As much of the early Black press remains scattered or difficult to access, UC Santa Barbara English assistant professor Jim Casey is leading a project to recover and share 19th-century African American newspapers using artificial intelligence. He will head a national research team awarded $750,000 from Schmidt Sciences’ Humanities and AI Virtual Institute for “Communities in the Loop: AI for Cultures & Contexts in Multimodal Archives,” a project that brings together technology, scholarship and community participation to make early African American newspapers more broadly and freely accessible to the public.
Under Casey’s leadership, the interdisciplinary team brings together expertise from 10 universities and the Adler Planetarium to develop new AI tools that will help unlock fragmented archives of 19th-century Black newspapers. The project represents a fundamentally different approach to artificial intelligence — one that centers community participation and historical justice rather than corporate extraction and “black box” algorithms trained on biased data.
“As Freedom’s Journal, the first Black newspaper, declared in 1827, ‘Too long have others spoken for us,’” said Casey, founding director of the Early Black Press Project. “We are not just adapting existing AI to read these archives. We are asking: What can the Black press tradition itself teach us about gathering, sharing and transforming information?
“Early Black editors and journalists were innovating under slavery and Jim Crow — their methods have something profound to teach us about building better, non-extractive technology today.”
Translating this vision into functional technology requires overcoming significant technical hurdles. According to Casey, current commercial AI tools are often trained on mainstream datasets that fail to account for historical nuances. As a result, these models struggle to accurately read the complex, experimental layouts of historical Black newspapers and frequently generate errors based on biased training data.
To address this, the UCSB-led team is developing machine learning models specifically trained on Black press materials to perform page layout segmentation and optical character recognition.
“Professor Casey’s work represents a vital convergence of historical inquiry and technological innovation,” said Daina Ramey Berry, the Michael Douglas Dean of Humanities and Fine Arts. “By bridging the gap between advanced computing and the humanities, this new project not only recovers crucial history but demonstrates how UCSB is leading the way in ethical, community-focused research.”
