Human-Centered AI Metacognition: Development and Validation of a Scale for Preserving Cognitive Autonomy in Human–AI Collaboration

The rapid advancement of generative artificial intelligence (AI) is transforming human cognitive activities and creating a growing need to preserve cognitive autonomy in human–AI interactions. Although recent research has examined metacognition in AI-mediated environments, existing work has primarily focused on improving AI use and human–AI collaboration, with less attention to how individuals regulate the role and extent of AI involvement in their own cognitive activities. To address this gap, the present study introduced Human-Centered AI Metacognition (HC-AIM), defined as the capacity to recognize AI capabilities and limitations, monitor AI-generated information, and regulate the extent to which AI participates in one’s own cognitive activities while maintaining cognitive autonomy. Across three studies, we developed the Chinese version of the Human-Centered AI Metacognition Scale (HC-AIMS) and conducted an initial psychometric evaluation. Study 1 examined the scale structure using exploratory factor analysis and supported a predominantly unidimensional structure with good internal consistency. Study 2 examined this structure using confirmatory factor analysis and provided evidence of its convergent validity through its association with general metacognition. Study 3 further replicated the scale structure and internal consistency and examined its relationships with AI literacy, collaborative AI metacognition, and autonomous cognitive offloading. HC-AIM was positively associated with all three constructs. Comparisons of theoretically specified factor models provided preliminary evidence of empirical distinguishability between HC-AIM and both AI literacy and collaborative AI metacognition, despite substantial correlations with these constructs. HC-AIM was also positively associated with autonomous cognitive offloading, providing complementary self-reported criterion-related evidence for its validity. Taken together, the findings suggest that HC-AIM represents a contextualized, human-centered form of metacognitive regulation that is closely related to broader metacognitive and AI-related competencies while specifically emphasizing the regulation of AI participation in human cognition. The Chinese version of the HC-AIMS provides a theoretically grounded starting point for investigating human cognition and cognitive autonomy in AI-mediated environments.