This project explores the dynamic relationship between human individuality and cultural heritage through the innovative use of digital tools, centred on the theme of “Ambiguity.” By employing virtual reality (VR) and machine learning (ML), it transforms cultural gestures into architectural elements, allowing participants to perform these gestures at a 1:1 scale in VR. The gestures are captured as 3D meshes, which are then interpolated across various body dimensions and gestural typologies using a 3D DCGAN, creating a diverse array of architectural fragments. This process fosters a novel form of co-authorship, blending human input with algorithms.The resulting structures are organised using SOMs and positioned through Python scripts, aligning the gestural meshes according to their spatial and temporal contexts. These architectural elements form community spaces such as playgrounds, café hubs and performance areas, reflecting the unique rhythms and dimensions of their users. This approach challenges the traditional notion of architecture as static, proposing instead that buildings can be dynamic, evolving expressions of the communities they serve.The project also delves into the ambiguity of authorship, as the integration of VR and ML creates a blurred line between human and machine contributions. It raises questions about the true ‘author’ of the design, as personal gestures are algorithmically transformed into architectural elements, blending individual expressions with community representation. Moreover, the research examines the complexities of cultural representation, where digitising and modifying cultural gestures through AI both preserves and transforms the original heritage, challenging conventional ideas of authenticity. It addresses the challenges of using data-driven models to represent diverse populations, emphasising the need to balance statistical generalisations with the unique realities of individual experiences.