A change in the relationship between a system's inputs and the correct output, so the same input should now get a different answer 1. Unlike data drift, it shows only in outcomes: in production it appears in performance on fresh labels and in change-point tests on the error rate.
- Developed in
- ch. 11, Contrast pairs
ch. 15, Drift: what moves and how to see it - Chapters
- ch. 11, AI Defined · ch. 15, Deployment
- Contrast with
- Data drift
- Source
- 1 numbered reference, listed below
Commonly confused
Data drift versus Concept drift
- Data drift
- A change in the distribution of the inputs a system sees in production relative to the data it was validated on, such as a new customer segment or a changed upstream form.
- Concept drift
- A change in the relationship between a system's inputs and the correct output, so the same input should now get a different answer.
The differenceThe inputs change, against the relationship between inputs and the right answer changing.
Why it mattersThe first shows in input monitors before labels arrive; the second only in outcomes on fresh labels.
Where it is used
3 chapters of the Body of Knowledge use the term. Each link opens the first section that does.
- 11 · AI Defined Eight characteristics that break classic IT governance 1 mention
- 15 · Deployment Operating the system 1 mention
- 17 · Incidents AI-specific failure modes 2 mentions
Related terms
Sources
- [1] "Learning under Concept Drift: A Review" (IEEE TKDE 31(12); detection, understanding and adaptation; arXiv 2004.05785). Lu et al.. 2018. https://arxiv.org/abs/2004.05785 (verified: primary)
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