The Signal and the Noise: Why So Many Predictions Fail-but Some Don't

by Nate Silver

Diversity. If everybody comes in thinking the same way about a problem, then forming a group is pointless. A room of one hundred Nates (a scary thought!) is going to come to pretty much exactly the same conclusion that one Nate does, only they’ll probably have become more hardheaded and inflexible about it by constantly agreeing with one another. So you want people with a diversity of backgrounds, experiences, and skill sets as part of your group.* Independence. People need to be able to share ideas and dissent openly, without fear of reprisal. Otherwise, the most powerful members of a group will just cow everyone else into submission and create a false consensus. Moreover, you want to avoid information cascades wherein people’s preferences are dependent on everyone else’s preferences. Trust. Groups are effective when people are confident that they are fair and free of corruption. And in

The 1970s were the high point for “vast amounts of theory applied to extremely small amounts of data,” as Paul Krugman

successful predictions of medical hypotheses carried out in laboratory experiments. It concluded that most of these findings were likely to fail when applied in the real world. Bayer Laboratories recently confirmed Ioannidis’s hypothesis. They could not replicate about two-thirds of the positive findings claimed in medical journals when they attempted the experiments themselves.40

There are so many hypotheses to test, so many data sets to mine—but a relatively constant amount of objective truth.

We are undoubtedly living with many delusions that we do not even realize.

The most calamitous failures of prediction usually have a lot in common. We focus on those signals that tell a story about the world as we would like it to be, not how it really is. We ignore the risks that are hardest to measure, even when they pose the greatest threats to our well-being. We make approximations and assumptions about the world that are much cruder than we realize.

Nobody saw it coming. When you can’t state your innocence, proclaim your ignorance:

“The major difference between a thing that might go wrong and a thing that cannot possibly go wrong is that when a thing that cannot possibly go wrong goes wrong it usually turns out to be impossible to get at or repair,” wrote

If you borrow $20 to wager on the Redskins to beat the Cowboys, that is a leveraged bet.* Likewise, it’s leverage when you borrow money to take out a mortgage—or when you borrow money to bet on a mortgage-backed security.

In the paper, he demonstrated that in a market plagued by asymmetries of information, the quality of goods will decrease and the market will come to be dominated by crooked sellers and gullible or desperate buyers.