Sounds like a bad idea, but you can use the idea of synthetic data to construct innovative models as starting points for serious research. We did this to understand how product sold in mock stores, then moved the models to real stores. It often gave us real insight to the data and its use. I remember working with Mitre years ago and even then they used the concept of mock data contexts. Always can be a good way to think through model data design. We did not do enough of it.
The People in This Medical Research Are Fake. The Innovations Are Real. By Dov Lieber, April 6, 2021, The Wall Street Journal
Medical researchers and data scientists are generating artificial patients algorithmically from real-life datasets to accelerate the development of innovations with real-world applications. Allan Tucker at the U.K.'s Brunel University London said, "The key advantage that synthetic data offers for healthcare is a large reduction in privacy risks that have bugged numerous projects [and] to open up healthcare data for the research and development of new technologies." The Covid-19 pandemic fueled demand for synthetic-data solutions as medical providers and researchers raced to understand the pathogen and develop treatments. Israel is a major testbed, using the MDClone startup's platform for creating synthetic data from medical records, for example. Not all synthetic-data research relies on real-life medical records: U.S. nonprofit Mitre's open source Synthea tool can generate populations of artificial patients from scratch, using publicly available data sources. ... '
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