You could do something like kaggle does, where you have some test data but the final score is determined by a more complete test data that you don't have access to.
1. A researcher puts out a model with bad initial parameters/data.
2. The chain workers/miners train the model as request.
3. The model fails at the test or verification dataset due to the bad setup.
In this case, the miners would not get paid despite doing exactly what was asked of them.
Lack of trust there can be addressed with a few other things like staking, and a broad desire for all miners that people trust the system as a whole. Quite how to design those things is a complex problem but not insurmountable I think.
Disclaimer, this kind of decentralised more useful kind of work is something I'm investigating now.