Beyond Chat: A Design Strategy for Enhancing Alignment Between User Requirements and AI Support in Online Decision-Making

Human-AI collaboration has demonstrated unique potential in various decision-making scenarios. However, the dynamic and personalized nature of online decision-making (e.g., shopping, trip planning) poses challenges to achieving alignment between AI support and user requirements. To address these challenges, we took online shopping as a representative scenario and conducted experience prototyping to explore human-AI collaboration in decision-making tasks. It revealed a dynamic transition in user requirements from ambiguity to clarity, while limited transparency and decision control hindered communication efficiency. Building on this, we formulated a design strategy comprising 10 AI actions that dynamically contribute to the human-AI interaction loop, aiming to achieve alignment between AI support and user requirements. We implemented this strategy in ContrXAI, an LLM-powered mixed-initiative system, and evaluated it as a technology probe. Findings demonstrated that ContrXAI effectively instantiated the design strategy, enhancing human-AI alignment and enriching the collaborative decision-making experience. We also identified typical user interaction patterns with ContrXAI and highlighted their expectations for AI collaborators.