If they were, they would go make money in the prediction markets, and the prediction markets would become more accurate.
Truths so brutal, and predictions so harsh that no one dares write them down.
But now we enter the information age, and certain realities are essentially undeniable, and can no longer concealed from the civilian panopticons like Google.
Sort of like how TV Networks (and even basic cable channels to a degree), with their Standards & Practices departments, waste time sanitizing television destined for the public air waves and radio spectrum, while media on the internet operates with an almost total lack of restraint.
Basically, get a degree in a related field (international politics, security, languages, demographics, economics, etc), and have decent marks. Apply. Don't tell anyone (until they have briefed you on what you can say). Don't have any skeletons in your closet.
It's basically like getting a USAID job, but probably not as competitive (lots of funding = lots of positions, and most people doing these kinds of degrees tend to not be very pro-defence) and with slightly higher security requirements.
huh?
On the other hand, if I actually _am_ good at making predictions, then I will continue to make good predictions.
> The big surprise has been the support for the unabashedly elitist “super-forecaster” hypothesis. The top 2% of forecasters in Year 1 showed that there is more than luck at play. If it were just luck, the “supers” would regress to the mean: yesterday’s champs would be today’s chumps. But they actually got better. When we randomly assigned “supers” into elite teams, they blew the lid off IARPA’s performance goals. They beat the unweighted average (wisdom-of-overall-crowd) by 65%; beat the best algorithms of four competitor institutions by 35-60%; and beat two prediction markets by 20-35%
[0]http://www.economist.com/news/21589145-how-sort-best-rest-wh...