# Bridging Minds and Machines: Toward an Integration of AI and Cognitive Science

## TL;DR

This paper reviews the reciprocal relationship between AI and Cognitive Science, emphasizing the need to integrate cognitive theories into AI development to better understand the human mind and improve AI systems.

## Contribution

It synthesizes interdisciplinary insights, highlighting the importance of embedding cognitive frameworks, embodiment, culture, and ethics into AI research for future advancements.

## Key findings

- AI progress is mainly focused on task performance.
- Cognitive foundations of AI are conceptually fragmented.
- Future directions include aligning AI with cognitive models and ethics.

## Abstract

Cognitive Science has profoundly shaped disciplines such as Artificial Intelligence (AI), Philosophy, Psychology, Neuroscience, Linguistics, and Culture. Many breakthroughs in AI trace their roots to cognitive theories, while AI itself has become an indispensable tool for advancing cognitive research. This reciprocal relationship motivates a comprehensive review of the intersections between AI and Cognitive Science. By synthesizing key contributions from both perspectives, we observe that AI progress has largely emphasized practical task performance, whereas its cognitive foundations remain conceptually fragmented. We argue that the future of AI within Cognitive Science lies not only in improving performance but also in constructing systems that deepen our understanding of the human mind. Promising directions include aligning AI behaviors with cognitive frameworks, situating AI in embodiment and culture, developing personalized cognitive models, and rethinking AI ethics through cognitive co-evaluation.