Graphing the Invisible: How Community Detection Makes AI Explanations Human-Scale
Graphing the Invisible: How Community Detection Makes AI Explanations Human-Scale Auditors like lists. Models, inconveniently, do not behave like lists. A credit model may tell you that income mattered, education mattered, job type mattered, age mattered, and postcode-adjacent variables mattered. A fraud model may produce the same kind of feature ranking, only with device fingerprints and transaction timings instead of employment history. The dashboard looks satisfyingly crisp: bars, scores, explanations, probably a tasteful shade of corporate blue. Then the real question arrives: which of these variables are acting together? ...