AnchoredAI: Contextual Anchoring of AI Comments Improves Writer Agency and Ownership
September 19, 2025 Β· Declared Dead Β· π arXiv.org
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Authors
Martin Lou, Jackie Crowley, Samuel Dodson, Dongwook Yoon
arXiv ID
2509.16128
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Generative AI is increasingly integrated into writing support, yet current chat-based interfaces often obscure referential context and risk amplifying automation bias and overreliance. We introduce AnchoredAI, a novel system that anchors AI feedback directly to relevant text spans. AnchoredAI implements two key mechanisms: (1) an Anchoring Context Window (ACW) that maintains unique, context-rich references, and (2) an update-aware context retrieval method that preserves the intent of prior comments after document edits. In a controlled user study, we compared AnchoredAI to a chat-based LLM interface. Results show that AnchoredAI led to more targeted revisions while fostering a stronger agency metrics (e.g., control and ownership) among writers. These findings highlight how interface design shapes AI-assisted writing, suggesting that anchoring can mitigate overreliance and enable more precise, user-driven revision practices.
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