Ongoing advancements in machine learning are revolutionizing the way researchers analyze visual data, particularly in the field of historical political economy. Valentine Figuroa from the Massachusetts Institute of Technology (MIT) has highlighted the potential of paintings from museums and private collections as a significant yet underutilized source of information. This development paves the way for a detailed framework that assesses the data encoded in these artworks, establishing the criteria under which this information can be interpreted.
Figuroa’s article introduces a comprehensive framework aimed at evaluating the political and social narratives captured in art. The framework is based on enduring themes in the humanities and is applied to a database of 25,000 European paintings spanning from 1000 CE to the First World War. The research identifies three distinct applications that illustrate how paintings convey various types of information, including depicted content, communicative intent, and incidental details.
Exploring the Civilizing Process through Art
The first application revisits the concept of a European “civilizing process,” a term that refers to the internalization of increasingly strict behavioral norms alongside the expansion of state power. Figuroa examines paintings depicting meals to determine whether they reflect a growing complexity in etiquette over time. This analysis aims to shed light on how societal expectations and behaviors evolved in tandem with political developments.
Political Portraits and Public Image
In the second application, the research delves into portraits to investigate how political elites constructed their public personas. Figuroa highlights a significant shift in representation, moving from chivalric depictions to more rational-bureaucratic portrayals of men. This transformation reflects broader changes in political and social structures, revealing how art served as a tool for shaping public image during critical historical periods.
The third application focuses on the long-term process of secularization, a trend that began before the Reformation and intensified in its aftermath. By analyzing the proportion of religious paintings within the dataset, Figuroa documents how the representation of religious themes in art has changed over centuries. This analysis not only contributes to an understanding of the evolution of artistic expression but also reflects broader cultural shifts away from religious iconography.
Overall, Figuroa’s research underscores the importance of establishing a robust framework for interpreting the wealth of information contained in historical artworks. As machine learning technologies continue to evolve, the potential for uncovering new insights into political history through art becomes increasingly promising. This innovative approach invites further exploration into the intersection of art and data, opening new avenues for understanding the complex narratives woven into the fabric of political history.
