R0043/2026-03-28/Q003/SRC03¶
MIT AI Risk Repository
Source¶
| Field | Value |
|---|---|
| Title | MIT AI Risk Repository |
| Publisher | Various |
| Author(s) | Various |
| Date | 2024-2025 |
| URL | https://iapp.org/news/a/naming-the-unseen-how-the-mit-ai-risk-repository-helps-map-the-uncertain-terrain-of-ai-governance |
| Type | Research paper/repository |
Summary¶
| Dimension | Rating |
|---|---|
| Reliability | Medium-High |
| Relevance | High |
| Bias: Missing data | Some concerns |
| Bias: Measurement | Low risk |
| 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 | Academic research; well-cited |
| Relevance | Addresses AI vocabulary/taxonomy bridging |
| Bias flags | Some missing data concern: may not capture all sycophancy-adjacent terminology |
Evidence Extracts¶
| Evidence ID | Summary |
|---|---|
| SRC03-E01 | 1,600 risk formulations across 65 documents; does not explicitly name sycophancy; related risks under generic 'human-computer interaction' domain |