The field of AI research is moving towards a greater emphasis on understanding and mitigating cultural bias and value misalignment in AI systems. Recent studies have highlighted the importance of considering the cultural context in which AI systems are deployed, and the need for more robust approaches to mitigate biases and improve cultural representativeness. The development of value-aware AI systems that can learn and represent the value systems of different societies is a key area of research. Noteworthy papers in this area include: An Empirical Investigation of Gender Stereotype Representation in Large Language Models, which examines the perpetuation of stereotypes in LLMs. Do Large Language Models Understand Morality Across Cultures, which investigates the extent to which LLMs capture cross-cultural differences and similarities in moral perspectives.