The data dance: choreographing seamless partnerships between humans, data, and GenAI

The accelerated development of generative artificial intelligence (GenAI) has initiated a transformative period in human–computer interaction, providing a wealth of unprecedented insights and concomitant complexities. This article examines the potential for the symbiotic integration of GenAI with Human–Data Interaction (HDI) principles, proposing a novel approach to the creation of more transparent, controllable, and user-centric AI systems. This article examines the ways in which the core principles of HDI—namely legibility, agency, and negotiability—can be systematically applied to GenAI systems across a range of domains. A comprehensive literature review and case studies demonstrate how this integration can address critical issues in AI development, including interpretability, user trust, and ethical alignment. This article introduces the Dynamic Neural Architecture for Interpretable and Customizable AI (DYNAMIC) approach, which represents a paradigm shift in the design of GenAI systems. DYNAMIC incorporates adaptive neural topologies, interpretable modules, and meta-learning techniques, thereby creating AI systems that are capable of dynamically adjusting to user needs and contexts while maintaining transparency and ethical awareness. Moreover, we put forth the Creative Cross-Domain Synergy (CDCS) approach, which employs HDI-enhanced GenAI to enable multimodal and cross-domain creative collaborations. The objective of this approach is to facilitate the formation of novel forms of partnership between humans and AI in a range of fields, including artistic creation and scientific research. Our research demonstrates the potential of HDI-GenAI integration to facilitate broader access to advanced AI technologies, mitigate ethical risks, and foster more meaningful human–AI collaborations. In conclusion, we present a research agenda that addresses key challenges in scalability, real-time interactivity, and ethical governance. We call for interdisciplinary efforts to realize the full potential of HDI-enhanced GenAI systems. This work contributes to the growing body of research on human-centred AI, offering a roadmap for developing GenAI systems that not only augment human capabilities but also align closely with human values and societal needs.