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Lookup NU author(s): Marci Ma, Dr Lei ShiORCiD, Jiacheng Cheng, Professor Dave KirkORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Generative AI offers scalable engagement with digital cultural heritage, yet current workflows rely on complex prompts, creating an interaction bottleneck for non-expert audiences. To address this gap, we introduce MoodCurator, a web-based design probe enabling low-friction, implicit affective steering for curatorial storytelling. The system replaces prompt engineering with a three-channel loop: audiences (1) select a colour palette to suggest narrative tone; (2) curate artworks to ground the narrative in visual content; and (3) choose an interpretive voice to constrain rhetorical stance. A mixed-methods study (𝑁 = 64) demonstrated encouraging patterns of perceived usability and user agency. A follow-up think-aloud study (𝑁 = 10) surfaced recurring cases of interpretive mismatch in this English-language deployment. Contributions include: (1) a legible steering paradigm for AI-supported cultural interpretation; (2) exploratory empirical evidence on usability, agency, and narrative resonance; and (3) preliminary design implications for more explicit and contestable framing controls in future systems.
Author(s): Ma M, Shi L, Li H, Cheng C, Kirk D
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: ACM Designing Interactive Systems
Year of Conference: 2026
Pages: 4709-4727
Online publication date: 12/06/2026
Acceptance date: 18/03/2026
Date deposited: 28/05/2026
ISSN: 2160-6455
Publisher: Springer
URL: https://doi.org/10.1145/3800645.3812861
DOI: 10.1145/3800645.3812861
