Google and DeepMind teams release first mass-scale empirical study of AI's impact on science
JMateosGarcia · x · 2026-09-16
Google DeepMind and Google teams have released "AI in Science: Early Insights", described as one of the first mass-scale empirical investigations into AI's impact on science, co-led with Jose Mateos-Garcia and Miguel Codreanu plus a team of co-authors. The authors frame it as the start of a new research agenda: AI's promise for economic growth runs directly through its impact on science. The report delivers numerous findings and insights while leaving many open questions, addressing the gap between widespread excitement/concern about AI in science and the lack of systematic empirical evidence.
More from AGI Musings
- AI safety researcher: AI companies entirely lack this kind of effective human oversight — davidmanheim · 2026-11-02
- Long-read: AI's real value comes after the efficiency era—infra glut, agent tooling boom — yangyi · 2026-11-02
- vikhyat predicts alternating compute oversupply and undersupply on the road to AGI — TheZachMueller · 2026-11-02
- Sam Altman: AI has surpassed top scientists, and 2026 will be a turning point year — kimmonismus · 2026-11-02
- DeepSeek design doc: a person can only follow 3-5 agent sessions at once, attention is the real bottleneck — heyshrutimishra · 2026-11-02
- AI researcher: we have no reliable way to tell whether an AI system is conscious — dioscuri · 2026-11-02