Does generative deep learning (diffusion or flow matching models) have a place in Economic research?

Hi,

I'm currently an econ undergrad heading into my final year; I'm required to do a final project around 7500 words, I was thinking of use generative models to explore policy analysis, (I used these models at internship at a biotech firm to understand drug effects on cells). For this project, I would:

1. Take geospatial data of a region before and after a policy is implemented
2. Train a generative model to learn the transformation from the "before" state to the "after" state, conditioned on the specific policy that was applied.
3. Use the trained model to predict potential outcomes by providing the "before" state but conditioning on a different policy, or no policy at all.

While i do understand that it's probably impossible to derive causality from this, is a project like this a waste of time? I want to use this project for methodological exploration is that too ambitious?

I'd love to get your feedback on this idea. Also are there any key papers, methods, or researchers i should be looking into?