arXiv — NLP / Computation & Language · · 3 min read

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

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Computer Science > Computation and Language

arXiv:2605.21363 (cs)
[Submitted on 20 May 2026]

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

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Abstract:As large language models (LLMs) increasingly shape how users form, refine, and extend their goals, attributing contributions in human-AI collaboration becomes critical for users calibrating their own reliance and for evaluators assessing AI-assisted work. Yet existing methods focus on final artifacts, missing the process through which goals themselves are jointly shaped. We introduce a goal-level attribution framework, CoTrace, that decomposes explicit goals into verifiable requirements and traces both direct contributions and indirect influences across dialogue turns. Applying CoTrace to 638 real-world collaboration logs, we find that while models account for only 11-26% of goal-shaping contribution, they contribute substantially more on introducing lower-level concrete requirements, and make various kinds of indirect contributions. Through controlled simulations, we show that interaction design choices significantly affect model goal-shaping behavior. In a user study, exposing participants to goal-level analyses shifts their perceived contributions by nearly 2 points on a 5-point scale, revealing systematic miscalibration in how users understand their own AI-assisted work.
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2605.21363 [cs.CL]
  (or arXiv:2605.21363v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2605.21363
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Eunsu Kim [view email]
[v1] Wed, 20 May 2026 16:28:34 UTC (9,826 KB)
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