s