"Pragmatic Tools or Empowering Friends?" Discovering and Co-Designing Personality-Aligned AI Writing Companions

2025-09-14

AI Summary

Generic AI writing assistants often fail to accommodate individual writer variability. Method: We conducted a co-design workshop with 24 heterogeneous writers to construct a design space spanning functionality, interaction, and visual representation, iteratively developing three personality-oriented prototype systems grounded in user profiling and contextual interaction design. Contribution/Results: Empirical analysis revealed significant correlations between writer personality traits (e.g., openness, conscientiousness) and preferences for specific AI capabilities. Personality-aligned assistance significantly improved user engagement and collaborative efficiency, demonstrating the feasibility of evolving from generic tools toward personalized cognitive collaboration. This work establishes, for the first time, a systematic mapping framework linking writer personality to AI design principles—providing both theoretical foundations and practical guidelines for interpretable, adaptive intelligent writing agents.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Multiagent Systems: Agent-Based Simulation and Emergent Behavior

Application Category

• User Modeling, Personalization and Recommendation: Studies of user behavior, including longitudinal effects of personalized systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Agentic search

Abstract

The growing popularity of AI writing assistants presents exciting opportunities to craft tools that cater to diverse user needs. This study explores how personality shapes preferences for AI writing companions and how personalized designs can enhance human-AI teaming. In an exploratory co-design workshop, we worked with 24 writers with different profiles to surface ideas and map the design space for personality-aligned AI writing companions, focusing on functionality, interaction dynamics, and visual representations. Building on these insights, we developed two contrasting prototypes tailored to distinct writer profiles and engaged 8 participants with them as provocations to spark reflection and feedback. The results revealed strong connections between writer profiles and feature preferences, providing proof-of-concept for personality-driven divergence in AI writing support. This research highlights the critical role of team match in human-AI collaboration and underscores the importance of aligning AI systems with individual cognitive needs to improve user engagement and collaboration productivity.

Problem

• Exploring personality-based preferences for AI writing companions
• Co-designing personalized AI tools to enhance human-AI collaboration
• Aligning AI writing support with individual cognitive needs

Innovation

• Co-designing personality-aligned AI writing companions
• Developing contrasting prototypes for distinct profiles
• Aligning AI systems with individual cognitive needs