Business Bio

Christoph Trattner is one of Europe’s leading experts in responsible recommender systems, computational user behaviour, and trustworthy AI. With more than 20 years of experience at the intersection of academia, industry, and applied AI innovation, he helps organisations design, evaluate, and govern AI systems that influence human decision-making in high-impact domains such as media, health, food, and consumer behaviour.

He is a Full Professor at the University of Bergen, Director of the Research Centre for Responsible Media Technology & Innovation (SFI MediaFutures), and founder and leader of the DARS research group, Norway’s largest research group on recommender systems. He also leads the Norwegian Computational Behaviour & AI Lab, where interdisciplinary teams develop responsible AI solutions for real-world societal and business challenges.

Trattner has led large-scale research and innovation projects with startups, public-sector organisations, and multinational companies across Europe and the United States. As PI and Co-PI, he has helped secure more than 650 million NOK in competitive research and innovation funding, including the MediaFutures centre, with a total budget of approximately €26 million. His work has contributed to AI-driven prototypes, recommender systems, decision-support tools, and responsible media technologies in collaboration with leading media, health-tech, and consumer-oriented partners.

His expertise covers responsible AI strategy, recommender systems, user modelling, behavioural analytics, AI transparency, trustworthy personalization, and human-centred evaluation. A central theme in his work is appropriate trust: designing AI systems that users neither reject blindly nor trust uncritically, but understand, question, and use responsibly.

He has authored more than 150 scientific publications in leading venues and journals, including Nature Food, Nature Sustainability, Communications of the ACM, ACM UMAP, and The Web Conference (WWW). He is an ACM Senior Member and ACM Distinguished Speaker, and serves on the editorial boards of AI and Ethics and Online Social Networks and Media.

Through his research, advisory work, and centre leadership, Trattner supports organisations in turning responsible AI from an abstract principle into scalable, measurable, and societally valuable technology.

Academic Bio

Christoph Trattner is a Full Professor of Information Science at the University of Bergen and a leading European researcher at the intersection of recommender systems, responsible AI, and computational user behaviour. His research investigates how AI systems shape human decisions, preferences, trust, and behaviour, and how such systems can be designed to support healthier choices, trustworthy information environments, and societal benefit.

He is the founder and director of the Research Centre for Responsible Media Technology & Innovation (SFI MediaFutures), a large-scale Norwegian centre for research-based innovation on responsible media technology. He is also founder and leader of the DARS research group, Norway’s largest research group on recommender systems, and leads the Norwegian Computational Behaviour & AI Lab. Across these environments, he has built interdisciplinary research teams working across computer science, media studies, psychology, health, and the social sciences.

Trattner’s work focuses on responsible recommender systems, user modelling, personalization, behavioural analytics, AI transparency, human-AI interaction, and trustworthy media and health technologies. A recurring theme across his research is appropriate trust in AI: understanding when, why, and how people should trust algorithmic systems, and designing systems that support informed, critical, and beneficial use rather than blind reliance or rejection.

He has authored more than 150 peer-reviewed publications in leading international journals and conferences, including Nature Food, Nature Sustainability, Communications of the ACM, The Web Conference (WWW), ACM RecSys, and ACM UMAP. His research has received several distinctions, including a Best Paper Award Honorable Mention at The Web Conference and inclusion in ACM Computing Reviews’ Best of Computing for his work on visual recommender systems.

As PI and Co-PI, he has helped secure more than 650 million NOK in competitive research and innovation funding, including SFI MediaFutures, with a total budget of approximately €26 million. His projects combine scientific excellence with industry collaboration and societal relevance, particularly in the domains of responsible media technology, AI-supported journalism, health communication, food recommender systems, and trustworthy personalization.

He holds a PhD, MSc, and BSc, all with distinction, in Computer Science and Telematics from Graz University of Technology. His academic career includes appointments at Graz University of Technology, the University of Pittsburgh, and the Norwegian University of Science and Technology, as well as visiting research stays at Yahoo! Labs Barcelona and CWI Amsterdam. He is a former fellow of the Austrian Research Promotion Agency, the Marshall Plan Foundation, and ERCIM.

Trattner is an ACM Senior Member and ACM Distinguished Speaker. He has served as senior program committee member for leading conferences including ACM RecSys, SIGIR, and UMAP, co-chaired international workshops such as HealthRecSys and MSM, and served as program co-chair for MMM 2023. He also serves on the editorial boards of Online Social Networks and Media and AI and Ethics, and advises innovative startups including preforma and caneat.

His overarching goal is to advance AI systems that are not only technically powerful, but also trustworthy, transparent, human-centred, and beneficial for society.

Latest News

• [05/2026] Happy to share that our SFI MediaFutures paper “Explanations for Recommended Low-Interest News Articles Fail to Persuade Selective News Avoiders” with Svenja Lys Forstner and Alain D. Starke has been accepted at the INRA workshop at ACM UMAP 2026 in Gothenburg.
• [04/2026] Great news to share: our paper “Impact of a Prototype Combining Recommender Functionality with Structured Documentation on Operator Performance in Calls to Medical Communication Centers: A Quasi-Experimental Feasibility Study” has been published. The work explores how recommender-based decision support can contribute to medical communication and emergency primary care. Link
• [04/2026] Very happy to share that two new Research Council of Norway mobility projects connected to SFI MediaFutures and the University of Bergen have been awarded: CuratedAI, focusing on AI transparency, media literacy and appropriate media trust, and VaccAI, focusing on trustworthy health communication and vaccine beliefs in Norway and Ukraine. Together, the projects represent NOK 17.1 million in funding.
• [03/2026] Very happy to share that two of our full papers have been accepted at ACM UMAP 2026: “Increasing Editor Trust in News Personalization Systems with Fact-checked Large Language Models” and “Using AI as a Chef: Users Overlook Nutritional Flaws in LLM-Generated Recipes”. Both papers are led by my research assistants Tobias Jovall Wessel and Yelyzaveta Lysova as first authors, together with Alain D. Starke and myself.
• [02/2026] Happy to share that I will be on parental leave until mid-June, spending time with my daughter.
• [01/2026] We are happy to announce NoSoCSS — a new interdisciplinary initiative advancing research at the intersection of computational social science, data, and society: https://nosocss.org/.
• [11/2025] I’m excited to share that our paper “C2PA Provenance Labels Increase Trust in Digital News Platforms Across Western Countries” has been accepted (8% acceptance rate this round) for publication at the prestigious ICWSM 2026 conference – The International AAAI Conference on Web and Social Media! Pre-Print
• [11/2025]My PhD student Ayoub has passed his PhD defense with flying colors. He also got a paper accepted at IEEE Access in the context of his PhD about digital nudges and recommender systems. PDF
• [09/2025] Happy to share that I have started up a new lab initative focused on user behaviour & responsible AI. Check it out
• [08/2025] Great news, 6 papers in workshops at ACM RecSys 2025 have been accepted for publication and presentation by our PhD and MA students :)
• [07/2025] Happy summer holidays :)
• [05/2025] Happy to share that "The role of GPT as an adaptive technology in climate change journalism." has been accepted at ACM UMAP 2025 as a full paper. PDF
• [05/2025] Happy top share that MediaFutures passed its midway evaluation with flying colors!
• [04/2025] Happy to share that "Decoding Global Palates: Unveiling Cross-Cultural Flavor Preferences Through Online Recipes" has been accepted and published Foods journal. PDF
• [01/2025] Our paper "Supporting healthier food choices through AI-tailored advice: A research agenda" has been accepted and published in Elsevier's PEC Innovation journal. PDF
• [01/2025] Our paper "Evaluating Sequential Recommendations in the Wild: A Case Study on Offline Accuracy, Click Rates, and Consumption" has been accepted at ECIR 2025. PDF
• [10/2024] I’m thrilled to share that three papers lead by our PhD students have been accepted at the INRA and HealthRecsys workshops in this year's ACM RecSys 2024 conference in Bari!
• [09/2024] Happy to share that our paper "Advancing Visual Food Attractiveness Predictions for Healthy Food Recommender Systems" has been accepted at the HealthRecsys workshop at ACM RecSys 2024.
• [08/2024] Our paper "Examining the merits of feature-specific similarity functions in the news domain using human judgments" has been published in Springer's UMUAI journal. PDF
• [07/2024] Happy holidays :)
• [06/2024] Fantastic to hear that our MediaFutures PhD candidate Anastasiia Klimashevskaia has gotten a Level 2 journal (highest journal ranking in Norway) accepted based on her PhD work.
• [06/2024] In total, we got 4 papers accepted at ACM UMAP 2024! Read the news here :)
• [04/2024] Nice to hear that our Workshop proposal on Health Recommender Systems with Helma Torkamaan, Hanna Hauptmann and myself as organisers has been accepted at ACM Recsys 2024 as a full day workshop! Stay tuned for the call for papers :)
• [03/2024] Great to hear that our paper "Shaping the Future of Content-based News Recommenders Insights from Evaluating Feature-Specific Similarity Metrics" with our MA student Daniel Roses as first author and co-authored/supervised by Alain Starke and myself has been accepted to ACM UMAP 2024 as a Full Paper!
• [02/2024] Great to hear that our MediaFutures: Research Centre for Responsible Media Technology & Innovation opinion paper co-authored by Nick Diakopoulos, Christoph Trattner, Dietmar Jannach, Irene Costera Meijer and Enrico Motta, entitled "Leveraging Professional Ethics for Responsible AI: Applying AI techniques to journalism." is finally online and published in Communications of the ACM! PDF
• [01/2024] Happy new year!
• [2023 - 2012] For older news, check the source code!

Latest 10 Publications

• Increasing Editor Trust in News Personalization Systems with Fact-checked Large Language Models. Wessel, T. J., Starke, A. D., and Trattner, C. ACM UMAP, 2026. PDF
• Using AI as a Chef: Users Overlook Nutritional Flaws in LLM-Generated Recipes. Lysova, Y., Starke, A. D., and Trattner, C. ACM UMAP, 2026. PDF
• Explanations for Recommended Low-Interest News Articles Fail to Persuade Selective News Avoiders. Forstner, S. L., Starke, A. D., and Trattner, C. INRA Workshop at ACM UMAP 2026, 2026. PDF
• Impact of a Prototype Combining Recommender Functionality with Structured Documentation on Operator Performance in Calls to Medical Communication Centers: A Quasi-Experimental Feasibility Study. Fotland, S.-L., Berge, A., Zakariassen, E., Midtbø, V., Baste, V., Fonnes, G., Guribye, F., Trattner, C., You, J., and Johansen, I. 2026. PDF
• C2PA provenance labels increase trust in news platforms across Western countries. Trattner, C., Forstner, S. L, Starke, A. D., & Knudsen, E. AAAI ICWSM 2026, 2026. PDF
• How Digital Nudges Can Be Integrated into AI Systems to Support Healthier Food Choices. A. El Majjodi, A. D. Starke & C. Trattner. Proceedings of the IEEE Xplore, IEEE, 2025. PDF
• Hope, Fear, or Anger? How Emotional Framing in a News Recommender System Guides User Preferences. Eknes-Riple, J., Hua, J., Jeng, J., Starke, A. D., Seddik, K. M. A., and Trattner, C. INRA Workshop at ACM RecSys 2025, 2025. PDF
• More of the Same? A Longitudinal Evaluation of Two Similarity-based Approaches in a News Recommender System. Kasangu, G., Starke, A. and Trattner, C. INRA Workshop at ACM RecSys 2025, 2025. PDF
• Using Large Language Models to ‘Lighten the Mood’: Satirically Reframing News Recommendations to Reduce News Avoidance. Wessel, T., Trattner, C., and Starke, A. INRA Workshop at ACM RecSys 2025, 2025. PDF
• Evaluating Image Trust Labels in a News Recommender System: Assessing the impact of visual trust indicators for images on user trust and interpretation. Forstner, S. L., Lysova, Y., Starke, A. D., and Trattner, C. INRA Workshop at ACM RecSys 2025, 2025. PDF