AI, Extra Credit, and the Andes: Discovering World’s Highest Communal Hunting Traps

With its environmental challenges and exceptional preservation, mountain archaeology affords special insight into human adaptability. New technologies such as remote sensing and artificial intelligence are elevating these archaeological insights, but their analytical power is fundamentally constrained by theoretical motivation and empirical grit. To illustrate this coupling and caution against unscrupulous application of new technologies, this talk presents a case study in which a theoretical hunch, student extra credit assignment, archaeological excavation, and artificial intelligence worked in concert to reveal more than 500 of the world’s highest communal hunting traps in the Andes Mountains, 4000–5000 masl. The discovery not only reveals a remarkable story of human cooperation and alpine engineering in the past but also how the potential of powerful new analytical tools depend on old analytical friends.