Researching with AI. Between Opportunity and Imposition
AI increasingly influences how we produce, assess and communicate research. Join us in an engaging workshop exploring uncertainties about the epistemological and methodological status of AI generated scholarly output.
WHAT: Workshop at the University of Bern
WHEN: 11th of February, 2026, 13:30-17:15 CET
WHERE: Main Building, Hochschulstrasse 4, Room 115
Artificial intelligence promises to revolutionize scholarly and scientific inquiries. It influences how we produce, assess, and communicate our research. However, generative AI is not a neutral instance but built on previously digitized data, text, and imagery. Therefore, all generative AI systems are highly biased and a model of the past. Still, it is undeniable that the usage will allow us to create new forms of research.
The workshop combines theoretical approaches to open research data strategies with applied uses of various forms of artificial intelligence. By addressing AI as a methodological issue, we don't subscribe to the hype but rather put the various opportunities and limitations up for discussion.
Amrei Bahr (University of Stuttgart) is a renowned expert in the field and an important voice with regards to epistemological and methodological questions, when leveraging AI in the sciences. She will open the event with an introductory talk that sets the stage for the discussion.
In the second part, we invite you to share concrete cases and examples in which you felt uncertain about how to use AI appropriately. These cases will form the basis for a joint reflection. In the final part, data stewards will comment on the raised uncertainties and provide their distinct perspectives.
This event is organized by Open Science/University Library and the Digital Humanities.
This event is part of the international Love Data Week 2026 #LoveData26
Call for Contributions: Uncertainties & AI
We are looking for short contributions (inputs of about 5 minutes, with a max. of 10 slides) based on your experience with generative Artificial Intelligence.
What scientific or scholarly output did you produce with AI, and are you uncertain about its epistemological or methodological status?
Describe your case and approach, including your stance on it.
Examples could be (but are not limited to):
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Vibe coding
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Data analysis
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Information extraction
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Synthetic data generation
Please send your proposal (topic and your questions, informal) until 25th of January 2026 to Ursula Loosli: ursula.loosli@unibe.ch
The language of the workshop will be English.
