This paper offers guidance on employing open and creative methods for co-designing critical data and artificial intelligence (AI) literacy spaces and learning activities, rooted in the principles of Data Justice. Through innovative approaches, we aim to enhance participation in learning, research and policymaking, fostering a comprehensive understanding of the impact of data and AI whilst promoting inclusivity in critical data and AI literacy. By reflecting on the Higher Education (HE) context, we advocate for active participation and co-creation within data ecosystems, amplifying the voices of educators and learners. Our methodology employs a triangulation model: initially, we conduct interpretative analyses of literature to gauge best practices for curriculum development in HE; then, we examine frameworks in data justice and ethics to identify principles and skills applicable to undergraduate, postgraduate and academic development programs; finally, we explore proposals for critical, creative, ethical, open and innovative ideas for educators to integrate data and AI into their practice.