Understanding involuntary thought and affect through big data and AI.

Involuntary and undirected cognitive processes, such as mind-wandering, task-unrelated thought, and spontaneous affective states, have gained significant attention in recent years. These internal states, which arise without deliberate intent, play essential roles in areas like education, mental health, and creativity but can be challenging to study due to their inherently covert nature. This special issue explores how artificial intelligence and large data sets can be leveraged to better understand these processes, offering new methods for measurement, theory development, and practical application. By integrating computational tools such as natural language processing and machine learning with cognitive theories, the contributions in this issue demonstrate how interdisciplinary approaches can uncover the dynamics of involuntary cognition and its impacts. We hope this collection inspires further research to expand the study and application of involuntary cognition.