New ‘AI scientists’ are improving – but reveal their fundamental limits
New ‘AI scientists’ are improving – but reveal their fundamental limits
Publish Date: 2026-05-20 02:26:00
Source Domain: theconversation.com
Many of the most exciting discoveries in science involve highly specialised knowledge and making connections between far-flung facts. Scientists must combine deep analysis with broad reasoning strategies.
As in many information-rich tasks, researchers are looking to artificial intelligence (AI) systems to speed up their work. AI tools may be able to support key steps such as generating ideas, reviewing existing work and analysing data.
The latest systems use large language models (LLMs) to allow scientists to interact naturally and directly with the vast body of knowledge captured in words in the scientific literature.
But as two new systems described in papers just published in Nature show, when it comes to science, language alone can only go so far.
What AI is doing to science
A number of organisations, such as Sakana AI, are trying to automate the entire scientific process. To date, these efforts have largely focused on computer science, where “experiments” mainly involved designing and writing code.
However, the Agents4Science conference organised at Stanford last October showcased a broader range of AI-generated papers. They covered topics from mechanical engineering and protein design to a system called BadScientist which deliberately produced “convincing but unsound” research.
I have previously raised concerns about the impacts of AI scientists on the scientific ecosystem. Recent work validates these concerns, showing increased quantity but lower quality of both papers and peer reviews, identifying fabricated references in published works, finding fabricated and misleading images, and more.
What scientists are doing with AI
AI systems clearly can’t be trusted to conduct the full process of science on their own. But how about using AI to help scientists get more done more quickly?
This is the intent of the two new systems described in Nature: Robin, made by non-profit Future House, and Co-Scientist, from Google DeepMind.
Both…
