Bridging Values and Logic: Philosophical Thought Analysis for Coherence Alignment in Artificial Intelligence Decision Systems: A Cross-disciplinary Approach to Resolving Value Conflicts in AI Ethics
DOI:
https://doi.org/10.64504/big.d.v3i3.783Keywords:
Artificial Intelligence ethics, philosophical thought analysis, value alignment, cognitive dissonance, logical reasoning in AIAbstract
Artificial Intelligence (AI) decision systems are increasingly integral to critical domains, yet they frequently encounter complex value conflicts that challenge their ethical integrity. Existing AI ethics frameworks, while valuable, often neglect the internal logical coherence of an AI's 'belief' system, leading to inconsistent and unpredictable decision-making. This paper introduces a novel approach, grounded in philosophical thought analysis, to address this gap. We adapt principles from cognitive dissonance theory and logical reasoning to develop the AI Belief Alignment Framework (ABAF), a systematic methodology for identifying, analyzing, and resolving value conflicts within AI. The framework is implemented and tested across three simulated high-stakes scenarios: autonomous driving, medical diagnostics, and content recommendation. Our findings demonstrate that applying philosophical thought analysis significantly enhances the coherence and ethical consistency of AI decisions compared to traditional models. This research contributes a new, philosophically informed perspective to the value alignment problem, offering a practical pathway toward developing more robust, transparent, and ethically sound AI systems.
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