mlsanityData to 7 Oct 2026

Evaluating Machine Perception of Indigeneity: An Analysis of ChatGPT's Perceptions of Indigenous Roles in Diverse Scenarios

arXiv 2310.09237 ↗First posted 13 Oct 2023cs.AI cs.HCcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 2 of its 19 references that are in the map. First posted on arXiv 13 Oct 2023.

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2 of 19 references.

References · 2

  1. 2021AI and the Everything in the Whole Wide World Benchmarkcited by 340
  2. 2020Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligencecited by 100

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