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When Should an AI Act? A Human-Centered Model of Scene, Context, and Behavior for Agentic AI Design
arXiv – CS AI|Soyoung Jung, Daehoo Yoon, Sung Gyu Koh, Young Hwan Kim, Yehan Ahn, Sung Park||8 views
🤖AI Summary
Researchers propose a new conceptual model for agentic AI systems that addresses when and how AI should intervene by integrating Scene, Context, and Human Behavior Factors. The model derives five design principles to guide AI intervention timing, depth, and restraint for more contextually sensitive autonomous systems.
Key Takeaways
- →Current agentic AI systems lack principled judgment about when and whether to act proactively.
- →The proposed model separates observable situations from user-constructed meanings to explain different behavioral outcomes.
- →Five design principles emerge: behavioral alignment, contextual sensitivity, temporal appropriateness, motivational calibration, and agency preservation.
- →The framework draws from multidisciplinary perspectives across humanities, social sciences, HCI, and engineering.
- →The model aims to help design AI agents that act with better contextual sensitivity and judgment in human interactions.
Read Original →via arXiv – CS AI
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