Nate Silver: preference

Transcript context

…Hi. My name’s Tom. Earlier, Tyler brought up the question, “How much data do people want?” A two-part question. Does the amount of data that people want, is that influenced by the way data is presented? The second part would be, what advice would you give as far as presenting data, or visualizing it? Visualizing it might be some of the advice. People seem to learn a lot better from visualization. One thing I think a lot about as a journalist is preferring simple models to more complicated models. There are other virtues of simple models. People can also take it too far. But as a journalist, for example, to have something I can say this is a benchmark, and I understand what it’s doing, and I can explain what it’s doing, and I can also understand what the limitations of it might be, and so I know which direction to lean relative to that baseline. It’s more useful than a place where you just say, “Well, we fed some data into a random number generator, or a magic machine, and here’s what it spit out. ” For example, I highly prefer — this is going off on a tangent — but I prefer regression-based modeling to machine learning, where you can’t really explain anything. To me, the whole value is in the explanation. But I do think likewise, people, when you explain it and say, “Hey, we probably have the same interests here in mind,” to say this is actually pretty simple once you start peeling away the BS. To me, that approach works a lot better in the long run than the approach of saying, arguments from authority, “Well, this is rigorous, and empirical, and objective, so therefore believe the numbers.” I think explaining to people why it’s actually not all that complicated, and why you’re making very defensible assumptions how that leads you to an answer that might surprise them. Next question.…

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