Über die Veranstaltung

The dominant narrative surrounding AI describes its impact across scientific disciplines as a significant shift—one that extends beyond mere tooling to influence the very fabric of research practices and epistemic cultures (Falk 2019; Fösel et al. 2019; Gethmann et al. 2022). This narrative is rooted in new and expanded types of prediction. Such capabilities require scientific disciplines to accommodate two interrelated challenges: uncertainty and simulated data. Both of these factors will be investigated at this conference across various methodological traditions.
The key question for this conference is how the impact of new AI-based research practices of prediction should be assessed. To test this narrative, we suggest to take a close look at the “doing, crafting, and toiling of scientists” (Heyman et al. 2017, 22). The conference seeks to capture realistic shifts in the forms of data usages and futurities with a focus on current European research projects. Specifically, we ask: How do AI-enhanced methodologies play out in forecasting, modeling, and pattern recognition?
To avoid treating ‘AI’ primarily as a punctuated innovation story, we have proposed to foreground the level of data practices and scientific methodologies, and to read current developments against longer histories of data, statistics, formalization, modeling, and simulation (Sudmann et al. 2023; Sudmann, Echterhölter & Schröter 2025).
To that end, we consider it essential to conceptualize AI neither as a value-neutral instrument nor as an epistemic authority in its own right. Instead, we examine how its transformative effects are mediated by the methodologies, infrastructures, and disciplinary norms through which it is implemented. Our extensive media ethnographies of AI-based research suggest that these implementations rarely remain uncontested. Recent methodological work has begun to explore agentic, multi-stage pipelines, in which specialized agents are assigned distinct roles across an end-to-end workflow for AI-supported qualitative analysis, while retaining space for critical human intervention (Retkowski et al. 2025). How then do validation, application, and critique in specific contexts of forecasting and future orientation play out?