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Algorithmic Intimacy: AI Co-authorship and Student Designer identity in Architectural Education
Abstract
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.
Keywords
Ethical Statement
This study qualified for exemption from Institutional Review Board (IRB) review under Category 1 [45 CFR 46.104(d)(1)] as it involved the retrospective analysis of existing pedagogical documentation (teaching archives, student work, and reflexive teaching notes) collected as part of normal educational practices.
References
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- Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101
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Details
Primary Language
English
Subjects
Instructional Technologies, Architecture (Other)
Journal Section
Research Article
Authors
Publication Date
January 12, 2026
Submission Date
November 12, 2025
Acceptance Date
December 27, 2025
Published in Issue
Year 2025 Volume: 6 Number: 2
APA
Azhar, J. (2026). Algorithmic Intimacy: AI Co-authorship and Student Designer identity in Architectural Education. International Journal of Mardin Studies, 6(2), 51-79. https://doi.org/10.63046/ijms.1822048
AMA
1.Azhar J. Algorithmic Intimacy: AI Co-authorship and Student Designer identity in Architectural Education. IJMS. 2026;6(2):51-79. doi:10.63046/ijms.1822048
Chicago
Azhar, Jasim. 2026. “Algorithmic Intimacy: AI Co-Authorship and Student Designer Identity in Architectural Education”. International Journal of Mardin Studies 6 (2): 51-79. https://doi.org/10.63046/ijms.1822048.
EndNote
Azhar J (January 1, 2026) Algorithmic Intimacy: AI Co-authorship and Student Designer identity in Architectural Education. International Journal of Mardin Studies 6 2 51–79.
IEEE
[1]J. Azhar, “Algorithmic Intimacy: AI Co-authorship and Student Designer identity in Architectural Education”, IJMS, vol. 6, no. 2, pp. 51–79, Jan. 2026, doi: 10.63046/ijms.1822048.
ISNAD
Azhar, Jasim. “Algorithmic Intimacy: AI Co-Authorship and Student Designer Identity in Architectural Education”. International Journal of Mardin Studies 6/2 (January 1, 2026): 51-79. https://doi.org/10.63046/ijms.1822048.
JAMA
1.Azhar J. Algorithmic Intimacy: AI Co-authorship and Student Designer identity in Architectural Education. IJMS. 2026;6:51–79.
MLA
Azhar, Jasim. “Algorithmic Intimacy: AI Co-Authorship and Student Designer Identity in Architectural Education”. International Journal of Mardin Studies, vol. 6, no. 2, Jan. 2026, pp. 51-79, doi:10.63046/ijms.1822048.
Vancouver
1.Jasim Azhar. Algorithmic Intimacy: AI Co-authorship and Student Designer identity in Architectural Education. IJMS. 2026 Jan. 1;6(2):51-79. doi:10.63046/ijms.1822048