Interaction-Centered Intelligence: Toward Interaction as the Primary Unit of Analysis in Co-Creative AI and Human-AI Systems
arXiv:2606.00807v1 Announce Type: new Abstract: Traditional artificial intelligence has largely conceptualized intelligence as isolated computation occurring within bounded agents. Across classical AI, machine learning, and many generative systems, the dominant unit of analysis remains the individual model or autonomous system evaluated through outputs, benchmarks, prediction accuracy, or optimization performance. While these approaches have produced major advances, they often under-theorize the role of interaction in the emergence of intelligence, creativity, meaning, and adaptive behavior. T
This publication represents an academic shift in AI conceptualization, emerging as current AI models demonstrate limitations in complex, interactive environments.
A strategic reader should care as a re-evaluation of intelligence to include interaction fundamentally changes how AI systems will be designed, evaluated, and integrated into human environments.
The primary unit of analysis for AI is shifting from isolated computation to interaction, emphasizing co-creativity and adaptive behavior in human-AI systems.
- · AI ethicists
- · Human-computer interaction researchers
- · Developers of collaborative AI systems
- · Companies building interactive AI products
- · Traditional AI benchmarking methodologies
- · AI companies focused solely on isolated model performance
- · Those resistant to interdisciplinary AI research
AI research will increasingly focus on multi-agent interaction and dynamic co-creation rather than static benchmarks.
New metrics and architectures for AI will emerge to evaluate interactive capabilities and adaptive behaviors with humans.
The development of highly integrated, context-aware AI systems will accelerate, leading to novel forms of human-AI collaboration in various industries.
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Read at arXiv cs.AI