I would like OpenAI to consider making the use of consumer ChatGPT data for model improvement more transparent and reciprocal.
Currently, users can choose whether their conversations may be used to improve models, but they receive little or no visibility into whether their data was actually useful. In the future, I would like to see some form of contribution dashboard—for example, showing whether a user’s conversations, corrections, feedback, or unusual use cases were selected or found useful for model evaluation or improvement.
I understand that it may be technically impossible to quantify the exact causal contribution of an individual conversation to model performance. However, OpenAI could still provide an approximate contribution score based on factors such as whether data was selected for training or evaluation, the quality of corrections, rarity of the use case, or usefulness in identifying model failures.
I would also like OpenAI to consider returning some value to users who voluntarily contribute high-quality data—for example through usage credits, additional tokens, temporary access to advanced features, or other benefits.
This would make opting in to model improvement feel less like one-way data collection and more like a voluntary exchange in which users can see that their contributions have value.
In particular, expert users may provide highly specialized conversations, detailed corrections, code debugging, scientific reasoning, or difficult real-world failure cases that could be disproportionately valuable for improving future models. A system that recognizes such contributions could benefit both OpenAI and its users.