American Association of Biological Anthropologists

Denver, CO; March 18th - 21st

Abstract

Since the late 1990s, development and application of artificial intelligence (AI) technologies has increased, with the past five years seeing exponential growth in the development of AI applications across disciplines. This expansion has increasingly influenced research methodology in biological anthropology, particularly through the development of AI decision support systems for assisting in skeletal based anthropological research contexts. As the field navigates and adapts to its relationship with these approaches, it has become apparent that ethical guidance on data collection, usage, and responsibility needs to be updated in response to emerging technologies. Skeletal biology data are frequently collected from documented skeletal assemblages, which often implement a formal consent process to participate in certain research activities (e.g., DNA). In response to growing public concern over data privacy and data transparency we posit that a similar informed consent process should be integrated for AI research, balancing research value and societal benefit. Beyond consent, responsible data analysis, application, and curation regarding AI remain underdeveloped, lacking standardized discipline-specific best practices. We consider several approaches to developing these practices, emphasizing transparency in model design, training, and data structure, along with challenges and dilemmas related to data storage and sharing. This includes necessary levels of model explainability for credible interpretations and differences in research perspectives and applications in different skeletal biology contexts. Collectively, these considerations inform how to maintain humanity in human skeletal data, promote ethical AI integration, advance AI best practices, and navigate the nuanced challenges of integrating AI in osteological research.

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