Algorithmic Intimacy: AI Co-authorship and Student Designer identity in Architectural Education

This study investigates the psychological dimensions of Human-AI collaboration in architectural education through a retrospective analysis of pedagogical documentation and student work from a second-year architectural design studio. The concept of algorithmic intimacy is introduced to characterise the emotional and collaborative bonds students develop with Artificial Intelligence (AI) agents, specifically examining how these relationships influence authorship attribution and professional identity formation. The research identifies four key themes: the prompt as a medium of personal expression, student ambivalence regarding authorship during critique defences, the tension between efficiency and deep comprehension in the design thinking process, and the projection of personal identity onto AI-generated outputs. While this inverse, concept-first pedagogical model facilitates rapid conceptual exploration, it presents challenges that may constrain students’ creative agency. Consequently, this study proposes a pedagogy of ‘algorithmic reflexivity’ to assist students in navigating authorship, agency, and ethical practice in an AI-augmented discipline. By shifting the analytical focus from the final design outcomes to the Human-AI interaction itself, this study offers critical strategies for integrating generative technologies into creative education.