Machine learning sucks at covid

Every “AI” covid tool was useless.

The worst part of machine learning snake-oil isn’t that it’s useless or harmful — it’s that ML-based statistical conclusions have the veneer of mathematics, the empirical facewash that makes otherwise suspect conclusions seem neutral, factual and scientific.

Think of “predictive policing,” in which police arrest data is fed to a statistical model that tells the police where crime is to be found. Put in those terms, it’s obvious that predictive policing doesn’t predict what criminals will do; it predicts what police will do.

Cops only find crime where they look for it. If the local law only performs stop-and-frisks and pretextual traffic stops on Black drivers, they will only find drugs, weapons and outstanding warrants among Black people, in Black neighborhoods.

That’s not because Black people have more contraband or outstanding warrants, but because the cops are only checking for their presence among Black people. Again, put that way, it’s obvious that policing has a systemic racial bias.

But when that policing data is fed to an algorithm, the algorithm dutifully treats it as the ground truth, and predicts accordingly. And then a mix of naive people and bad-faith “experts” declare the predictions to be mathematical and hence…