AI Boosts Research Careers but Flattens Scientific Discovery
My analysis of over 40 million papers reveals that while AI tools help scientists publish more and climb the career ladder faster, they are simultaneously narrowing the scope of scientific inquiry. Instead of exploring diverse frontiers, researchers are clustering around the same data-rich problems, creating a paradox where individual success drives collective conformity and reduces the originality of scientific discovery.
We are digging the same hole deeper and deeper.
- dahart
> Scientists who adopt AI gain productivity and visibility: On average, they publish three times as many papers, receive nearly five times as many citations, and become team leaders a year or two earlier than those who do not.
To me this effect doesn’t seem to reflect on AI very much, it seems to reflect on humans. Like maybe this is more evidence of the Babble Hypothesis and the incentives in research than AI, no?
- skeledrew
As with other fields touched, AI is merely amplifying what was already there. The aim of many scientists isn't discovery in and of itself. Discovery is a side effect of their primary drive to publish and - hopefully - become well known. And establishments only make things worse, because it's the things that are most likely to produce tangible results (the papers, or economically valuable products) that get the most funding.
- Labo333
> “It’s not about the architecture per se,” Evans says. “It’s about the incentives.”
It would have been useful to check whether less original work was already getting more citations before AI adoption. That could reflect broader trends and network effects: heavily cited research areas attract more authors optimizing for citations, so high-productivity researchers end up clustering on the same topics.
- aborsy
A new breed of academics has appeared whose jobs is to put their names in every paper possible. Literally, their job is to work on frameworks to buy co-authorship.
They do this in various ways, like establishing paper pipelines, collecting rents on labs and committees, focusing on money layer, using their profiles and citation count to help with acceptance of papers of other people , etc. You talk to them and they can’t explain their papers beyond a superficial introduction.
They collect huge citations, travel and give talk on the winner horses, collect credit, which feeds back into this fraudulent scheme. A scientist used to be a scientist not long ago, not a credit collector.
I wonder if Google could invent a new metric to expose them (weak ratio of first authorship, etc).
- overgard
I think we're finding measures of "productivity" in almost all fields are pretty bad and AI is a great way to game them. PR's, papers, etc. We have to stop looking at volume-of-stuff as a useful metric.
- radarsat1
"boost research careers".. seems like a pretty drastic conclusion to draw based on a technology that has existed for like 3 years and only lately is any good..
- dickersnoodle
This isn't a real surprise to anyone who knows how "AI" works.
- Nevermark
Any flattening of discovery due to AI, but will be temporary.
We tend to think that obvious potential is the same as realized potential, for new technology.
For any specific context, there are generally innumerable smaller adaptations and capability thresholds that have to be crossed. And the price for that journey is often temporary loss off overt productivity.