Keep AI-augmented science contestable
Why researchers must be able to inspect, challenge and correct the contributions of AI to science.
14 selected pieces · 2017–2026
Authored work and independent coverage identified01 / Selected perspectives
How AI changes scientific scrutiny, professional judgement and the terms of work.
Why researchers must be able to inspect, challenge and correct the contributions of AI to science.
A personal account of how AI-polished emails changed trust between colleagues, and why I returned to my own voice when personal connection mattered.
Why employees may hesitate to reveal AI productivity gains when their jobs could change.
02 / Selected perspectives
Professional ethics, AI-assisted verification, newsroom evaluation and the limits of provenance labels.
Who is responsible for finding out what users can still judge when AI checks facts for them? An argument for measuring unaided judgement, disclosing dependency and offering meaningful participation. Accepted for publication; author preprint available.
Applying the values of professional journalism to the design and evaluation of responsible AI. Published online 23 January; February 2024 issue.
An image’s provenance can be documented. That alone does not establish whether its source deserves our trust.
Editors need to test AI on their own journalistic tasks, document failures and repeat evaluations when systems change.
03 / Selected perspectives
Leadership, institutional power and the conditions for translating research into practice.
Academic leadership should be assessed through the people, teams and lasting capabilities it develops.
An argument for open competition and meaningful leadership assessment in universities.
An argument for aligning researchers’ risk, control and rewards when universities seek to turn research into new companies.
04 / Selected perspectives
From digital eating habits to AI-generated health advice, with selected independent discussion of the research.
A News & Views commentary on how online behaviour can help explain shifts towards diets with smaller environmental footprints.
Why AI-generated health advice belongs in the clinical conversation, drawing on research into the reliability of AI-generated nutrition information.
Writing by others about the research.
A separate News & Views article discusses recipe analysis and cites the Nature Food research by Angelsen, Starke and Trattner.
Coverage of the study comparing the nutritional quality of online recipes, cookbook recipes and ready meals, and the implications for recipe recommendation.
Original-language titles are retained. English summaries are brief guides to the pieces. Some publishers require a subscription.
For the next conversation
Christoph Trattner is Professor of Information Science at the University of Bergen and founder and director of SFI MediaFutures. His research focuses on responsible AI for media and health, spanning news recommendation, AI-supported journalism and trustworthy health information. His food research examines how online recipes and recommender systems can support healthier, more sustainable choices. He is Principal Investigator of CuratedAI and VaccAI, and an ACM Distinguished Speaker. His publications include research in Nature Food and scholarly commentary in Science and Nature Sustainability.
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Media enquiries trattner.christoph@gmail.com
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