R0029/2026-03-27/Q001/S01
WebSearch — Frameworks and standards for attributing AI contributions in collaborative work
Summary
| Field |
Value |
| Source/Database |
WebSearch |
| Query terms |
"framework standard attributing AI contributions collaborative human-AI work authorship" |
| Filters |
None |
| Results returned |
10 |
| Results selected |
3 |
| Results rejected |
7 |
Selected Results
| Result |
Title |
URL |
Rationale |
| S01-R01 |
Which Contributions Deserve Credit? Perceptions of Attribution in Human-AI Co-Creation |
https://arxiv.org/html/2502.18357v1 |
CHI 2025 peer-reviewed study directly on AI attribution perceptions |
| S01-R02 |
Attributing AI Authorship: Towards a System of Icons for Legal and Ethical Disclosure |
https://scholarlycommons.law.northwestern.edu/njtip/vol22/iss1/1/ |
Formal proposal for an AI attribution icon system |
| S01-R03 |
CRediT — Contributor Roles Taxonomy |
https://credit.niso.org/ |
Existing NISO standard for contributor attribution — baseline reference |
Rejected Results
| Result |
Title |
URL |
Rationale |
| S01-R04 |
Human-AI Collaboration in Writing |
https://digitalcommons.lindenwood.edu/cgi/viewcontent.cgi?article=1727&context=faculty-research-papers |
General collaboration paper, not focused on attribution frameworks |
| S01-R05 |
Who Owns the Output? Bridging Law and Technology in LLMs Attribution |
https://arxiv.org/html/2504.01032v1 |
Focuses on legal ownership rather than contribution attribution |
| S01-R06 |
Authorship and Attribution of AI Generated Content |
https://project-rachel.4open.science/Rachel.So.Authorship.and.Attribution.of.AI.Generated.Content.pdf |
Overlaps with other sources; primarily a literature review |
| S01-R07 |
Joining forces for online feedback management |
https://www.cambridge.org/core/journals/data-and-policy/article/joining-forces-for-online-feedback-management-policy-recommendations-for-humanai-collaboration/5DEBADE69D10D5B90B7CB7FD0BC745D6 |
About online feedback management, not attribution |
| S01-R08 |
Authorship in AI-Generated Works: Exploring Originality |
https://atrip.org/wp-content/uploads/2024/05/3rd-place-revised.pdf |
Copyright originality focus rather than attribution frameworks |
| S01-R09 |
A new tool for crediting AI's contributions — IBM Research |
https://research.ibm.com/blog/AI-attribution-toolkit |
Selected via S02 instead to avoid duplication |
| S01-R10 |
The Human Authorship Requirement in AI-Generated Works |
https://www.researchgate.net/publication/398723345 |
Copyright framework analysis, not contribution attribution |
Notes
Search returned a mix of attribution-focused and copyright/authorship-focused results. The distinction between "attribution" (who contributed what) and "authorship" (who holds legal credit) is important — this search captured both, with the selected results focused on the former.