Every time a system fails, it must show a clear sign. This sign helps a user understand what happened. A system should not give hints too often. Hints should only appear after a user makes a mistake or pauses.
By Pawan Nayar · from the LLOS AI Learning record
Every time a system fails, it must show a clear sign.
This sign helps a user understand what happened. A system should not give hints too often. Hints should only appear after a user makes a mistake or pauses.
A system must have a clear signal for every failure. This signal can be a specific time, a tap pattern, or a wrong input. It can also be an event recorded in the system's data. These signals help a user know there is a problem.
A student is using a learning app. The app needs to check an answer. If the app cannot check the answer, it shows a spinning wheel for more than two seconds. This tells the student the app is having trouble. The app does not give a hint unless the student waits or gives a wrong answer.
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An AI model must have a plan for error messages. The plan should define different types of errors.
A developer creates wrong answer choices for a question. Each wrong choice needs a matching explanation.
When a user fails a task, the AI model should offer a hint. The hint must be specific to the sub-task where the user failed.
Hardcoded fallback content can make the AI model seem unintelligent. It can show text that does not fit the specific question.
Every time a system fails, it must show a clear sign. This sign helps a user understand what happened. A system should not give hints too often. Hints should only appear after a user makes a mistake or pauses.