Mitigating Generative AI’s negative impact on indigenous knowledge from international and Vietnamese laws perspectives - Duong Thuy Pham; Tronel Joubert (Technology and Regulation, 2025)
Indigenous knowledge, which has been developed over generations and possesses a unique understanding of local environments, offers precious responses to sustainable development challenges, for instance, climate change, biodiversity loss and pollution. Despite its pivotal role, indigenous knowledge of various ethnic minorities and indigenous peoples is in danger of disappearing due to centuries of history of colonization, discrimination and racism. The emergence of GenAI will complicate the knowledge preservation effort as GenAI models constitute a threat, via content created by those models, to perpetuating and even amplifying inaccurate information related to indigenous knowledge. This paper aims to discuss solutions to alleviate GenAI’s adverse impact on indigenous knowledge from international and Vietnamese laws perspectives, with the ultimate goal being to propose a feasible answer to protect indigenous knowledge of 53 ethnic minorities in Vietnam from GenAI’s threats. To arrive at the eventual outcome, this paper identifies the significance of indigenous knowledge to sustainable development, and the vulnerability of indigenous knowledge under GenAI’s drawbacks. The paper, additionally, applies experience in addressing this issue from an international perspective to the context of Vietnam. By doing so,  the paper furthermore raises the need for research to provide solutions to preserve and promote indigenous knowledge that suits the socio-economic condition of each country, as there is no one-size-fits-all answer for ethnic minorities and indigenous peoples on a global scale.