The consequence of this is that we have fundamentally basic models that adapt only to what features we, with limit understanding, point to.
-
-
-
This is in some sense fair; in many cases, we don't have the requisite mathematics to fully explain the behaviors we observe.
-
But it is terrifying when we elide their existence entirely. Instead, we use simplified techniques to understand very complex phenomena...
-
and then use these limited conclusions to make actual policy decisions. In the worst case, these conclusions determine who to drone-strike.
-
But we chug ahead because computing power is cheap, databases are ultimately pretty easy, and the ramifications ultimately seem distant.
-
This is not to say that data science is irrelevant. But there is a missing component and that is a posteriori validation of models...
-
along with an explicit process in which to do so. Data analysis is a step in a solution process, not a solution in and of itself.
-
We too often confuse provability in a mathematical context with truth in the broad strokes of human experience.
End of conversation
New conversation -
Loading seems to be taking a while.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.