  Automatic text summarization systems commonly involve humans for preparing
data or evaluating model performance, yet, there lacks a systematic
understanding of humans' roles, experience, and needs when interacting with or
being assisted by AI. From a human-centered perspective, we map the design
opportunities and considerations for human-AI interaction in text summarization
and broader text generation tasks. We first conducted a systematic literature
review of 70 papers, developing a taxonomy of five interactions in AI-assisted
text generation and relevant design dimensions. We designed text summarization
prototypes for each interaction. We then interviewed 16 users, aided by the
prototypes, to understand their expectations, experience, and needs regarding
efficiency, control, and trust with AI in text summarization and propose design
considerations accordingly.
