| Description |
This immersive two-day course aims at equipping participants with knowledge and practical skills in AI-assisted scientific writing. The program covers AI fundamentals, ethical considerations, and hands-on applications. Participants will learn good practices as well as major caveats in prompt engineering, scientific writing, and literature retrieval using usual web-based AI tools. Through interactive workshops and problem-solving sessions, students will develop critical skills, all without requiring technical expertise in data science.The course particularly emphasizes the responsible use of AI in research.
Day 1: Foundations and practical AI applications in writing
- Introduction to AI in life sciences: Brief history of AI/ML/NLP/LLM; introduction of algorithm functioning; current landscape of available tools for life scientists.
- Ethical considerations in AI: Research integrity; potential biases; considerations about authorship and citations; data privacy and confidentiality; institutional guidelines.
- Prompt engineering fundamentals: CraNing effective prompts; zero-shot vs few-shot learning; techniques for scientific writing; avoiding and spoPng allucinations; practical exercises in prompt design.
- AI for scientific writing: Literature retrieval and summarization; draNing manuscript sections; reference management; edition and refinement techniques; hands-on writing workshop.
- Practical session: Writing: Use of generic (ex: ChatGPT, Claude) and specific (ex: askyourpdf, consensus) tools; comparative analysis of outputs and capabilities; Hands-on exploration.
Day 2: Advanced AI functionalities of AI in the management of scientific contents
- AI in literature retrieval: Use of generic (ex: ChatGPT, Claude) and specific (ex: askyourpdf, consensus) tools.
- PiXalls of AI use in article writing: Be wary of 'hallucinations'; issues with content standardisation and tortured phases.
- Practical workshop: writing: Group challenges: writing a short (2 pages) referenced article on a given topic (free choice of tools); presentations of group outputs; critical evaluation.
- Can I peer review helped by AI?: Extracting information from a manuscript; detecting the use of AI; structuring a review report; journal regulations.
- Practical workshop: peer reviewing: Group challenges: peer reviewing a given (short) text; focus on the detection of AI contents, detection of fabricated images, and the writing of the review report.
- Caveat with AI detectors: Presentation of detectors; AI detectors lack reliability; A variety of outputs. • Final conclusions: Course wrap-up, perspectives, recommendations for continued learning.
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| Expenses |
Travel
PhD students of the CUSO DPEE are eligible for the reimbursement of incurred travel expenses by train (half-fare card, 2nd class). Claims can be done online via MyCUSO when the activity is over.
Fees
CUSO members: Free
Others (ex. MSc, postdocs, ...): please email the CUSO coordinator in charge to find out about your registration fee: plants(at)cuso.ch
DSLS-UNINE participants must keep all original tickets and receipts.
For any question regarding reimbursements, please contact Sarah Miéville (DSLS-UNINE coordinator at [email protected]) or visit https://www.unine.ch/dp-biol/courses-activities/ |
Workshop language is English 
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