Ongoing advancements in machine learning are opening new avenues for analyzing visual data, particularly in the realm of historical political economy. According to Valentine Figuroa from MIT, artworks from museums and private collections represent a largely untapped resource for understanding political history. Figuroa emphasizes the importance of establishing a framework to assess the information encoded in paintings and the assumptions guiding their interpretation.
This article introduces such a framework, integrating traditional humanities concerns with modern computational analysis. Using a database of 25,000 European paintings spanning from 1000 CE to the First World War, Figuroa outlines three distinct applications aimed at extracting valuable insights from these artworks. Each application targets different types of information conveyed through paintings, focusing on depicted content, communicative intent, and incidental details.
Exploring the Civilizing Process in European Art
The first application revisits the concept of a European “civilizing process,” which refers to the internalization of stricter behavioral norms alongside the expansion of state power. Figuroa examines how paintings depicting meals reflect increasingly complex etiquette over time. By analyzing the visual representations of dining scenes, the research aims to illustrate how societal norms evolved, providing a visual record of changing expectations regarding behavior in public and private settings.
Shifting Representations of Political Elites
The second application focuses on portraits, revealing how political elites crafted their public images throughout history. This analysis highlights a significant shift from chivalric representations to more rational-bureaucratic depictions of men. By examining the stylistic choices in portraiture, Figuroa’s work uncovers the evolving standards of masculinity and authority, shaped by the political landscape of the time. This shift reflects broader cultural transformations and the changing nature of power.
The third application documents a long-term process of secularization in European art, measured by the decreasing share of religious-themed paintings. Figuroa notes that this trend began prior to the Reformation and accelerated in its aftermath. By quantifying the representation of religious subjects in art, the research provides insights into the broader societal shifts away from religious authority and toward secular narratives.
Through these applications, Figuroa’s framework not only sheds light on the political implications of visual art but also challenges traditional interpretations of historical narratives. This innovative approach to art analysis positions paintings as critical data points in understanding the cultural transformations of the early-modern period.
As machine learning continues to evolve, the integration of art into political history offers a fresh perspective on how visual culture shapes and reflects societal values over time. The potential for further research in this area remains vast, promising new discoveries that could reshape our understanding of history itself.
