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Automatic text summarization systems commonly involve humans for preparingdata or evaluating model performance, yet, there lacks a systematicunderstanding of humans' roles, experience, and needs when interacting with orbeing assisted by AI. From a human-centered perspective, we map the designopportunities and considerations for human-AI interaction in text summarizationand broader text generation tasks. We first conducted a systematic literaturereview of 70 papers, developing a taxonomy of five interactions in AI-assistedtext generation and relevant design dimensions. We designed text summarizationprototypes for each interaction. We then interviewed 16 users, aided by theprototypes, to understand their expectations, experience, and needs regardingefficiency, control, and trust with AI in text summarization and propose designconsiderations accordingly.

Mapping the Design Space of Human-AI Interaction in Text Summarization