How well did they follow the Wisdom of Crowds tenants? (James Surowiecki)
Diversity of opinion—Each person should have private information even if it’s just an eccentric interpretation of the known facts.
Independence—People’s opinions aren’t determined by the opinions of those around them.
Decentralization—People can specialize and draw on local knowledge.
Aggregation—Some mechanism exists for turning private judgments into a collective decision.
I would say this is based on the Matt Ridley book The Rational Optimist? Rational Optimist Book | Matt Ridley
Brier score them?
What is considered the half-life of facts now?
“In an unlikely but conceivable turn of events, what if that scientist becomes infected with the virus, which leads to an outbreak and ultimately triggers a pandemic?” Fauci wrote in a paper reported on by The Australian. “Scientists working in this field might say — as indeed I have said — that the benefits of such experiments and the resulting knowledge outweigh the risks.” National Institute of Allergy and Infectious Diseases (NIAID) Director Anthony Fauci defended “gain-of-function” research in 2012
Flatland for machine learning?
How would you use a Brier score on this going forward? Also ran across this podcast last night on bias. https://knowledge.wharton.upenn.edu/article/want-better-forecasting-silence-the-noise/
Is there a trustworthy confusion matrix on for all the various testing methods? The drive to quote “cases” in a hysterical media seems to be misleading without it. Also a definition of “cases” seems to vary widely.
My other issue is a net deaths versus dyeing from other things previously. Is there a good metric seeing as there is a economic reason to label deaths for Covid over the other usual suspects.
Does any one believe that experts in this field are any better than others? Check out Tetlock’s work on forecasting.
Tetlock decided to put expert political and economic predictions to the test. With the Cold War in full swing, he collected forecasts from 284 highly educated experts who averaged more than 12 years of experience in their specialties. To ensure that the predictions were concrete, experts had to give specific probabilities of future events. Tetlock had to collect enough predictions that he could separate lucky and unlucky streaks from true skill. The project lasted 20 years and comprised 82,361 probability estimates about the future.
The result: The experts were, by and large, horrific forecasters. Their areas of specialty, years of experience, and (for some) access to classified information made no difference. They were bad at short-term forecasting and bad at long-term forecasting. They were bad at forecasting in every domain. When experts declared that future events were impossible or nearly impossible, 15 percent of them occurred, nonetheless. When they declared events to be a sure thing, more than one-quarter of them failed to transpire. As the Danish proverb warns, “It is difficult to make predictions, especially about the future.”
A guy in a cornfield in the Midwest destroyed the rest in a competition of the so called intelligence of Thinktanks, PhD’s, and others that should and were paid to know better.
Narrative – a story that is put above facts, logic, and evidence.
“On what principle is it that with nothing but improvement behind us, we are to expect nothing but deterioration before us?”—Lord Macaulay 1840
For two hundred years the pessimists have dominated public discourse, insisting that things will soon be getting much worse. But in fact, life is getting better—and at an accelerating rate. Food availability, income, and life span are up; disease, child mortality, and violence are down all across the globe. Africa is following Asia out of poverty; the Internet, the mobile phone, and container shipping are enriching people’s lives as never before.
If you listen to those that can only look at their feet but never the sky, check this book out.
Fourth generation nuclear weapons are as many say in the industry are the “technology of the future and always will be”. I understand this is partially a thought experiment, but just to point out that the premise is far from reality.
Molecular laser isotope separation is a much more likely scenario to create fissionable material on the sly. Remember the first atomic bomb to kill people was a howitzer barrel and two lumps of Uranium 235 (not even weapons grade) shot into each other. The amount of material that actually fused would be about the mass of a penny. The tiny amount of fissioned material in little boy was the equivalent of 1.25 miles of box cars full of TNT.
The key to larger and efficient weapons is keeping the radioactive material together longer for more cycles of fission and creating more neutrons from the start. This is done by containment, implosion designs, neutron generators, neutron reflectors, and injecting deuterium and tritium to create more neutrons as the reaction starts.
A truck driver as a hobby built a copy of Little Boy with public sources. As this was easy to do by a single individual why don’t we already have these devices cooking off left and right. The given scenario also assumes that design is the only hurdle. Procurement of materials and concealment aren’t something that AI can teach.
Why would a technology like fusion be more likely than a technology that has been shown to work?
All of these technologies revolve around a huge amount of electricity up front. Governments already watch high electrical use locations for signs of marijuana growers and uranium refinement. Charging the huge banks of capacitors necessary to start a fusion reaction would easily trigger an investigation on anyone but state actors.
I would suggest that machine learning and gene editing using CRISPR technology to create pathogens would be much easier path to a weapon of mass destruction as they can be done far more covertly.
https://en.wikipedia.org/wiki/Molecular_laser_isotope_separation
https://www.youtube.com/watch?v=hlJD0i_WwdQ&list=PLC4FFB9664D0850A0
A playlist of all things Rand...
https://www.galtsgulchonline.com/
Galt’s Gulch Online.
How would you write into your model market psychology?
“What seems too high and risky to the majority generally goes higher and what seems low and cheap generally goes lower.”—William O’Neil
Most of these chestnuts in trading continue to be repeated because of the ground truth in them. What part of the market shows the binary view of most traders euphoria and despair?
How good would have been a pre-mortem as many products in tech get before they are released to the public? https://medium.com/paypal-tech/pre-mortem-technically-working-backwards-1724eafbba02