Caring Without Feeling: Affective Dynamics as the Control Layer of Human-AI Agent Collaboration
arXiv:2606.18259v1 Announce Type: cross Abstract: AI agents that plan, retain memory across sessions, invoke external tools and act with partial autonomy are transforming human--AI collaboration. Research on affective computing, simulated empathy in large language models, trust in automation and AI safety has illuminated important design principles, yet these literatures remain fragmented. No integrated account explains how affective cues operate within agentic collaboration -- settings in which humans delegate, monitor and correct consequential tasks. This Review synthesises computational and
The paper addresses the crucial intersection of affective computing and AI agent development, which is increasingly relevant as autonomous agents become more integrated into complex human workflows.
Understanding how affective cues manage human-AI agent collaboration is critical for designing robust, trustworthy, and effective autonomous systems, directly impacting productivity and safety.
This research provides an integrated framework for understanding the role of affective dynamics in agentic collaboration, moving beyond fragmented approaches in AI safety and trust.
- · AI development firms
- · Human-computer interaction researchers
- · Industries deploying AI agents
- · Users of AI-powered tools
- · Developers ignoring human factors
- · Companies with poorly integrated AI systems
Improved design and functionality of collaborative AI agents across various applications.
Increased adoption and trust in autonomous AI systems in high-stakes environments.
Re-evaluation of ethical guidelines and regulatory frameworks for emotionally intelligent AI interactions.
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Read at arXiv cs.AI