Faith, Human Dignity, and Governance: Why AI Ethics Demands Moral Depth Over Statistical Consensus
Wed, July 28 2026 /Mpelembe Media/ — The Limits of Preference Aggregation and the Rise of Algorithmic Pluralism Leading technology executives have proposed aligning artificial intelligence with human values by calculating a “weighted average” or statistical consensus through techniques such as Reinforcement Learning from Human Feedback (RLHF). However, social choice theory demonstrates that there is no unique voting protocol capable of universally aggregating individual preferences without generating logical contradictions or violating private ethical values. Theological and philosophical scholars emphasize that religious traditions cannot be reduced to modular, extractable rulebooks to be averaged in machine learning models. Attempting to compute a universal moral consensus flattens culturally rich worldviews, suppresses minority perspectives, and risks codifying dominant, secular-rational norms at the expense of global faith communities. Continue reading
