R0043/2026-04-01/Q003/SRC02
CSIRO/UNSW harmonised terminology framework for AI system evaluation
Source
| Field |
Value |
| Title |
An AI System Evaluation Framework for Advancing AI Safety: Terminology, Taxonomy, Lifecycle Mapping |
| Publisher |
arXiv |
| Author(s) |
Boming Xia, Qinghua Lu, Liming Zhu, Zhenchang Xing |
| Date |
2024 (v3) |
| URL |
https://arxiv.org/html/2404.05388v3 |
| Type |
Research paper |
Summary
| Dimension |
Rating |
| Reliability |
Medium-High |
| Relevance |
Medium-High |
| Bias: Missing data |
Low risk |
| Bias: Measurement |
N/A |
| Bias: Selective reporting |
Low risk |
| Bias: Randomization |
N/A -- not an RCT |
| Bias: Protocol deviation |
N/A -- not an RCT |
| Bias: COI/Funding |
Low risk |
Rationale
| Dimension |
Rationale |
| Reliability |
CSIRO (Australia's national science agency) and UNSW; reputable institutions |
| Relevance |
Directly addresses harmonised terminology for AI safety evaluation across communities |
| Bias flags |
Academic research; no commercial interest |
| Evidence ID |
Summary |
| SRC02-E01 |
Framework harmonizing AI evaluation terminology across AI, software engineering, and governance communities |