What is it that software sees, hears and perceives when technologies for pattern recognition are applied to
media historical sources?
All historical work requires interpretation, but what kind of algorithmic interpretations of modernity does software yield from historical archives? Modern Times 1936 is empirically committed to everyday experiences and sets out to study how machines interpret symbols of modernity in media from 1936. By utilising photographic and audiovisual collections, the project seeks to analyse how modern Sweden was, while also exploring how computational methods can help us understand modernity in new ways.
The project will hence explore how artificial intelligence and machine learning methods can foster new knowledge about the history of Swedish modernity––while at the same time critically scrutinizing algorithmic toolboxes for the study of the past.
Modern Times 1936 will use three datasets from 1936: 15,000 digitized photographs from DigitaltMuseum, all surviving radio programs from Swedish Radio, and all weekly newsreels and short films produced by Svensk Filmindustri. The research focuses on modernity in relation to gender, urbanity and industrialization, and will: (1.) examine how software can assist historians in discerning new historical knowledge, (2.) construct midsize and curated datasets that increase the scholarly capacity of media historical sources, and (3.) interrogate algorithmic detection by evaluating what machines can—or cannot—notice in historic data.