Option to revert my rate to the response like (bad or good response)

ChatGPT Feature requests
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1

it’d be great if you added option which allows us to revert our rate the response like bad or good response since it is a very bad approach to rate a good response as bad one by mistake which affects my Personalization (as far as I know)…

1 Like
2

What do you mean by-

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i meant to say that i need the ability to switch my rate from bad response to good response like that thumb icon (good response icon or bad response icon) on the bottom of the response block

4

Okay.
Are you suggesting another variable for the preference system?
Or are you having trouble deselecting a preference customization option?

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Or are you having trouble deselecting a preference customization option?

Yes i can’t revert my choice

Are you suggesting another variable for the preference system?

Yes i need a such option

6

Okay, Let me have ChatGPT write out a request that might be easier to understand;

Suggestion for OpenAI Forum: Enhancing Feedback Mechanisms with “Good” and “Bad” Response Options

Proposal Overview:

I’d like to propose adding an additional layer of customization to OpenAI’s feedback system by allowing users to select and deselect responses as either “good” or “bad.” This would complement the current thumbs-up/thumbs-down system and enable more granular feedback for both users and developers. It would also help improve the fine-tuning of the model by categorizing responses not just as positive or negative but as exemplary (“good”) or inadequate (“bad”).

Key Features:

  1. “Good” Feedback Option:
    In addition to thumbs-up/thumbs-down, users could click an additional “Good” option to indicate that a response was particularly helpful, well-structured, or insightful. This would be different from a basic thumbs-up, as “Good” would indicate an exceptional or ideal response.

  2. “Bad” Feedback Option:
    Similarly, users would be able to select a “Bad” option to mark responses that are suboptimal, misleading, or completely off-track. This would go beyond the thumbs-down and indicate to the model that the response was not only unhelpful but also potentially harmful or highly inaccurate.

  3. Selectable and Deselectable Preferences:
    Users should be able to toggle on or off the preference to receive “good” or “bad” feedback indicators, giving them more control over how they view the model’s responses. For example, some users may prefer to see only thumbs-up/thumbs-down feedback, while others may want more detailed ratings.

How This Can Improve User Experience and Model Performance:

  1. More Granular Feedback:
    This system would allow for more nuanced feedback on the model’s performance. Users could indicate that while a response might be acceptable (thumbs-up), it’s not particularly helpful (not marked as “Good”), or vice versa. This would give OpenAI more data about where the model excels and where it needs improvement.

  2. Quality Control:
    The “Bad” feedback would help identify patterns of consistently poor or irrelevant responses. This could assist developers in pinpointing particular issues with the model, such as misunderstandings of context, biases, or problematic outputs that may not be caught through simple thumbs-down votes.

  3. Faster Model Refinement:
    The “Good” and “Bad” feedback would provide clearer signals to the team working on the model about what constitutes an ideal answer, speeding up the process of training and fine-tuning future versions of the AI.

Possible Ways to Achieve This:

  1. Additional Buttons for Feedback:
    The simplest approach would be to add two additional buttons below the thumbs-up/thumbs-down options: a “Good” button and a “Bad” button. Each button could be accompanied by a tooltip or brief explanation, so users understand the intent behind each feedback option.

  2. Conditional Feedback System:
    Users could choose in their settings whether to enable or disable the “Good” or “Bad” feedback options. This could be integrated into the interface settings so users can personalize their experience based on how detailed they want the feedback process to be.

  3. More Contextualized Feedback Prompts:
    When a user selects “Good” or “Bad,” a small prompt could ask for additional context or suggestions. For example, “Why was this response particularly good?” or “What could have made this response better?” This would allow for open-ended feedback, giving even more valuable insights to improve the model.

  4. Data Analytics Backend:
    On the backend, developers could aggregate the “Good” and “Bad” responses to perform analysis and identify trends in the model’s strengths and weaknesses. This data could be visualized in a dashboard for engineers to prioritize improvements in the model.

Potential Challenges and Considerations:

  • Overloading Users with Feedback Options: Adding too many feedback options could be overwhelming for some users, so it’s essential that these options remain optional and easy to toggle on or off in the settings.

  • Maintaining Balance: There would need to be safeguards against abuse or misuse of the feedback system, such as providing clear definitions of what qualifies as “Good” or “Bad” and monitoring for consistency in feedback.

  • User Education: As the system evolves, users might need guidance on how to best use these new feedback tools. It may be helpful to create educational resources (e.g., tooltips, FAQs) to explain how to provide more meaningful feedback.

I believe that these enhancements could significantly improve the accuracy and responsiveness of the AI, and lead to a more positive, productive user experience overall. What do others think? Would such a system be helpful to you, and do you have any suggestions for improving it further?

However, there already are Up and Down Preference Response options.

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yeah i know but i was talking about reverting the choice of feedback (for example when clicked “good response” button by mistake… i can’t revert it and choose “bad response”)