This Nature Portfolio perspective argues that self-driving labs are moving from isolated autonomous experiments toward multi-agent AI systems that manage full research campaigns, including experiment selection, lab coordination, resource constraints, and collaboration among specialized agents.
This Nature Portfolio perspective argues that self-driving labs are moving from isolated autonomous experiments toward multi-agent AI systems that manage full research campaigns, including experiment selection, lab coordination, resource constraints, and collaboration among specialized agents.
The broader significance is that AI impact on science is not only faster discovery; it may reshape how laboratories allocate attention, define evidence, coordinate resources, protect IP/privacy/security, and produce “epistemic” outcomes.
Read the evidence behind this analysis. External links open in a new tab.
Nature
A review of evidence across cognitive science, education, medicine, and human-factors research finds that fully offloading mental work to AI can weaken the acquisition and retention of the specific skills people stop practicing. The authors distinguish that evidence from broader claims about declining intelligence: effects on foundational abilities such as attention and working memory remain uncertain, while AI used as a collaborator, tutor, or source of feedback can preserve or improve learning.
In a randomized field experiment across a chain of middle and high schools in Turkey, giving teachers a generative-AI support tool reduced students’ intrinsic motivation by 0.11 standard deviations. Average academic performance did not change, but students taught by lower-performing teachers experienced significant declines in both performance and confidence, showing that a tool that makes lesson preparation easier for teachers does not automatically improve the student experience.
The European Commission has issued operational guidance for Article 50 of the AI Act before its transparency obligations begin applying on August 2, 2026. Providers must disclose when people are interacting with systems such as chatbots, agents, or avatars and make generative outputs detectable through machine-readable marking; deployers must disclose emotion-recognition or biometric-categorization uses and clearly label deepfakes and certain AI-generated public-interest text when it lacks human review or editorial control.