Positive Alignment is defined as AI systems that support human flourishing pluralistically while staying safe and cooperative, presented as a necessary complement to existing safety-focused alignment research.
arXiv preprint arXiv:2403.18932 , year =
3 Pith papers cite this work, alongside 3 external citations. Polarity classification is still indexing.
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LLMs display political plasticity via prompt-driven ideological adaptation that is more reliable in larger newer models, but inverted questions produce counterintuitive shifts suggesting data leakage.
The paper introduces a taxonomy of AI safety for LLMs organized into Trustworthy AI, Responsible AI, and Safe AI perspectives, accompanied by a review of state-of-the-art methods, challenges, and future directions.
citing papers explorer
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Positive Alignment: Artificial Intelligence for Human Flourishing
Positive Alignment is defined as AI systems that support human flourishing pluralistically while staying safe and cooperative, presented as a necessary complement to existing safety-focused alignment research.
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Political Plasticity: An Analysis of Ideological Adaptability in Large Language Models
LLMs display political plasticity via prompt-driven ideological adaptation that is more reliable in larger newer models, but inverted questions produce counterintuitive shifts suggesting data leakage.
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AI Safety Landscape for Large Language Models: Taxonomy, State-of-the-art, and Future Directions
The paper introduces a taxonomy of AI safety for LLMs organized into Trustworthy AI, Responsible AI, and Safe AI perspectives, accompanied by a review of state-of-the-art methods, challenges, and future directions.