Beyond Algorithmic Agency: A Comparative Inquiry into the Efficacy of Generative AI for Enhancing Divergent Thinking and Creative Exploration in Persona Construction

Authors

  • Lin Yong College of Engineering, Northeastern University, 02115, USA Author

Keywords:

Generative AI, Persona Construction, Creativity Support Index, Human-AI Collaboration, Design Fixation

Abstract

The rigorous integration of Generative Artificial Intelligence into design workflows necessitates a meticulous re-evaluation of how algorithmic tools reshape the ideation journey, particularly within the cognitively demanding task of persona construction. This research scrutinizes the creative support capacities of two distinct AI-assisted modalities—the prompt-driven FounderPal and the conversational InstantPersonas—by engaging design practitioners in a controlled experimental environment. Evaluated through the lens of the Creativity Support Index, the findings elucidate a nuanced landscape where AI significantly augments exploratory creativity while simultaneously revealing a discernible deficit in fostering user immersion and personalized expressiveness. Although statistical parity was observed in overall creativity scores, the conversational interface of InstantPersonas appeared to yield a heightened sense of result worthiness, suggesting that the iterative nature of human-AI dialogue may mitigate the risks of design fixation identified in previous studies. This study argues that the optimal role for AI lies not in autonomous generation but in serving as a structured catalyst across differentiated creative phases. Consequently, future AI architectures must prioritize transparency, traceability, and high editability to ensure human-in-the-loop agency over mere computational efficiency.

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Published

2026-03-04

Issue

Section

Research Articles

How to Cite

Beyond Algorithmic Agency: A Comparative Inquiry into the Efficacy of Generative AI for Enhancing Divergent Thinking and Creative Exploration in Persona Construction. (2026). International Journal of Computer Science and Engineering, 1(02), 35-39. https://iakjournals.org/index.php/iakj/article/view/14