Enabling Trustless Audits of Machine Learning Models without Revealing Sensitive Data or Model Weights

It is possible to simultaneously allow model providers to keep their model weights and data secret while allowing other parties to trustlessly audit model and data properties through the use of zero-knowledge proofs.