Progression without progress
Abstract
Progress in the use of artificial intelligence (AI) to advance scientific discovery has made it increasingly realistic to envision automated "end-to-end science" (ETES) systems: integrated pipelines that could generate hypotheses, run experiments (in silico or robotic), analyze results, and produce publishable outputs with minimal human intervention. The critical question is not whether AI can "do" science but whether science-as a social, evolutionary system that generates trustworthy knowledge-survives the way AI does it.
Fields of Study & Subjects
Scientific Computing and Data Management
Academic Publishing and Open Access
Cell Image Analysis Techniques
Publication details
- Journal / source
- Science
- Publisher
- American Association for the Advancement of Science (AAAS)
- Volume
- 392
- Issue
- 6800
- Pages
- 791–791
- Publication date
- 21 May 2026
- Language
- EN