Readable notes
Reading guide
Summary
This review asks how plant science education and research training should change as generative AI becomes part of everyday scientific work. It is framed as a global perspective, with attention to both opportunity and uneven access.
Key themes
- Generative AI can support plant scientists in literature work, coding, data analysis, communication, and teaching.
- Training needs to include responsible use, evaluation, reproducibility, and awareness of limitations.
- Access constraints affect whether AI training resources can be adopted across labs with different infrastructure, funding, and institutional support.
Technical contribution
The review is paired with a companion repository of AI tools and learning resources for plant scientists: plant-ai-training.
Review scope
The review covers computational tools for plant-science training, with emphasis on access, evaluation, responsible use, and reproducibility.