It would be great to know the weights of a model but that won’t happen. They could, however, give us abstracted coordinates that reference the training data relevant to produce an output which would help you discovery your own way to more precisely steer the output

@backpack put a bank in your pocket and use your money whenever, wherever, however without permission

/backpack
/notdevin
icebreaker.xyz/notdevin

If AI models gave us hints about what info they used to answer, how could we keep things fair for everyone involved in terms of privacy

What do fairness and privacy mean in this context?

It’s going to always favor a data source that’s got a large representation. The idea of over representation is exclusively a subjective outcome based on the viewer or user and impossible to predict ahead of time

The idea of data privacy is also a bit obtuse. If the model is trained on data, and you want to use it, then it’s not private. If there is data in the model that should have been private, too late. If there is data that is private and it’s before training then just remove the data 🤷‍♂️

Fairness in this case would mean ensuring the AI doesn’t favour certain data sources
And privacy in the sense of protecting sensitive data from being revealed