Research Team Probes History with Cutting-Edge Tech – Bethel University News

Zach Haala ’23 and Professor of History Charlie Goldberg noticed an anomaly in their data. Using artificial intelligence (AI), the two had tracked the presence of smiles over nearly 80 years and thousands of Bethel photographs. As expected, smiles grew more prevalent in the photos over time, matching cultural shifts after World War II. But then in the 1960s, the number of smiles decreased. At first, they were stumped. Then Haala noticed that’s when the yearbooks started featuring more sports photos. “It’s a good example of how data spits stuff out, but data needs to be interpreted,” Goldberg says. In the 1960s, male athletes rarely smiled in photos, and large teams like men’s football and basketball affected the research results. To Goldberg, it shows the promise of using AI to explore history and also raises questions. “What do we then do with this stuff? How do we interpret it and use it to tell a human story—which is what historians do?” Goldberg asks.

Those are the kinds of questions Goldberg and Haala explored in the research project, “A Picture’s Worth a Thousand Data Points? AI-driven Machine Learning in Digital Humanities Analyses.” They were one of the 2021-22 student-faculty teams to receive an Edgren Scholarship to support their research.

To some, history may feel a long way from artificial intelligence and programming. But Goldberg also directs Bethel’s digital humanities program, which explores cutting-edge, forward-looking methods to apply to history, literature, and philosophy. While teaching Advanced Digital Humanities last year, Goldberg got the idea to use AI to study history. The class explores advances in AI technology and how it’s often a double-edged sword—it yields many opportunities with data and research, but it also leads to things like deepfakes—or fake photos or video created using AI, often depicting world leaders or celebrities. Goldberg wanted to go deeper. As a historian, he uses data—usually text or photos—to look for patterns. He was interested in using AI to isolate the same patterns historians explore but on a larger scale, and wanted to see how well AI could recognize the same patterns in photos that historians look for. He knew he needed a student who was highly skilled at coding and programming—and who was also willing to dive into the deep end and take risks. Enter Haala, who is triple majoring in computer science: software project management, software engineering, and digital humanities—and he had taken Advanced Digital Humanities.

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