Bridging the Gap Between Human and Artificial Intelligence-Translating Traditional Ecological Knowledge into Machine Learning Models
Abstract
Traditional Ecological Knowledge (TEK), largely untapped by science, could be considered the original situational awareness skillset, formed through multi-factorial individual and group observations and inferences, using complex cognitive processes. The elements and pathways of TEK are structured on trust and influence within and between groups. This project will collaborate with two distinct groups of tracking experts; primary or indigenous trackers and secondary experts who have individually acquired tracking expertise using Western analytical methods. By examining the contrasts in their methods-such as communal versus individual learning, intuitive versus deductive reasoning, and reaction-decision times both in the field and during analysis of knowledge on digital platforms-decoding their cognitive processes will be key to understanding how they interpret and trust ground evidence. Numerous factors influence the acquisition of environmental knowledge, with the local ecosystem or natural environment being a primary determinant. This project will be conducted in two significantly different settings- the Kalahari Desert in Botswana and the rainforest in Brazil.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 06, 2025
- Source ID
- FA95502510027
Entities
People
- Zoe Jewell
Organizations
- Air Force Office of Scientific Research
- United States Air Force