Flourishing cultural diversity in AI

Artificial intelligence is important for innovation yet fails to encapsulate the global mosaic of human culture and cognition. The rapid loss of ancient cultural practices and skills underscores the urgency of addressing this gap in AI systems. We advocate for AI training that reflects and protects the full spectrum of human diversity and propose interdisciplinary approaches to achieve this. Our review highlights insights from studies in non-Western societies, with a specific focus on indigenous hunter-gatherer groups and the foraging context, to pave the way for transdisciplinary research. We propose an inclusive examination of human cognition at both the individual and collective levels, where individuals are viewed within their social networks. Our proposal emphasizes a bi-directional approach: integrating diversity into AI models to unlock their full potential, ensuring these technologies reflect the breadth of human cultural products, and utilizing machine learning tools to deepen our understanding of human cognitive processes across various ecological contexts.