Explorer Projekt Multi-Level Aggregation

This interdisciplinary project investigates the handling of information at different levels of aggregation (multi-level) and the regulation between them. Considering the same problem at different levels can lead to entirely different implications for action and decision-making. Crucial for successfully managing multi-level data is the effective regulation between different levels of aggregation and an understanding that different truths can coexist at different levels. Metacognitive monitoring can contribute to a deeper understanding of the data and its inherent levels of aggregation, helping to clarify apparent contradictions. Successful regulation enables the process of moving from mere knowledge of the data to appropriate actions and decisions.

This complex interplay is investigated in the project through experimental research. The aim is to explore the influence of information at different levels of aggregation on decisions and behavior, and under what conditions successful regulation succeeds or fails. The project links this to the question of which interventions can support successful regulation. Approaches to collective decision-making, debiasing methods, and the support provided by modern IT infrastructure are being considered. Initial findings indicate that groups find it easier to regulate appropriately between levels of aggregation.
Multi-level problems represent a significant source of social and political conflict from an inherently interdisciplinary perspective. Different actors can view a problem at precisely the level of aggregation that best suits their interests, thereby contributing to the emergence of conflicts and errors. This project offers the opportunity for new collaborative research and knowledge transfer on the handling of complex data and the resulting actions and decisions in the fields of sport, fitness, and health.

Status: 2. Quarter 2022