TY - CHAP
T1 - Unlearning to Learn: AI as Catalyst for Epistemological Transformation in Architectural Education
AU - Lombardi, Davide
AU - Albano, Silvia
PY - 2026/3
Y1 - 2026/3
N2 - This chapter examines how artificial intelligence is fundamentally reshaping architectural education, necessitating a profound process of "unlearning" established pedagogical assumptions, cognitive practices, and curricular structures. Drawing on a critical synthesis of recent scholarship (2020–2026) and complementary theoretical frameworks, this chapter argues that AI's integration into architectural pedagogy represents not merely a technological upgrade but an epistemological transformation that challenges core assumptions about authorship, creativity, design cognition, and the nature of architectural knowledge itself. Through examination of concrete case studies, empirical evidence, and critical perspectives, this chapter discusses that effective AI integration requires educators and students to unlearn instrumental views of technology, design processes frameworks (e.g., the RIBA Plan of Work), and individualistic notions of authorship while learning to engage AI as a co-creative partner that provokes exploration rather than delivers optimization. The chapter advances a theoretical "Unlearning Framework" that identifies specific assumptions to discard at epistemological, cognitive, and pedagogical levels, and synthesises insights from scholarship and pedagogical exemplars to suggest that AI’s transformative potential depends critically on how it is pedagogically framed, as design partner rather than design assistant, as conversational collaborator rather than automated tool, and as catalyst for critical inquiry rather than shortcut to efficiency. The study highlights both opportunities for enhanced creativity, accessibility, and exploratory learning, and significant risks including cognitive offloading, aesthetic homogenisation, diminished human agency, and the erosion of foundational design thinking skills. This contribution aims to be a theoretical reflection grounded in a critical synthesis of recent scholarship and selected pedagogical exemplars (2020–2026); its input is the proposal of an ‘Unlearning Framework’ as a conceptual scaffold for future empirical testing rather than a validated instrument.
AB - This chapter examines how artificial intelligence is fundamentally reshaping architectural education, necessitating a profound process of "unlearning" established pedagogical assumptions, cognitive practices, and curricular structures. Drawing on a critical synthesis of recent scholarship (2020–2026) and complementary theoretical frameworks, this chapter argues that AI's integration into architectural pedagogy represents not merely a technological upgrade but an epistemological transformation that challenges core assumptions about authorship, creativity, design cognition, and the nature of architectural knowledge itself. Through examination of concrete case studies, empirical evidence, and critical perspectives, this chapter discusses that effective AI integration requires educators and students to unlearn instrumental views of technology, design processes frameworks (e.g., the RIBA Plan of Work), and individualistic notions of authorship while learning to engage AI as a co-creative partner that provokes exploration rather than delivers optimization. The chapter advances a theoretical "Unlearning Framework" that identifies specific assumptions to discard at epistemological, cognitive, and pedagogical levels, and synthesises insights from scholarship and pedagogical exemplars to suggest that AI’s transformative potential depends critically on how it is pedagogically framed, as design partner rather than design assistant, as conversational collaborator rather than automated tool, and as catalyst for critical inquiry rather than shortcut to efficiency. The study highlights both opportunities for enhanced creativity, accessibility, and exploratory learning, and significant risks including cognitive offloading, aesthetic homogenisation, diminished human agency, and the erosion of foundational design thinking skills. This contribution aims to be a theoretical reflection grounded in a critical synthesis of recent scholarship and selected pedagogical exemplars (2020–2026); its input is the proposal of an ‘Unlearning Framework’ as a conceptual scaffold for future empirical testing rather than a validated instrument.
M3 - Chapter
T3 - AI for Design, the Built Environment and Sustainability
BT - The Future of Architectural Domain - AI an Existential threat or Opportunity?
PB - Springer Nature Switzerland
ER -