The Case for AI Fluency in Human AI Collaboration
AI fluency is defined as a set of interacting practical skills, knowledge, and values enabling interaction with AI systems that is effective, efficient, ethical, and safe, distinct from mere prompt engineering or technical expertise. The theory identifies three modes of human-AI engagement — automation (AI executes a defined task per explicit instructions), augmentation (AI collaborates as a creative/problem-solving partner), and agency (AI operates independently based on established knowledge and behavior patterns rather than specific directives) — situating this within the domain of human-AI collaboration theory, where AI is conceptualized not merely as a tool but potentially as a medium, partner, or co-creator depending on the mode of engagement.
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AI fluency is defined as a set of interacting practical skills, knowledge, and values enabling interaction with AI systems that is effective, efficient, ethical, and safe, distinct from mere prompt engineering or technical expertise. The theory identifies three modes of human-AI engagement — automation (AI executes a defined task per explicit instructions), augmentation (AI collaborates as a creative/problem-solving partner), and agency (AI operates independently based on established knowledge and behavior patterns rather than specific directives) — situating this within the domain of human-AI collaboration theory, where AI is conceptualized not merely as a tool but potentially as a medium, partner, or co-creator depending on the mode of engagement.
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