Framework for Governing Repository Data in AI Training
Students: Tony Hoang, Rachel Amanor, Ashlee Wood
A new problem that has arisen with AI is deciding what data to use when training new models. The more information and data that a model is trained on, and the more diverse that information is, the more accurate and reliable the model will be. When looking at the problem from this perspective only, it does not sound like much of a problem — use as much data as possible to train a model. But is anything ever that simple?
