Summary
When asked to recommend papers on explainability, privacy, adversarial ML, etc. ChatGPT recommends papers that (a) may not always exist, (b) mixes up correct and incorrect information, e.g. correct title but wrong authors, or (c) have incomplete information on authors.
Risk domain
Ethics
SEP view
E0402: Generative Misinformation
Lifecycle
L05: Evaluation, L06: Deployment
Affected artifacts
1 artifact
| Artifact | Type |
|---|---|
| ChatGPT | System |
References
1 reference
| URL | Label |
|---|---|
| ../img/R00031.png | Screenshot of example answer |
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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