The Relation between Micro and Macro History

During recent years, we have witnessed a growing convergence between historical disciplines and research in Artificial Intelligence (AI). This convergence operates on various levels and brings about diverse impacts: from basic classificatory models aiding source analysis to unsupervised models autonomously establishing similarity-based relationships among data sources. Additionally, there are eXplainable AI approaches that elevate machine learning (ML) models from mere supportive tools to active investigative instruments capable of generating insights and enriching domain experts' knowledge.

This presentation will delve into how this evolving dynamic is reshaping the relationship between micro and macro history. It will draw upon current research examples to illustrate how the amalgamation of AI research and historical disciplines might pave the way for AI-generated long-term trend analyses. These analyses, in turn, could serve as a guide for historians seeking specific relevant moments and cases within or characterizing the historical process they are investigating.