Training is not certainty
A model's training data does not guarantee that its output will be correct in a new situation.
INSIGHTS / ARTIFICIAL INTELLIGENCE
AI is powerful. It is not infallible.
AI systems can identify patterns and generate outputs, but their reliability depends on the task, data, evaluation, and operating conditions.
THE ESSENTIALS
Built on clear principles.
Evaluate with relevant tests
Use representative evaluation data, clear metrics, and independent review where appropriate.
Be careful with random systems
AI cannot infer future outcomes from historical records alone when the process is genuinely random and offers no exploitable information.
KEEP EXPLORING
Curiosity is a good place to start.
Browse the learning center for clear explanations of algorithms, probability, data, and digital safety.
Visit the learning center