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To mitigate the negative effects of false information more effectively, thedevelopment of automated AI (artificial intelligence) tools assistingfact-checkers is needed. Despite the existing research, there is still a gapbetween the fact-checking practitioners' needs and pains and the current AIresearch. We aspire to bridge this gap by employing methods of informationbehavior research to identify implications for designing better human-centeredAI-based supporting tools.  In this study, we conducted semi-structured in-depth interviews with CentralEuropean fact-checkers. The information behavior and requirements on desiredsupporting tools were analyzed using iterative bottom-up content analysis,bringing the techniques from grounded theory. The most significant needs werevalidated with a survey extended to fact-checkers from across Europe, in whichwe collected 24 responses from 20 European countries, i.e., 62% active EuropeanIFCN (International Fact-Checking Network) signatories.  Our contributions are theoretical as well as practical. First, by being ableto map our findings about the needs of fact-checking organizations to therelevant tasks for AI research, we have shown that the methods of informationbehavior research are relevant for studying the processes in the organizationsand that these methods can be used to bridge the gap between the users and AIresearchers. Second, we have identified fact-checkers' needs and pains focusingon so far unexplored dimensions and emphasizing the needs of fact-checkers fromCentral and Eastern Europe as well as from low-resource language groups whichhave implications for development of new resources (datasets) as well as forthe focus of AI research in this domain.

Automated, not Automatic: Needs and Practices in European Fact-checking Organizations as a basis for Designing Human-centered AI Systems