Why AI Safety Requires Uncertainty, Incomplete Preferences, and Non-Archimedean Utilities
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866918265380405248 |
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| author | Benavoli, Alessio Facchini, Alessandro Zaffalon, Marco |
| author_facet | Benavoli, Alessio Facchini, Alessandro Zaffalon, Marco |
| contents | How can we ensure that AI systems are aligned with human values and remain safe? We can study this problem through the frameworks of the AI assistance and the AI shutdown games. The AI assistance problem concerns designing an AI agent that helps a human to maximise their utility function(s). However, only the human knows these function(s); the AI assistant must learn them. The shutdown problem instead concerns designing AI agents that: shut down when a shutdown button is pressed; neither try to prevent nor cause the pressing of the shutdown button; and otherwise accomplish their task competently. In this paper, we show that addressing these challenges requires AI agents that can reason under uncertainty and handle both incomplete and non-Archimedean preferences. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2512_23508 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Why AI Safety Requires Uncertainty, Incomplete Preferences, and Non-Archimedean Utilities Benavoli, Alessio Facchini, Alessandro Zaffalon, Marco Artificial Intelligence Computer Science and Game Theory How can we ensure that AI systems are aligned with human values and remain safe? We can study this problem through the frameworks of the AI assistance and the AI shutdown games. The AI assistance problem concerns designing an AI agent that helps a human to maximise their utility function(s). However, only the human knows these function(s); the AI assistant must learn them. The shutdown problem instead concerns designing AI agents that: shut down when a shutdown button is pressed; neither try to prevent nor cause the pressing of the shutdown button; and otherwise accomplish their task competently. In this paper, we show that addressing these challenges requires AI agents that can reason under uncertainty and handle both incomplete and non-Archimedean preferences. |
| title | Why AI Safety Requires Uncertainty, Incomplete Preferences, and Non-Archimedean Utilities |
| topic | Artificial Intelligence Computer Science and Game Theory |
| url | https://arxiv.org/abs/2512.23508 |