Practice, Theory, and Ethics of Machine Learning in Archaeology

This collection contains the abstracts of the papers presented in the session entitled "Practice, Theory, and Ethics of Machine Learning in Archaeology" at the 90th annual meeting of the Society for American Archaeology.

Technological advances have catalyzed scientific innovation and societal change for centuries, but the recent precipitous rise in computing power has introduced powerful new tools at a rapid pace, which can be overwhelming to parse. In particular, the increasing popularity of machine learning (ML) methods in archaeology has occurred so quickly that many scholars are left with questions regarding how, why, and with what datasets these methods should be used. This symposium explores the practices, theories, and ethics linked to emerging ML methods in archaeology. We showcase new and innovative approaches to the topic, explore the practical applications of ML that emphasize enhancing data quality, site preservation, and synthesis, discuss publishing and code sharing, and provide a forum to discuss the ethical use of ML in archaeology.