Anthropology and Archeology Teachers, Postsecondary

Teach courses in anthropology or archeology. Includes both teachers primarily engaged in teaching and those who do a combination of teaching and research.

The occupation “Anthropology and Archeology Teachers, Postsecondary” has an estimated automation risk of 41.6%, which is just slightly below the base risk for this occupation class (42.3%). This risk assessment reflects a balance between tasks susceptible to automation and those inherently resistant. On one hand, the academic environment is seeing an increased integration of technology, which can automate repetitive or information-based tasks. Computers, for instance, can already help conduct literature reviews, draft academic papers, and even create lecture materials, aligning with the automation of knowledge dissemination and routine research processes. Among the tasks most likely to be automated are conducting research and presenting findings, keeping up with field developments, and preparing and delivering lectures. These duties often involve compiling information, managing data, and reproducing established knowledge—areas where AI and algorithmic systems already excel. Online resources, academic databases, and automated presentation tools allow much of this work to be streamlined. Similarly, lectures can be replaced or supplemented by pre-recorded or AI-generated video content, digital simulations, and virtual classrooms that maintain consistency and efficiency in delivery. In contrast, the most resistant tasks for anthropology and archeology educators involve activities that require high interpersonal engagement, judgement, and contextual sensitivity. Advising student organizations, providing consulting services to government or industry, and conducting ethnographic field research depend on unique human interactions, empathy, and adaptability—traits not easily replicated by automation. The skill “Originality” is particularly significant as a bottleneck, with a low automation probability (3.3-3.9%). Originality underpins creative problem-solving and the generation of new theories or methods, cornerstones of both teaching and ethnographic research. As a result, while routine elements of this occupation may become increasingly automatable, the core creative, advisory, and fieldwork responsibilities will likely remain dominated by human expertise for the foreseeable future.