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Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 18th Apr 2026, 04:06:12pm CEST

Agenda Overview

Session

D224: HUMAN–AI CO-CREATION IN DESIGN PRACTICE

Time:

Tuesday, 19/May/2026:

10:15am - 11:15am

Session Chair: John Gero, Drexel University, United States of America

Location: Conference Hall Orlando 2

Presentations

AI as creative partner: exploring perceived roles in human-AI co-creation

Susanne Dreyer, Chris McTeague, Katja Thoring

Technical University of Munich, Germany

Generative AI (GenAI) tools are getting more and more integrated into creative workflows, evolving from assistants to collaborators, and reshaping human-AI interactions in the creative process. To better understand the human side of this co-creation, an interview study was conducted with 19 architecture students participating in a GenAI-supported design futuring course. The study identified 18 roles humans and AI can take during co-creation, along with tool-specific variations and insights into emotional dynamics, creative experiences, perceived agency, and control during the design process.

Understanding designers’ experiences with generative AI through user interaction pattern analysis

Charlie Ranscombe¹, Linus Tan¹, Nadia Anam¹, James Gopsill²

¹Swinburne University of Technology, Australia; ²University of Bristol, United Kingdom

This study examines how designers’ experiences with text-to-image GenAI relate to their interaction patterns during a design hackathon. Survey data and two contrasting cases show that positive experiences align with shifting prompts and broader command use as designers move from exploration to refinement, while negative experiences correlate with fixed prompting and limited variations. The study demonstrates how interaction data can inform adaptive GenAI support across design phases, offering opportunities to enhance both practice and tool development.

Motivation and post-design evaluations of AI usage behind AI-assisted design

Yuan Yin¹, Haoyu Zuo¹, Liuqing Chen², Pan Wang³, Peter Childs¹

¹Imperial College London, United Kingdom; ²College of Computer Science and Technology, Zhejiang University, China; ³Faculty of Industrial Design Engineering, Delft University of Technology, The Netherlands

This study aimed to detect designers’ motivations (Personal Identity, Conformity, Life Efficiency, and Information) in using Generative AI in AI-assisted design and how these motivations related to post-design evaluations of AI (Attitudes, Satisfaction, and Continuance Intention). The results showed that personal identity, conformity, and efficiency motives can predict attitudes and satisfaction for the use of Generative AI in AI-assisted design. No motivation indicated in the study can predict continuance intention, which suggests that long-term AI usage depends on factors beyond motivation.

Artificial co-intelligence in multi-domain platform development: what is now and what is next?

Massimo Panarotto, Gaetano Cascini

Politecnico di Milano, Italy

This paper reviews 89 studies on AI in product platform design, further focusing on 21 multi-domain contributions. The dominant archetype is AI as a Tool × Method × Solution Proposal, with AI mainly used for automation and optimization. Collaborative roles remain rare, especially in requirements and architecture phases. Robust evaluation of AI benefits is largely missing, revealing an automation-centric paradigm and key gaps for co-intelligent, cross-domain platform development.