AI and 3D evidence of Evolution of Human Hunting and Butchery Clarence E. Dammon Dean Academic Year 2023 Accepted Archaeology, data science, Artificial Intelligence, Human evolution Like archaeological detectives, this project uses the newest technologies to digitize evidence of ancient hunting on fossil bones using a 3D microscopic scanner, data science, and AI. Our purpose is to replicate the evidence via experimental archaeology (butchery using stone tools, launching spear points at animal bones, extracting marrow), then scan them in 3D, and use data science and AI to compare them with potential evidence of hunting on fossil bones. Erik R Otarola-Castillo Under instructor supervision, interns will conduct experimental archaeology to simulate evidence of hunting, scavenging, and butchery for nutrient extraction. Students will also analyze the resulting and available evidence in 3D. Moreover, we will search for ambiguous cases in the archaeological/paleoanthropological literature that warrant further investigation. Interns will learn the basics of (randomized-controlled) experimental design, 3D scanning of objects, data cleaning and analysis techniques, and the use of programming languages to conduct AI and data science work.

Interns will also aid in the preparation of Powerpoint presentations and data entry, management, and analysis. Following initial work, interns will also have the opportunity to contribute to the writing of manuscripts for publication and presentation at international professional conferences. Desired Candidate Qualifications: Candidates are required to possess a demonstrated interest and skill in two or more of the following: Anthropology, Archaeology, Human Evolution, and Human Ecology. in addition, candidates must have an interest in applying new technologies to answer problem-based scientific questions. Interested students must know how to use the library and their research procedures (e.g., inter-library loans) and have good basic-computer skills. Desired software knowledge includes ArcGIS, Word, Excel, and Access. Optional, but not required interests are in Computer science and statistics, and learning language skills like R, Python, Matlab, or C++. 3 10 (estimated)