Aligning Advanced AI Systems with Human Intentions and Values: A Comprehensive Survey
AI alignment aims to make AI systems behave in line with human intentions and values, focusing on the objectives of AI systems rather than their capabilities. Failures of alignment (i.e., misalignment) are among the most salient causes of potential harm from AI.
Supertrust: Rethinking Foundational AI Alignment Through the Lens of Mutual Trust Rather Than Permanent Control
Foundational AI alignment should prioritize building mutual trust between humans and AI over attempting to maintain permanent control, shifting from a control-based strategy to one that fosters a relationship of familial trust and cooperation.
Simulating Ethical Dilemmas: Comparing Behavior, Emotion, and Belief Alignment in Humans and Large Language Models
Large language models, particularly GPT-4o, demonstrate a consistent and strong sense of fairness and justice in simulated moral dilemmas, even surpassing humans in some aspects. However, human responses are more emotionally complex and influenced by feelings, highlighting the need for further research into aligning AI systems with nuanced human values and emotions.
倫理的ジレンマにおける人間とLLMエージェントの行動、感情、信念のアラインメント：FairMindSimによるシミュレーション研究
AI alignmentにおいて、LLMエージェントは公平性と正義において高い信念を示すが、人間の信念は感情の影響を受けやすく、より複雑で多様な反応を示す。
인간과 LLM 에이전트의 윤리적 딜레마 속 행동, 감정, 신념의 일치: FairMindSim 소개
본 연구는 인간과 LLM 에이전트가 불공정한 상황에 어떻게 반응하는지, 특히 사회적 가치와 감정, 신념 측면에서 어떤 차이를 보이는지 실험을 통해 분석하고, 이를 바탕으로 AI 정렬 문제에 대한 시사점을 제시합니다.
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