Challenges arise in applying existing design rules to AI companions
Assessing the Applicability of Existing Design Recommendations to AI Companion Design: A Multi-Method Study
Human-Computer InteractionArtificial Intelligence
Summary
AI companions are conversational programs meant to create emotional bonds with people over time. Designing these AI companions is tricky because existing design advice from related areas doesn’t always fit well. The authors studied how current guidelines apply to AI companions by reviewing literature, working with designers, and evaluating expert feedback. They found that ethical and user experience issues are closely linked and depend heavily on context. This means new or adapted design principles are needed specifically for AI companions.
What this means in practice
- •For ai product designers: Use identified principle areas to navigate ethical and UX tensions when creating AI companions that foster emotional connection.
- •For user experience teams: Adapt existing AI design guidelines contextually to improve design decisions for conversational agents focused on companionship.
Authors
Soobin Cho, Deveshi Modi, Divya Mavinkurve, Jieqiong Ding, Mark Zachry
Abstract
With the rapid proliferation of large language model (LLM)-based systems, AI companions have emerged as conversational agents designed to cultivate emotional connection rather than primarily to support humans in instrumental tasks. Because engagement with AI companions involves relational, emotional, and potentially long-term interactions, their design is consequential. Prior work has offered guidance for designing trustworthy and relational AI systems and has begun to examine design for AI companionship. However, while such work provides insights into possible design solutions, less is known about what makes AI companion design difficult as a design problem. To examine this challenge, we assessed the applicability of existing design recommendations from adjacent domains in the context of AI companion design. Our multi-method investigation unfolded across four phases: literature review, practitioner co-analysis, internal heuristic evaluation, and external expert assessment. Throughout this process, we synthesized nine design principle areas that surfaced tensions in the applicability of existing recommendations to AI companion design. Our findings show that ethical and UX-oriented considerations are deeply intertwined and often require context-sensitive application. We document a systematic, multi-method problem analysis that uses these principle areas as an analytic artifact to examine why existing recommendations cannot be directly transferred to AI companion contexts.