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Rethinking Libraries in the Age of AI: Impressions and Takeaways from TPDL 2025

This year, the 29th International Conference on Theory and Practice of Digital Libraries (TPDL 2025) took place in Tampere, Finland, from September 23–26. I attended the conference together with Sarah Oberbichler from the DH Lab to present our joint paper, “Studying Model Design Biases in LLMs for Multilingual Historical Newspaper Extraction; The Messina Earthquake Case Study”, in which we propose an explainability-driven framework to detect and analyze biases in large language models used for multilingual historical newspaper article extraction.

Focusing on the conference’s many LLM-related contributions, this blog post explores how digital libraries are evolving under the continuous advancement of AI and what digital humanities can contribute to the field. „Rethinking Libraries in the Age of AI: Impressions and Takeaways from TPDL 2025“ weiterlesen

LLM Biases: Expected and Unexpected Model Design Effects in Historical Newspaper Article Extraction on the Messina Earthquake

by Johanna Mauermann and Sarah Oberbichler

When it comes to analysing large collections of historical documents – like digitized historical newspapers – language models are incredibly powerful tools. But as these technologies become more common in humanities research, scholars also need to think critically about how they use them.

One big question researchers face when using language models for their analysis is about bias. Described by Rob Kitchin in his book „Critical Data Science,“ bias can be understood as „a consistent pattern of error within a dataset, or within a method of data processing and analysis, that skews findings and interpretation“ (Kitchin, 2024). Biases manifest in AI models on various levels: in the model design, in the data itself, in its application to contexts the model wasn’t trained for, and in the prompts themselves (compare e.g., Ferrer et al., 2021). Addressing bias questions therefore is crucial for ensuring our historical research stands up to scrutiny and Good Scientific Practice demands that we take these challenges seriously. „LLM Biases: Expected and Unexpected Model Design Effects in Historical Newspaper Article Extraction on the Messina Earthquake“ weiterlesen

Large-Scale Research with Historical Newspapers: A Turning Point through Generative AI

by Sarah Oberbichler

Digitized historical newspapers have been a crucial source for my research over the past decade. Exactly ten years ago, in 2014, I began my research journey with historical newspapers at the University of Innsbruck in Austria. Using a semi-automated multilingual approach to analyze a corpus of over 20,000 articles from German and Italian newspapers, I also started learning how to apply digital methods to historical sources: analyzing large-scale historical newspaper archives simply required such skills. „Large-Scale Research with Historical Newspapers: A Turning Point through Generative AI“ weiterlesen

Seasons of Green DH and Thirsty Computing

Talking about the weather used to be an innocent topic suitable for small talk. These days, this became a political issue, the existence of snow being populistically framed in order to negate climate change, completely misrepresenting its processes.

„Seasons of Green DH and Thirsty Computing“ weiterlesen