An AI model's feedback must help the user understand and move forward. If feedback does not explain or advance the user's learning, it is not useful. A developer must ensure all feedback is helpful.
By Pawan Nayar · from the LLOS AI Learning record
An AI model's feedback must help the user understand and move forward.
If feedback does not explain or advance the user's learning, it is not useful. A developer must ensure all feedback is helpful.
An AI model should give feedback that explains why an answer is wrong. The feedback must help the user learn. It should guide the user to the correct answer. If feedback does not do this, it is not helpful. A developer must review the feedback system.
A student uses an AI model for a math problem. The student makes two wrong attempts. The AI model's feedback only says 'Incorrect.' It does not explain the mistake. The student does not learn from the feedback. The student cannot solve the problem.
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After a third wrong attempt, the AI model should show a large explanation. Correct parts of the user's answer should turn green.
An AI model should first acknowledge the user's reasoning. This shows the AI model understands the user's thought process.
An AI model should match its communication style to the user's interests. For example, if a user likes science, the AI model uses science examples.
A wrong answer is not a dead end for the user. It is a chance for the AI model to teach.
An AI model's feedback must help the user understand and move forward. If feedback does not explain or advance the user's learning, it is not useful. A developer must ensure all feedback is helpful.