The development of AI and machine learning tools such as ChatGPT has raised concerns about authorship, creativity, bias, and the role of AI in the production of knowledge. In the field of art and design, ‘text-to-image’ AI tools have the potential to save time and explore new ideas, but they also raise concerns about the devaluing of creative and critical thinking skills. A key feature of this "algorithmic anxiety" is the fundamental unknowability of AI deep learning models which demands a radically alternative dialogic encounter and an activity of ‘finding out what the machine actually knows’. This articulation offers the potential of approaching human-computer interfaces with a sense of openness and curiosity and a non/human collaboration.

This paper explores the potential of AI imaging tools, specifically 'text-to-image' processes, for interior design pedagogy and practice. The research will investigate where and how these tools should be located in a design process, identify benefits and limitations of their use, and develop strategies for engaging with these tools in an ethical manner. The research aims to identify the potential of non/human collaboration with these tools in an ethical manner as contextualised under a posthuman condition, and explore strategies that are supportive to collaborative arrangements between designer, machine, and other stakeholders. The outcome of the research will inform pedagogical frameworks and digital work practices for interior design.

The research presented in this paper is interim findings from a series of workshops conducted in partnership with interior design students, supported with discussions with researchers and industry experts. The research is contextualised under the wider frame of research on the 'interior-as-image' and the role of the image and imaging of the interior under post-digital experience.