We Think There’s Been a Glitch Artificial Intelligence and Machine Learning in Forensic Anthropology

Abstract

Forensic anthropology plays a pivotal role in the medicolegal system analyzing skeletal remains in forensic casework. With the increased incorporation of artificial intelligence (AI) and machine learning (ML), their continued application in the field promises
enhanced efficiency and accuracy in identification processes, trauma analyses, and decision-making. However, the integration of AI/ML also raises critical ethical concerns. The use of any technology involving human skeletal remains poses challenges related to privacy, consent, and the potential for dehumanization. Furthermore, the risk of bias within algorithms cannot be ignored—specifically, the inadvertent perpetuation of existing biases in training data, which can lead to incorrect identifications or skewed results. Addressing these concerns requires a balanced approach. Transparency in AI/ML design, clear guidelines for data collection and integration, and ongoing evaluation of algorithmic performance are essential. Additionally, interdisciplinary collaboration between anthropologists, ethicists, computer scientists, and legal experts would be a crucial step forward to ensure that the benefits of AI/ML are maximized while capturing the accountability and responsibilities within a legal and ethical context. Only through such an integrated approach can the potential of AI/ML in forensic anthropology be utilized as a tool responsibly, preserving the dignity of the deceased.