The field of cognitive science is undergoing a profound transformation as artificial intelligence (AI) becomes embedded into daily life, acting not only as a tool but increasingly as a cognitive collaborator. We use the term AI broadly to include established cognitive architectures and recent high-profile systems (e.g., GPT, Gemini, Copilot). This shift poses pressing questions: how does human cognition adapt when people work alongside, delegate tasks to, or learn from AI systems? While recent studies have begun to reveal changes in memory, problem-solving, attention, and reasoning when AI is present, the mechanisms and long-term consequences of these shifts remain uncertain. Current research highlights variations in trust calibration, metacognitive monitoring, and cognitive offloading when interacting with intelligent machines, yet foundational questions about cross-cultural patterns, developmental trajectories, and group-level dynamics are still only partially explored. There is growing recognition that AI influences not just individual cognitive processes, but also the broader ecology of minds, including social interaction, communication, and collaboration within diverse cultural and environmental contexts. To advance knowledge, cognitive science needs rigorous theories and empirical evidence on how human-AI interactions are reshaping the core mechanisms and boundaries of cognition.

This Research Topic aims to advance the understanding of human cognition in the age of AI, with a focus on the mechanisms underlying cognitive processes as they are transformed by our interactions with artificial agents across contexts and cultures. The objectives are to uncover how core cognitive systems (attention, learning, memory, language, reasoning, and metacognition) are altered, extended, or reorganized. We seek answers to questions such as: What new forms of cognitive collaboration emerge from human-AI teaming? How do trust and reliance develop and adjust in the presence of adaptive, machine-based partners? In what ways do developmental, cultural, and task-specific factors modulate the impact of AI on cognitive function? By engaging with these issues, this initiative aims to encourage submissions that contribute robust theoretical, experimental, or cross-cultural insights into the evolving landscape of human cognition.

To gather further insights into the boundaries and limitations of core cognitive processes as they intersect with artificial agents and environments, we welcome articles addressing, but not limited to, the following themes:

- Cognitive impacts of human-computer and human-AI collaboration
- The utility of commercially available AI systems on our undertanding of human cognition
- Cognitive(-like) behavior in groups of interacting agents (human-human-AI teams)
- Developmental and lifespan changes in cognition with persistent AI exposure
- Cross-cultural variation in cognitive adaptation to AI-mediated environments
- Theoretical and historical contributions clarifying the legacy and evolution of cognitive science with respect to AI
- Mechanisms of trust, metacognitive calibration, and cognitive control in AI-supported tasks
- The assumptions about cognition made by particular types of computational cognitive models
- Cognitive architectures as models of cognition and their use of attention, learning, memory, reasoning, or metacognition

We encourage empirical reports, computational studies, theory-driven papers grounded in behavioral or formal data, and cross-cultural or lifespan research. Submissions should center on cognitive mechanisms and their implications for human cognition in the context of AI. Manuscripts focused solely on clinical interventions, occupational stress, or elderly care are outside of scope, except where they inform core cognitive processes or mechanisms. Philosophical discussions are welcomed when empirically anchored and relevant to cognitive science audiences.

Are you interested in contributing a manuscript to this Research Topic?

The Future of Cognitive Science in the Age of Artificial Agents