Knowledge Base Repository
In addition to research papers, the Design Society is developing several valuable resources for those interested in the study of design. These include a repository of PhD theses, a library of case studies and transcripts of design activities, and an archive of our newsletters. Please note that these resources are accessible exclusively to Design Society members.
FROM FASCINATED TO SCARED: AFFECTIVE RESPONSES OF DESIGNERS USING GENERATIVE AI IN THE DESIGN PROCESS
Figoli, Fabio Antonio; Mattioli, Francesca; Rampino, Lucia
Type:
Year:
2025
Editor:
Bohemia, Erik; Buck, Lyndon; Grierson, Hilary
Author:
Series:
E&PDE
Institution:
Department of Design, Politecnico di Milano, Italy
Page(s):
211 - 216
DOI number:
ISBN:
3005-4753
ISSN:
978-1-912254-22-4
Abstract:
Generative Artificial Intelligence (genAI) is transforming professional design workflows, yet its affective impact on designers remains underexplored. This study investigates designers’ affective responses to genAI adoption in the design process, examining the associated underlying causes. Using a grounded theory approach, we conducted semi-structured interviews with fourteen designers who regularly engage with genAI. The collected data were qualitatively analysed through thematic coding, and the results were visualised to identify patterns between affective responses and their triggers. This process revealed genAI evoking affective responses in designers on two levels: on the emotional level, reactive and driven by immediate experiences during AI interaction, and the feeling level, reflective and primarily shaped by broader concerns about genAI’s long-term impact on professional identity and practice. The findings highlight a tension between genAI practical adoption and designers’ professional uncertainty, underscoring the need for design education to address affective awareness alongside technical proficiency. This approach not only equips designers for more resilient and informed engagement with AI-integrated practices but also enhances their ability to anticipate and design for end users’ affective responses to AI-infused systems.
Keywords:
