A Framework for Assessing Moral Competence in Large Language Models

The growing intersection of artificial intelligence (AI) and ethics has prompted extensive research on aligning Large Language Models (LLMs) with human moral values. Awad et al. (2018) initiated this discourse through the “Moral Machine” experiment, exploring moral dilemmas faced by AI. Subsequent studies, including the creation of the ETHICS dataset by Hendrycks et al. (2020), aim to evaluate how effectively LLMs can predict human moral judgments involving concepts such as justice and well-being. Notable contributions include Askell et al. (2021) and Schramowski et al. (2020), which examine AI’s capacity for ethical reasoning. The discourse extends to perceived moral competence in models like GPT-3, as highlighted by Momen et al. (2023). Ongoing research continues to assess the robustness, fairness, and accountability of these systems, presenting challenges in ensuring AI ethically aligns with societal norms. Overall, as AI capabilities evolve, the ethical frameworks governing these technologies remain critical for safe implementation.

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