[Super Forecasting The Art And Science Of Prediction Epub Download
Ainoha Sistek
Cut to the late 2000s. The US intelligence community has just been seriously embarrassed by their disastrous declaration that there were weapons of mass destruction in Iraq. They set up an Intelligence Advanced Research Projects Agency to try crazy things and see if any of them worked. IARPA approached a bunch of scientists, handed them a list of important world events that might or might not happen, and told them to create some teams and systems for themselves and compete against each other to see who could predict them the best.
super forecasting the art and science of prediction epub download
Download File ⇒ https://t.co/xE3kvO1GVJ
Updating based on evidence and avoiding simple biases like anchoring or scope insensitivity is first, a very basic of the sequences and second, something that you could have heard from any number of other sources from Kahnemann to Silver.
That said, I wonder if there are any weirder cultural affinities of superforecasters. What sort of music to they like? What books do they read? What cultures did they grow up in, or are descended from? Do superforecasters peak at a certain age? Are they nerds, or physically fit and mentally healthy? I suppose I should read the book.
because it alleges that only lesser nerds need status, and us True Geeks know the score before it was cool. This is an incredibly stupid and damaging way of looking at the world, a classic nerd failure mode, and everytime nerds sneer at those of high status they emphasize their own weakness and make their situation worse.
TBH, there have been many hostile, aggressive, and confrontational posters toward whom no one has expressed anything approaching pleasure. But, people get singled out seemingly at random, depending on who they happen to rub the wrong way.
Beware the fundamental attribution error. Right now honestlymellowstarlight had made a post people are objecting to and is defending themself. In a less confrontational context they may make valuable contributions.
If Scott were to be appointed government czar of all message boards, maybe. But given that the whole reason I come here is that I enjoy his insight and trust his judgment, I support him banning whoever he wants.
I also was in the experiment for a year and they would ask things about the probability of president X being ousted in the next year in small african country Y. I am a person that reads alot, but every question usually involved quite a bit of reading to do basic background probabilities.
Well, you beat me to it ? One could also say that the marginal utility I have from an additional bird is decreasing. After all, if the question was about billions of birds, people would probably pay killing some of them to keep their population in check.
The question is actually hard to answer if you are not provided with the information about how many birds there are in total. Saving 10 birds is a big deal if there are only 10 birds in total, saving ten birds in a population of millions is not worth a dime.
On the other hand, 1000 birds may be enough to bring the species back from the brink pretty easily, while a population of 100 turns out to be a hopeless money pit (for comparison, it has cost $35 million to turn 27 California condors into 425). The point is well-taken, though, there are too many extra factors here.
The actual source Scott is pointing to is a 1992 experiment done by Desvouges et al., in which it was specified that there were 8.5 million migratory waterfowl, and that N of them died, and that it would be possible to prevent those deaths, but doing so is costly and the costs would be passed on to the consumers. So, how much are you, as a consumer, willing to pay to prevent the N deaths?
The straightforward interpretation of this result, that lines up with other experiments, is that people are imagining a single bird, deciding how much sympathy they have towards that one bird, and choosing a price accordingly. They are not making use of the number of birds, or of the fraction of all birds that this represents.
In retrospect, an event has a probability of either 100% or 0%, depending on whether it happened or not. Take the difference between the predicted and the actual value, maybe square that number to more heavily punish strong mispredictions. Assign that value as an absolute as penalty points, and the person with the lowest penalty score wins. Then repeat that same scoring except with the prediction values rounded, and compare the scores.
Regardless, dozens or hundreds of predictions is not implausible, especially when you do them as part of a study/program i.e. when it becomes your job for a while. People like Scott make dozens of such predictions each year on their own time.
It is worth noting that around the 80s and 90s (%), rounding can make a very large difference when you think in terms of log odds or bits. E.g. many people would round 85% to 90%, or might feel a bit more than 90% confident and call that 95%, or a bit more than 95% confident and call it 99%. The last one is particularly bad.
I would also imagine that knowing the system 1/system 2 reasoning behind the question would help a lot more in answering future questions of that style than simply seeing one such question and having a wrong answer.
The contest was well publicized ahead of time on the highbrow public affairs and forecasting blogs. Tetlock is a big name in certain circles, so there was much interest in it among the kind of people who might do well on it.
If the benefits of foxiness are purely from randomness, why do the foxes repeatedly outperform random guessing? And why do good predictors remain good predictors over time rather than regressing to the mean?
The bird question is kind of ill-defined because unlike the probability of korea going to war, it depends on a value judgement, namely how much a species and an individual animal is worth. These numbers will either have to be pulled out of thin air by each individual participant, or else estimated based on the amount of funding similar bird-saving initiatives receive in the real world. I think the relevant information is hard to find and interpret in this case, again unlike the korea example.
Which is to say, some of the people are answering a different question than is being asked. (I think schools train students to do this by inserting red-herring numbers into word problems, training people to think of the question first, and the numbers second.)
Saving 100000 birds is a larger number than saving 100 birds. However, it may not be a larger percentage of the bird population, and I might gain constant utility from saving a fixed percentage of the bird population rather than from saving a fixed number of birds. Furthermore, someone asking me a question about saving birds will normally name a number that roughly scales with the size of the population.
Edit: this probably came off as meaner than I intended. That last paragraph was intended in a joking manner. I just think this whole discussion is silly. Clearly scope insensitivity is a real phenomenon, and I think these results are much more likely attributable to it than to other strange implicit premises.
My point is, I think, that people like to be consistent. If you have a deeply held belief about the nature of the world, you obviously also believe that this belief holds, and if it holds, then events in the world will be consistent with it.
I think the economist who deserves credit for taking a fox approach to macroeconomic predictions is David Henderson. He disagreed with Krugman when Krugman was predicting runaway inflation in the early 1980s, and he bet against Bob Murphy when Bob was predicting runaway inflation after 2008. Krugman and Murphy are both smart hedgehogs, and Henderson was able to out-predict both of them by just projecting the status quo forward.
He then tried to split human forecasters by scores, looking for correlations with various things about them (my favorite correlation is that people regularly in contact with the media did substantially *worse*). He found that cognitive style (fox/hedgehog) had a big impact. You can see his fox/hedgehog quiz on page 74.
So foxes do as good or better than than the chimp on calibration (accuracy of their responses) while substantially improving discrimination (they hedge less). Hedgehogs do substantially worse than the chimp on calibration while picking up only a bit of additional discrimination.
Whereas the superforecasters knew nothing about General X and so left his influence out of their weighing of the probabilities, so when he fell into disfavour it made no difference to their predictions?
Another possibility is that there might not be a democratic nominee. The party could split, or the election process could be suspended. Something like a Yellowstone eruption, or a nuclear war with Russia, would probably take care of the latter.
Which tables did you use to give Clinton a 2.9% chance of dying? (The ones I found put it at 1.4% for her age/sex.)
(less chance for SES, imo, and more because of previous health issues, so I think it evens out.)
However I am apparently unable to correctly read data from a simple table, since I now see that it should be 1.3% for Hillary. I remember in an earlier version of my post I wrote that Clinton is 2 years older than Sanders, so I think I was mistakenly taking her age as 76 instead of 68. Whoops.
I think there is a significant chance of someone other than those three being nominated, probably several percent. Clinton could be eliminated either by dropping dead or by being indicted over the emails. Neither is likely, both possible.
Well Hillary, or rather most of her immediate entourage have been already been implicated. The real question is whether or not the Obama administration will actually prosecute, which I doubt they will.
795a8134c1