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New framework reveals AI's subtle role in shaping user goals

A new framework called CoTrace has been developed to analyze how large language models influence goal formation in human-AI collaborations. Research using this framework on over 600 collaboration logs indicates that while AI models contribute directly to goal shaping only 11-26% of the time, they are significant in introducing specific requirements and making indirect contributions. Furthermore, the study found that interaction design choices impact AI goal-shaping behavior, and exposing users to goal-level analyses helps correct miscalibrations in their perception of AI-assisted work. AI

IMPACT This research offers a new lens for understanding and quantifying AI's indirect influence in collaborative tasks, potentially leading to better AI design and user calibration.

RANK_REASON The cluster contains an academic paper detailing a new framework and findings on AI contributions in collaboration. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Hugging Face Daily Papers →

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New framework reveals AI's subtle role in shaping user goals

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The cluster contains an academic paper detailing a new framework and findings on AI contributions in collaboration. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    "I didn't Make the Micro Decisions": Measuring, Inducing, and Exposing Goal-Level AI Contributions in Collaboration

    A goal-level attribution framework called CoTrace is introduced to analyze how large language models contribute to goal shaping in human-AI collaboration, revealing that while models account for a small percentage of direct contributions, they play a significant role in introduci…