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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.06324 |
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| _version_ | 1866912317141155840 |
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| author | Jotautaite, Monika Phuong, Mary Mangat, Chatrik Singh Martinez, Maria Angelica |
| author_facet | Jotautaite, Monika Phuong, Mary Mangat, Chatrik Singh Martinez, Maria Angelica |
| contents | As large language models (LLMs) increasingly integrate into our daily lives, it becomes crucial to understand their implicit biases and moral tendencies. To address this, we introduce a Moral Foundations LLM dataset (MFD-LLM) grounded in Moral Foundations Theory, which conceptualizes human morality through six core foundations. We propose a novel evaluation method that captures the full spectrum of LLMs' revealed moral preferences by answering a range of real-world moral dilemmas. Our findings reveal that state-of-the-art models have remarkably homogeneous value preferences, yet demonstrate a lack of consistency. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_06324 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | From Stability to Inconsistency: A Study of Moral Preferences in LLMs Jotautaite, Monika Phuong, Mary Mangat, Chatrik Singh Martinez, Maria Angelica Computers and Society Artificial Intelligence As large language models (LLMs) increasingly integrate into our daily lives, it becomes crucial to understand their implicit biases and moral tendencies. To address this, we introduce a Moral Foundations LLM dataset (MFD-LLM) grounded in Moral Foundations Theory, which conceptualizes human morality through six core foundations. We propose a novel evaluation method that captures the full spectrum of LLMs' revealed moral preferences by answering a range of real-world moral dilemmas. Our findings reveal that state-of-the-art models have remarkably homogeneous value preferences, yet demonstrate a lack of consistency. |
| title | From Stability to Inconsistency: A Study of Moral Preferences in LLMs |
| topic | Computers and Society Artificial Intelligence |
| url | https://arxiv.org/abs/2504.06324 |