From explanations to human-AI co-evolution: charting trajectories towards future user-centric AI

Abstract

This paper explores the evolving landscape of User-Centric Artificial Intelligence, particularly in light of the challenges posed by systems that are powerful but not fully transparent or comprehensible to their users. Despite advances in AI, significant gaps remain in aligning system actions with user understanding, prompting a reevaluation of what “user-centric” really means. We argue that current XAI efforts are often too much focused on system developers rather than end users, and fail to address the comprehensibility of the explanations provided. Instead, we propose a broader, more dynamic conceptualization of human-AI interaction that emphasizes the need for AI not only to explain, but also to co-create and cognitively resonate with users. We examine the evolution of a communication-centric paradigm of human-AI interaction, underscoring the need for AI systems to enhance rather than mimic human interactions. We argue for a shift toward more meaningful and adaptive exchanges in which AI’s role is understood as facilitative rather than autonomous. Finally, we outline how future UCAI may leverage AI’s growing capabilities to foster a genuine co-evolution of human and machine intelligence, while ensuring that such interactions remain grounded in ethical and user-centered principles.

Keywords

• user-centric ai
• explainable ai
• transmodal interaction
• human-ai co-evolution