Human–AI Co-Production: Normative Challenges in Public Space Design

The integration of artificial intelligence (AI) in design disciplines marks a shift in design agency, from predominantly human-centered processes toward distributed forms of Human–AI co-production. This study conceptualizes Human–AI co-production as an interpretive construct and examines it through Jasanoff’s co-production framework. As AI becomes involved in multiple stages of design, it functions not merely as a passive tool but as an influential participant in shaping the built environment. Yet, the normative challenges emerging from Human–AI co-production in public space design remain insufficiently examined. Using an exploratory, qualitative, concept-oriented approach, this paper develops a framework-guided synthesis of sixteen normative challenges that are reconfigured when AI is introduced into public space design. These challenges are analyzed at two levels. At the interactional level, they are grouped into four themes—Invisibility and Exclusion, Imposition and Rigidity, Erosion and Displacement, and Distortion and Deception—and reinterpreted through Jasanoff’s four dimensions: identity, discourse, institutions, and representation. At the constitutive level, the analysis suggests that AI recursively embeds an algorithmic rationality across these dimensions, interpreted here as a closed-loop mechanism that reshapes the normative foundations of public space design. The authors find that Human–AI agency can be understood as shaping public space design and its normative challenges immanently, rather than as an external force acting upon it.