The role of financial mathematics in data protection and fairness in technology: based in a case study of Te Hiku Media
Yi Gu
LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library
Abstract:
This analysis explores how Te Hiku Media, a Mori-led non-profit organization, integrates interdisciplinary strategies to protect and revitalize the Mori language while actively resisting the forces of data colonization driven by large technology corporations. Central to their approach is the development of in-house machine learning models that leverage semi-supervised learning methods, which significantly reduce the need for extensive labeled datasets. By adopting this strategy, Te Hiku maintains linguistic sovereignty, safeguards cultural heritage, and minimizes reliance on external corporate infrastructures. Beyond the technical dimension, the organization applies financial tools such as cost-benefit analysis, Bayesian probability, and multivariate regression to support risk-aware decision-making in areas of data ownership, potential commercialization, and the long-term preservation of cultural value. The initiative also foregrounds critical ethical considerations, including the avoidance of algorithmic bias, the prevention of price discrimination in educational access, and the enforcement of strict community-led governance structures to ensure data privacy and cultural accountability. Te Hiku Medias work demonstrates how localized, ethical applications of artificial intelligence can simultaneously promote cultural continuity and advance social equity. Their model provides a replicable pathway for other Indigenous communities navigating similar technological, cultural, and geopolitical challenges in the rapidly evolving digital age.
Keywords: Te Hiku Media; financial mathematics; data protection (search for similar items in EconPapers)
JEL-codes: F3 G3 (search for similar items in EconPapers)
Pages: 7 pages
Date: 2025-12-24
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Citations:
Published in Advances in Economics, Management and Political Sciences, 24, December, 2025, 238(1), pp. 58 - 64. ISSN: 2754-1169
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:130831
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