The Arctic, a region of unparalleled environmental complexity and geopolitical significance, stands at an inflection point shaped by both modern Artificial Intelligence (AI) methodologies and profound Indigenous insights. This paper delves into the role of AI in Arctic Climate Data Science, emphasizing its transformative impact in assimilating and analyzing vast data sets, from high-resolution satellite imagery to age-old oral traditions of Indigenous communities. We explore the capacity of AI sub-domains, including machine learning, neural networks, and deep learning, in harnessing the dual knowledge systems to offer a panoramic view of the Arctic’s ever-evolving dynamics. Additionally, the paper critically evaluates the challenges AI presents, from data integrity concerns to potential feedback loops that compound errors. Broader geopolitical ramifications, intensified by the Arctic’s changing landscape and potential operational risks, further underscore the necessity of a synergistic approach in applying AI to this region. Conclusively, the research underscores the essential balance between technological advancements and respect for Indigenous knowledge, offering strategic recommendations for a sustainable Arctic future.
