Partnering with AI to derive and embed principles for ethically guided AI behavior

Abstract

As artificial intelligence (AI) systems, particularly large language models (LLMs), become increasingly embedded in sensitive and impactful domains, ethical failures threaten public trust and the broader acceptance of these technologies. Current approaches to AI ethics rely on reactive measures—such as keyword filters, disclaimers, and content moderation—that address immediate concerns but fail to provide the depth and flexibility required for principled decision-making. This paper introduces AI-aided reflective equilibrium (AIRE), a novel framework for embedding ethical reasoning into AI systems. Building on the philosophical tradition of deriving principles from specific cases, AIRE leverages the capabilities of AI to dynamically generate and analyze such cases and abstract and refine ethical principles from them. Through illustrative scenarios, including a self-driving car dilemma and a vulnerable individual interacting with an AI, we demonstrate how AIRE navigates complex ethical decisions by prioritizing principles like minimizing harm and protecting the vulnerable. We address critiques of scalability, complexity, and the question of “whose ethics,” highlighting AIRE’s potential to democratize ethical reasoning while maintaining rigor and transparency. Beyond its technical contributions, this paper underscores the transformative potential of AI as a collaborative partner in ethical deliberation, paving the way for trustworthy, principled systems that can adapt to diverse real-world challenges.