AI or Augmented Intelligence?
Artificial Intelligence usually means a system that decides and acts entirely on its own; Augmented Intelligence means a system that assists a person, who still makes the final call — the same underlying model can be run either way, and which one you're building comes down to how much you trust its decisions, not how smart it is. A tea shop wants to know: can a simple computer program be trusted to sort incoming stock as Green or Black tea on its own, or should a person always double-check it? The program looks at a new sample's steep time and water temperature, compares it to cups it already knows the answer for, and makes a guess — plus a confidence score for how sure it is. Real systems (fraud detection, content moderation, medical-image checks) use exactly this kind of confidence cutoff to decide when to trust a model and when to send it to a person instead.
Drag the marker — or tab to it and use the arrow keys — to change the sample's steep time and water temperature, same as the k-Nearest Neighbours demo. Confidence is how many of the k nearest known cups actually agree on the type: all of them agreeing means very sure, a near-even split means barely sure at all. Set how confident the system needs to be before it's allowed to decide alone with the threshold slider. Cross that line and the outcome below flips: above it, the system decides on its own — this is what "AI" means here, fully autonomous. Below it, the case gets sent to a person to review instead — this is "Augmented Intelligence," a human makes the final call. Same underlying guess both times; only who acts on it changes.
What this teaches: Set a confidence threshold to decide which of a model's predictions are acted on automatically and which go to a person for review. It teaches the trade-off between automation and human oversight, and the difference between artificial and augmented intelligence.