Technological progress has persistently shaped the dynamics of human-machine interactions in task execution. In response to the advancements in Generative AI, this paper outlines a detailed study plan that investigates various human-AI interaction modalities across a range of tasks, characterized by differing levels of creativity and complexity. This exploration aims to inform and contribute to the development of Graphical User Interfaces (GUIs) that effectively integrate with and enhance the capabilities of Generative AI systems. The study comprises three parts: exploring fixed-scope tasks through news headline generation, delving into atomic creative tasks with analogy generation, and investigating complex tasks via data visualization. Future work aims to extend this exploration to linearize complex data analysis results into narratives understandable to a broader audience, thereby enhancing the interpretability of AI-generated content.

翻译：技术进步持续塑造着任务执行中人机交互的动态模式。针对生成式AI的最新进展，本文概述了一项详细的研究计划，系统考察了不同创造力与复杂性水平任务中的多种人机交互模式。该探索旨在为有效集成并增强生成式AI系统能力的图形用户界面开发提供参考与贡献。研究包含三个部分：通过新闻标题生成任务探索固定范围交互、通过类比生成任务深入原子化创意交互、以及通过数据可视化任务研究复杂交互。未来工作拟将此类探索延伸至将复杂数据分析结果线性转化为更广泛受众可理解的叙事，从而增强AI生成内容的可解释性。