R0029/2026-03-27/Q001/SRC01
He, Houde, Weisz et al. — CHI 2025 paper on attribution perceptions
Source
| Field |
Value |
| Title |
Which Contributions Deserve Credit? Perceptions of Attribution in Human-AI Co-Creation |
| Publisher |
ACM CHI 2025 Conference on Human Factors in Computing Systems |
| Author(s) |
Jessica He, Stephanie Houde, Justin D. Weisz, et al. |
| Date |
April 2025 |
| URL |
https://dl.acm.org/doi/10.1145/3706598.3713522 |
| Type |
Research paper (peer-reviewed conference) |
Summary
| Dimension |
Rating |
| Reliability |
High |
| Relevance |
High |
| Bias: Missing data |
Low risk |
| Bias: Measurement |
Some concerns |
| Bias: Selective reporting |
Low risk |
| Bias: Randomization |
N/A — not an RCT |
| Bias: Protocol deviation |
N/A — not an RCT |
| Bias: COI/Funding |
Some concerns |
Rationale
| Dimension |
Rationale |
| Reliability |
Peer-reviewed at CHI 2025 (top-tier HCI venue), 155-participant survey study with mixed methods, published by ACM |
| Relevance |
Directly addresses how people perceive and assign credit in human-AI collaboration — the core question |
| Bias flags |
Measurement concern: participants from a single technology company (IBM), which may skew toward tech-savvy population. COI concern: authors are IBM researchers who also built the AI Attribution Toolkit, creating potential motivation to find that attribution frameworks are needed |
| Evidence ID |
Summary |
| SRC01-E01 |
AI partners receive less credit than human partners for equivalent contributions; attribution requires granularity beyond binary disclosure |