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Qualitative Feedback for Training



When a system being trained by a user is not producing adequate outputs, more information is required to understand what's not working as expected or desired. The user does not want to invest a lot of effort in this process.

An example of a low-effort feedback option with prompts (multiple choice inputs and open text entry field) in a user app
In the two images above, a user is given the option to provide feedback with the simple push of a button, and then the application makes feedback easy by auto-generating some options as well as providing an open text field for more information if desired.


Triggered by a negative response or rating, the system prompts the user to provide qualitative feedback in the form of an explanation of what is unsatisfactory. This may be free text input or selection from preset options, and is usually done in combination with Quantitative Feedback for Training.


As the effort required here is relatively high for the user with no immediate reward, care should be taken to motivate the user accordingly. This could be the system advising that this feedback will help the system improve and thus establish the benefit to the user. Or the motivation could simply be a pleasant and rewarding interaction, e.g. an interesting conversation point with a chatbot.