Large Language Models (LLMs), like ChatGPT, are fundamentally tools trained
on vast data, reflecting diverse societal impressions. This paper aims to
investigate LLMs' self-perceived bias concerning indigeneity when simulating
scenarios of indigenous people performing various roles. Through generating and
analyzing multiple scenarios, this work offers a unique perspective on how
technology perceives and potentially amplifies societal biases related to
indigeneity in social computing. The findings offer insights into the broader
implications of indigeneity in critical computing.Comment: 5 pages, 3 figure