A governance lead is categorising the AI systems in use across a bank. One system drafts new marketing copy from a short brief, while another scores loan applications as approve or decline. What distinguishes the copywriting system as generative rather than classic AI?
- AIt produces new content by sampling from patterns it has learned, whereas the classic system assigns inputs to predefined outcome categories. Correct
- BIt runs on cloud infrastructure, whereas classic systems are always installed and operated entirely on local hardware.
- CIt was trained on labelled examples, whereas classic systems are built only from unlabelled data with no human supervision.
- DIt guarantees factually accurate outputs on every request, whereas the classic system can return scored predictions that are occasionally incorrect.
Why A is correct: Generative AI synthesises novel artefacts such as text by modelling the data distribution, while classic discriminative AI maps an input to one of a fixed set of labels such as approve or decline.
Why B is wrong: Deployment location is tempting because hosting often differs in practice, but where a model runs has no bearing on whether it is generative or classic; both kinds run on cloud or local hardware.
Why C is wrong: This inverts the truth and is tempting because supervision is a real distinction; many classic classifiers use labelled data, and generative models often learn in a self-supervised way, so the contrast is wrong.
Why D is wrong: This is tempting because accuracy matters to governance, but generative models do not guarantee correctness and can hallucinate, so reliability does not define the generative category.