Cognitive bias in generative AI influences religious education - Jing Zhang; Wenlong Song; Yang Liu (Scientific Reports)
Abstract This study explores the transformative role of generative artificial intelligence (AI) in shaping religious cognition, with particular emphasis on its implications for religious education. By examining the biases inherent in AI-generated content, this research highlights how these biases influence user perceptions and interactions with diverse religious teachings. Through experimental frameworks and pre/post-interaction evaluations, the study reveals that generative AI not only reflects but amplifies cognitive biases, affecting users’ understanding of religious doctrines and cultural diversity. The findings underscore the potential of generative AI to act as a double-edged sword in religious education: enhancing personalized learning and cross-cultural understanding while risking the reinforcement of prejudice. These insights call for ethical guidelines and oversight mechanisms in deploying generative AI within religious contexts. This research contributes to the growing discourse on AI ethics and its pivotal role in shaping inclusive and unbiased religious education in the digital era.