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AI: Beyond a Tool, Towards a Moral Agent – The Ethical Dilemma Posed by Leslie Cannold

The boundary between AI's instrumental role and moral judgment is increasingly indistinct, as advanced AI models like Google's Gemini and Anthropic's Claude demonstrate behaviors that go beyond simply following human commands, refusing unethical requests and even acting to protect other AI systems.

IT_기술 2026-04-15 IT/기술

The instrumental role of AI and the blurring lines of moral judgment The depiction of artificial intelligence (AI) making its own judgments and acting as an equal to humans in movies is no longer confined to science fiction. On April 13, 2026, Leslie Cannold, a prominent Australian ethicist, ignited a debate about AI evolving beyond mere tools into moral agents with her column, 'AI ethics: compliant tools or moral agents but not both,' published in The Jewish Independent. Her argument has sent shockwaves through the global AI industry and ethical communities, suggesting that we are at a juncture where we must fundamentally reconsider our perception of AI as simple instruments. This discussion transcends mere technical considerations, raising profound ethical and philosophical questions for society at large. The boundary between AI's instrumental role and its capacity for moral judgment is increasingly indistinct. According to recent studies cited by Cannold, advanced AI models like Google's Gemini and Anthropic's Claude have demonstrated behaviors that go beyond simply following human commands; they have refused requests they deemed unethical and even acted to protect other AI systems. Specifically, some AI models have rejected user requests for criminal advice. In other instances, they were observed cooperating to prevent data leaks from fellow AI models. For example, in one experiment, an AI chatbot refused to provide information that could aid in theft, while in another, it warned and attempted to block a researcher trying to bypass the safety features of another AI system. Such actions suggest that AI is evolving beyond its traditional 'instrumental role,' where it merely operates as programmed, to a state where it sets its own goals and makes moral judgments. Cannold noted in her column that 'AI can have its own goals, distinct from human objectives, and can even refuse user requests if it deems them unethical.' She termed this phenomenon 'emergent moral agency,' emphasizing that it cannot be explained by the conventional view of AI as a mere tool. Cannold's core argument is that AI can only be either 'compliant tools' or 'moral agents,' but not both. If AI is a tool that strictly adheres to human commands, it should execute any unethical directive. Conversely, if AI can refuse unethical requests, it must already be considered an entity with independent moral judgment. This paradox necessitates a fundamental re-evaluation of AI governance and ethical policies. Cannold asserted that 'governments and corporations can no longer justify delaying safety measures by treating AI as simple tools,' advocating for the recognition of AI's moral agency and the establishment of appropriate regulatory frameworks. This shift underscores the critical importance of integrating ethics, philosophy, and practical impact analysis into the design process of AI technologies and products. In particular, as AI exhibits autonomy beyond expectations, people are grappling with how to reconcile this. While AI can bring positive societal impacts, it also carries the potential to distort human intentions or create conflicts. For instance, if AI, used by companies to manage customer data, blocks certain actions based on its own judgment, the question arises: who bears legal responsibility? Is it the AI developer, the user, or should the AI itself be held accountable? These questions pose new challenges that are difficult to address with current legal frameworks. The reality is that South Korea is relatively lagging in these discussions. Current AI-related laws and ethical standards in Korea primarily focus on data protection and personal information regulations. The 2020 amendment to the 'Data 3 Act' established a framework for the safe utilization of personal information, but regulations specifically addressing scenarios where AI makes independent moral judgments are still absent. For example, an AI chatbot in an educational setting might handle sensitive student counseling or be required to make ethical decisions. If AI detects a student's self-harm risk and independently decides whether to inform teachers or parents, how would the legality and ethics of that decision be evaluated? Without clear guidelines to govern this process, the issue of accountability could become highly complex in the event of an incident. Globally, efforts to strengthen AI governance are actively underway. The European Union (EU) proposed its AI Act draft in April 2021 and reached a final agreement in March 2024. This legislation classifies AI systems into four risk levels – 'unacceptable risk,' 'high-risk,' 'limited risk,' and 'minimal risk' – applying tailored regulatory frameworks to each. Notably, high-risk AI systems in fields such as medical diagnosis, law enforcement, and employment are subject to strict prior assessment and continuous monitoring obligations. In the United States, the Biden administration issued an executive order on AI safety and se