R0043/2026-03-28/Q003/SRC01
Trilateral Research — How to Fix the AI Terminology Gap
Source
| Field |
Value |
| Title |
How to fix the AI terminology gap |
| Publisher |
Trilateral Research |
| Author(s) |
Trilateral Research |
| Date |
2025 |
| URL |
https://trilateralresearch.com/responsible-ai/how-to-fix-the-ai-terminology-gap |
| Type |
Policy research article |
Summary
| Dimension |
Rating |
| Reliability |
Medium |
| Relevance |
High |
| Bias: Missing data |
Low risk |
| Bias: Measurement |
N/A |
| Bias: Selective reporting |
Some concerns |
| Bias: Randomization |
N/A — not an RCT |
| Bias: Protocol deviation |
N/A — not an RCT |
| Bias: COI/Funding |
Some concerns |
Rationale
| Dimension |
Rationale |
| Reliability |
Private research firm; not peer-reviewed but well-argued |
| Relevance |
Most direct treatment of the AI terminology gap as a named problem |
| Bias flags |
COI: Trilateral may benefit commercially from organizations needing terminology consulting; selective reporting toward solution-selling |
| Evidence ID |
Summary |
| SRC01-E01 |
Explicit identification of the AI terminology gap with cross-domain examples and proposed solutions |