Designing Proactive Thought Partners for Writing
Read the original on arXiv AI →The Flow has not summarised this story yet — read it at arXiv AI.
The Flow has not summarised this story yet — read it at arXiv AI.
Writing involves diverse cognitive activities, from ideation to revision, and writers' needs vary across individuals and moments. Proactive AI promises to provide the right support at the right time,...
The paper proposes a proactive writing support system that infers users’ needs from their writing interactions, using Flower and Hayes’ cognitive process theory as a framework. By mapping six cognitive processes to 14 specific support types and associated interaction behaviors, the authors develop AToM CoWriter, which offers context-aware suggestions without requiring explicit prompts. Two within-subjects studies with 21 participants show that this approach improves expressiveness, idea exploration, and engagement with proactive suggestions.
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Conversational agents are increasingly embedded in human collaborative work, yet they remain fundamentally passive and reactive: they respond to explicit user requests rather than proactively recognizing moments when a team would benefit from timely intervention as human collaborators often do. This reactive design substantially limits the use of agents as active participants in multi-user collaboration, where disagreements, ambiguous goals, forgotten constraints, underspecified plans, discussion loops, and imbalanced participation can gradually undermine group progress.
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