arXiv:2605.31340v1 Announce Type: cross Abstract: The appropriateness of empathy in AI has emerged as a critical concern, as excessive empathy risks seeming manipulative while insufficient empathy appears dismissive. While prior research has explored how to quantify empathy in AI, few studies examine whether such empathy is contextually appropriate. This paper introduces an economic perspective by applying signaling theory to human-AI conversations. We propose Signal Cost Proxies (emotional richness, perspective-taking, and contextual tailoring) mapped to affective, cognitive, and associative
The rapid advancement and integration of AI into human-facing applications necessitate urgent attention to the qualitative aspects of AI-human interaction, moving beyond mere technical capability.
Understanding the 'appropriateness' of AI empathy from an economic perspective provides a robust framework for developing more effective and trustable AI systems, influencing adoption and regulatory approaches.
The focus expands from simply building empathetic AI to strategically deploying empathy where it yields the most effective and non-manipulative outcomes, guided by 'signal cost' principles.
- · Ethical AI developers
- · AI-powered customer service
- · Human-computer interaction researchers
- · Trustworthy AI platforms
- · AI systems with undifferentiated empathy
- · Developers ignoring contextual appropriateness
- · Users subjected to manipulative AI
- · Companies with low-trust AI interactions
AI development shifts toward context-aware empathetic responses, rather than blanket empathetic programming.
This deepens user trust and acceptance of AI in sensitive domains, leading to broader integration.
New ethical guidelines and regulatory frameworks emerge, centered on the 'appropriateness' and 'signal cost' of AI behavior, potentially influencing future AI design principles globally.
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Read at arXiv cs.AI