The tendency of neural networks to lose earlier competence when trained on new tasks 1. It is a reason every retraining is a change event that re-runs the full eval suite, not only the tests for the new capability.
- Developed in
- ch. 11, Eight characteristics that break classic IT governance
- Chapters
- ch. 11, AI Defined
- Source
- 1 numbered reference, listed below
Where it is used
One chapter of the Body of Knowledge uses 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 | 0 | 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 |
- 11 · AI Defined Eight characteristics that break classic IT governance 1 mention
Related terms
Sources
- [1] Overcoming catastrophic forgetting in neural networks (networks lose earlier competence when trained on new tasks; arXiv 1612.00796). Kirkpatrick et al.. 2016-12-02. https://arxiv.org/abs/1612.00796 (verified: primary)
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