← 研踪 PaperTrailarXiv:2610.37469 · v1
Who Shaped What? Untangling Human and AI Creative Contributions Through Spatial Provenance in Image Editing
首次提交 2026-10-28 00:03
版本更新 2026-10-28 00:03
雷达观测 2026-10-29 00:34
摘要
Images co-edited with AI are often labeled to disclose AI use. However, creators feel these labels do not sufficiently describe their contributions to the editing process. Editing histories preserve requests, suggestions, and revisions, but how do creators use these logs to judge contribution? We investigated this with Roop, a mixed-initiative design probe that links image regions to editing histories (spatial provenance) and summarizes interactions in a heat map. Twenty participants edited images, annotated human and AI contributions, then reviewed the spatial provenance heat map. Participants credited themselves for directing changes while crediting AI for determining visual details. They judged contribution partly by whether their interactions achieved their intentions. Reviewing provenance helped participants remember interactions without always changing whom they credited. These findings motivate provenance systems that preserve enough context for creators to explain how interactions shaped their work, alongside the record of what happened.
作者备注：24 pages, 7 figures
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v1 · 2026-10-28 00:03 · 最新观测版本
Who Shaped What? Untangling Human and AI Creative Contributions Through Spatial Provenance in Image Editing
Images co-edited with AI are often labeled to disclose AI use. However, creators feel these labels do not sufficiently describe their contributions to the editing process. Editing histories preserve requests, suggestions, and revisions, but how do creators use these logs to judge contribution? We investigated this with Roop, a mixed-initiative design probe that links image regions to editing histories (spatial provenance) and summarizes interactions in a heat map. Twenty participants edited images, annotated human and AI contributions, then reviewed the spatial provenance heat map. Participants credited themselves for directing changes while crediting AI for determining visual details. They judged contribution partly by whether their interactions achieved their intentions. Reviewing provenance helped participants remember interactions without always changing whom they credited. These findings motivate provenance systems that preserve enough context for creators to explain how interactions shaped their work, alongside the record of what happened.
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