Exploratory Responsiveness and Adaptive Rigidity under AI-Assisted Optimization

The paper presents a theoretical framework for understanding exploratory adaptation in AI-assisted optimization, highlighting how predictive assistance can influence adaptive responsiveness in cognitive and institutional systems. It introduces a dynamical model that explores the interplay between AI systems and exploratory engagement, revealing that under certain conditions, AI can lead to decreased adaptability and rigidity, while in other contexts, it can enhance exploratory capabilities. This research is significant for practitioners as it underscores the importance of institutional structures and interaction designs when integrating AI into adaptive systems, potentially guiding the development of more resilient AI applications.