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The articles in this special issue grew from a symposium at the 2020 American Academy of Forensic Sciences Annual Scientific meeting, with the same title as this introduction. The symposium focused on current research and practice of ancestry estimation in forensic anthropology. The symposium concluded with a discussion of the value (or lack thereof) of ancestry estimation as a standard component of the forensic anthropological biological profile. The articles constituting this volume address these questions: What is the current state of race/ancestry estimation in practice? What terminology should we use to describe patterned variation among human populations? How do we sample contemporary populations, and how long are studies built on such samples applicable? What role does genomic data play? Should race/ancestry remain a core component of the biological profile? Further, the issue includes an examination of ancestry estimation in teaching and community outreach. While fine points are still up for debate among these authors, there is general agreement that any future of ancestry estimation must be based in cultural context and evolutionary theory, be sensitive to the importance of terminology employed, and be iteratively reflexive about the relative costs and benefits of this work. [ABSTRACT FROM AUTHOR]

The use of crown and root morphology to estimate population relationships has a long history in dental anthropology. Over the past two decades, methods employing dental morphology within forensic anthropology have been formalized with the incorporation of statistical models. This paper presents a new web-based application (rASUDAS) that estimates the ancestry of unknown individuals based on their suite of tooth crown and root traits. The application utilizes 21 independent traits that were scored following the Arizona State University Dental Anthropology System (ASUDAS). The reference sample represents approximately 30,000 individuals from seven biogeographic regions. A naive Bayes classifier algorithm was created in the R open source programming language to assign posterior probabilities for individual group assignment. To test the application, 150 individuals were selected from the C. G. Turner II database with the proviso that an individual had to be scored for a minimum of 12 of the 21 traits. In a seven-group analysis, the model correctly assigned individuals to groups 51.8% of the time. In a four-group analysis, classification accuracy improved to 66.7%. With three groups, accuracy was at 72.7%. It is still necessary to validate the program using forensic cases and to augment the reference sample with modern skeletal data. However, results from the beta version of rASUDAS are presented as proof of concept on the potential of dental morphology in ancestry estimation in forensic contexts. [ABSTRACT FROM AUTHOR]