Ethical AI and Sustainability through the Ayni MultiNeutrosophic Method Based on Ancestral Logic and N Alectical Reasoning

Abstract

This paper introduces the Ayni MultiNeutrosophic Method, an innovative framework that integrates Latin American indigenous philosophies with neutrosophic logic to guide the ethical and sustainable development of Artificial Intelligence (AI). Based on ancestral principles such as Ayni, Buen Vivir, In Lakech, Chixi, and Nepantla, this approach enables the modeling of plural, ambiguous, and context-dependent ethical judgments through Multi-Neutrosophic Sets (MNS). A key contribution is the Multi-Neutrosophic Euclidean Consensus Measure, designed to quantify the level of agreement among evaluations from different stakeholders without eliminating epistemological differences. This tool facilitates the identification of convergence thresholds during intercultural deliberations, providing a robust and flexible instrument for complex ethical decision-making. The method is illustrated through a case study analyzing the implementation of an AI based diagnostic system within an indigenous community. Findings indicate that the iterative application of the Ayni principle, understood as a process of reciprocal ethical negotiation, enhances both alignment among parties and the legitimacy of decisions. This work demonstrates that indigenous logics, when formalized through neutrosophic, possess not only profound philosophical value but also methodological utility for designing responsible and sustainable AI systems, operationally supporting the development of fair, inclusive, and context-sensitive technologies.