A distribution-free method that turns a trained model's output into a set of candidate answers that contains the right one with a chosen probability 1. A large set signals uncertainty that a governance rule can route on.
- Developed in
- ch. 11, Calibration before thresholds
- Chapters
- ch. 11, AI Defined
- Source
- 1 numbered reference, listed below
Where it is used
2 chapters of the Body of Knowledge use the term. Each link opens the first section that does.
Mentions as a table
| Chapter | Mentions | Cross-referenced |
|---|---|---|
| 00 Preface | 0 | No |
| 01 Definition | 0 | No |
| 02 Why Now | 0 | No |
| 03 Values & Principles | 0 | No |
| 04 The Stack | 0 | No |
| 05 Patterns | 0 | No |
| 06 The Role | 0 | No |
| 07 Maturity Model | 0 | No |
| 08 Regulatory Map | 0 | No |
| 10 Reading List | 1 | No |
| 11 AI Defined | 1 | Yes |
| 12 Governance Program | 0 | No |
| 13 Risk Management | 0 | No |
| 14 Development | 0 | No |
| 15 Deployment | 0 | No |
| 16 Fairness & XAI | 0 | No |
| 17 Incidents | 0 | No |
| 18 EU AI Act | 0 | No |
| 19 Privacy & AI | 0 | No |
| 20 Existing Law | 0 | No |
| 21 AI Laws Worldwide | 0 | No |
| 22 Principles & Standards | 0 | No |
| 23 AI Agents | 0 | No |
- 10 · Reading List Canonical papers: measurement, fairness and evaluation 1 mention
- 11 · AI Defined Governing probabilistic outputs 1 mention
Related terms
Sources
- [1] A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification (prediction sets with user-specified coverage; arXiv 2107.07511). Angelopoulos and Bates. 2021-07-15. https://arxiv.org/abs/2107.07511 (verified: primary)
Definitions of legal terms paraphrase the cited text, which governs. Dated statements are as of .