  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.
