Rethinking Intelligence: An Interdisciplinary Framework for AI Research

Abstract

The pursuit of artificial intelligence (AI) has historically been fragmented across multiple domains such as computer science, cognitive psychology, neuroscience, philosophy, and linguistics, each contributing distinct perspectives and methodologies. However, as AI systems grow increasingly complex and integrated into the fabric of modern society, the need for a comprehensive and unified framework for understanding and advancing intelligence has become critical. This paper proposes an interdisciplinary approach to AI research that draws from both the empirical and conceptual contributions of various scientific and humanistic disciplines. By rethinking intelligence not merely as computation but as an emergent phenomenon influenced by context, embodiment, learning, and social interaction, we can foster a more nuanced and robust path for AI development. The discussion centers on integrating theoretical models with empirical data, emphasizing the necessity for ethical design, cognitive plausibility, and long-term alignment with human values. This framework is designed to support a more cohesive, resilient, and inclusive trajectory for future AI systems.