Harnessing AI to Uncover and Disseminate Complexity in the Oral Histories of Historic Ranchers: An Ethnographic Approach

Anne Palmer, University of Utah
Drew Holley, University of Utah

This paper proposes an exploration of ethnographic methods enhanced by Artificial Intelligence (AI) to address two critical aspects of studying oral histories of ranchers: (a) preparing a nuanced literature review taking into account the varied stakeholders, including indigenous prior occupants of ranch lands, and (b) disseminating videotaped oral histories effectively to libraries, researchers, and trade associations. By integrating AI tools into the analysis and dissemination processes, this research seeks to uncover the complex interplay between historical agency and emergent structures in the social and economic practices of ranching communities. The application of AI offers new insights into interdependence in systems, dynamic social processes, and network properties inherent in these oral narratives. This study aligns with the SSHA’s 2025 conference theme, addressing the potential and limitations of AI in understanding historical complexity and advancing methods for capturing emergent phenomena in history.

See paper

 Presented in Session 42. The Past and Present of Agribusiness