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Kantian Deontology Meets AI Alignment: Towards Morally Grounded Fairness Metrics
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Deontological ethics, specifically understood through Immanuel Kant, provides a moral framework that emphasizes the importance of duties and principles, rather than the consequences of action. Understanding that despite the prominence of deontology, it is currently an overlooked approach in fairness metrics, this paper explores the compatibility of a Kantian deontological framework in fairness metrics, part of the AI alignment field. We revisit Kant's critique of utilitarianism, which is the primary approach in AI fairness metrics and argue that fairness principles should align with the Kantian deontological framework. By integrating Kantian ethics into AI alignment, we not only bring in a widely-accepted prominent moral theory but also strive for a more morally grounded AI landscape that better balances outcomes and procedures in pursuit of fairness and justice.
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Towards Friendly AI: A Comprehensive Review and New Perspectives on Human-AI Alignment
A literature review that synthesizes definitions of Friendly AI and catalogs ethical arguments and technical subfields relevant to human-AI alignment.
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