AI-authored goals produce higher SMART quality scores but lower psychological ownership, commitment, importance, and goal-directed behavior than self-authored goals, with ownership as the mediating mechanism.
InProceedings of the 2024 CHI Conference on Human Factors in Computing Systems
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Structural mental models of AI writing assistants improve system understanding and usability but result in more grammatical errors in user writing compared to functional models.
A VR study found that dynamic feedback based on completion time, straightness or peak speed improved average pointing performance but produced small or opposite effects for some users.
An online experiment finds that showing users an overview of an AI's values reduces reliance on AI suggestions during writing tasks.
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Optimized but Unowned: How AI-Authored Goals Undermine the Motivation They Are Meant to Drive
AI-authored goals produce higher SMART quality scores but lower psychological ownership, commitment, importance, and goal-directed behavior than self-authored goals, with ownership as the mediating mechanism.
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From Use to Oversight: How Mental Models Influence User Behavior and Output in AI Writing Assistants
Structural mental models of AI writing assistants improve system understanding and usability but result in more grammatical errors in user writing compared to functional models.
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Game Changers: Designing and Measuring Dynamic Feedback To Help Users Self-Regulate in a VR Pointing Game
A VR study found that dynamic feedback based on completion time, straightness or peak speed improved average pointing performance but produced small or opposite effects for some users.
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Framing an AI with Values Reduces AI Reliance in AI-supported Writing Tasks
An online experiment finds that showing users an overview of an AI's values reduces reliance on AI suggestions during writing tasks.