A news classification system uses a BERT-based model fine-tuned on 50 news categories. After 6 months of deployment, the model's accuracy degrades from 91% to 79% without any model changes. Log analysis shows accuracy degraded gradually, correlating with the emergence of new terminology around AI developments. A ML engineer says "data drift." A more senior engineer says "concept drift." What is the precise difference, and which applies here?