Category Archives: Intelligence

Nate Silver’s Pandemic Observations As ‘Sharp’ As His Prediction About Trump’s Election

Argument, COVID-19, Intelligence, Republicans, Science, THE ELITES

Nate Silver, a statistician, is a mediocre mind.

In this “glorious commonwealth of morons”—H. L. Mencken’s description, not mine—there are many minds even more mediocre than Silver’s, who hype and highlight his banal observations. In the context of the coronavirus, I imagine this is motivated by their own pandemic politics.

But first, to Mr. Silver’s political prognostications during Donald Trump’s election campaign. As chronicled in my June 29 book, The Trump Revolution: The Donald’s Creative Destruction Deconstructed:

… whether they’re missing the Trump phenom or the casus belli for war in Iraq—America’s deeply stupid, self-anointed cognoscenti recognize truth only once card-carrying members arrive at it independently, grasp and broadcast it, sometimes years too late. Not so the marginalized writers of America. Not in 2012, but in 2002 did we pinpoint the wrongness of the Iraq War. And not in 2016, but on July 19, 2015—when this chronicle began—did some of us, not fortuitously, finger Trump as “a candidate to ‘kick the crap out of all the politicians’” and “send the system’s sycophants scattering.” (August 14, 2015). His appeal, as this writer has contended since late in 2015, transcended left and right, at the time.

Conversely, vaunted statistician Nate Silver ‘calculated that Trump’s support was “about the same share of people who think the Apollo moon landings were faked.”

No wonder Professor Tyler Cowen of George Mason University properly downgraded wonder boy Silver’s intellectual prowess. His prose, ventured Cowen, was a sprawl that “evinces a greater affiliation to rigor with data analysis than to rigor with philosophy of science or, for that matter, rigor with rhetoric,” wrote the good teacher, adding that to him, the Silver columns are “tweener” pieces, “too superficial for smart and informed readers, yet on topics which are too abstruse for the more casual readers.”

(MORE in “The Trump Revolution: The Donald’s Creative Destruction Deconstructed”.)

Now, Nate, that national treasure, is back. This time, he is constructing a straw argument on Fox News, to say nothing of wading into coronavirus politics. I thought he was an objective numbers man?

Nate states the obvious, saying that, “By focusing on coronavirus case counts, the media … makes the numbers look superficially worse … [since]… increases in testing [are what] have led to more cases being diagnosed.”

D’oh! And so obviously true. Does Nate really need to state the obvious? I guess so. (Meanwhile, Silver calls out others for their “boringly conventional positions in … political punditry.”)

The more fundamental point is this: Certainly in the U.S, the coronavirus case count is less significant than the death count: rates and absolute numbers. (Which is why, presumably, Ron Unz highlighted mortality in “The Government Employee Who May Have Saved a Million American Lives.“)

America’s case count, moreover, is scandalously inaccurate. According to the Economist:

Throughout April the number of daily tests has averaged around 150,000, with the share of positive tests staying around 20%. That suggests America is testing only people who are probably infected (in Taiwan, for instance, one in every 132 tests is positive), which in turn suggests that many mild or asymptomatic cases are going undetected. America may have 15 to 20 times more actual infected people than confirmed cases.

That more people are infected is a double-edged sword: More people infected means more people infecting other, but also, we hope, more population-level immunity.

A much more meaningful and reliable number is mortality, death rates and absolute numbers. Right now, the latter stands at 80,037. RIP.

@ The Unz Review.

What Canada’s Outbreak Scientists Knew About WuFlu By December 31 (And The US Was Too Callous and Incurious To Find Out)

Canada, China, COVID-19, Intelligence, Technology

It’s telling that, not the US, but a Canadian company, Blue Dot, was among the first to raise the alarm about WuFlu in late December. It uses an Artificial Intelligence algorithm, which pointed to the suspect wetmarket, then lit up as the infection spread therefrom. Anybody could have purchased this program.

The company, Blue Dot, had no clients in the [intellectually incurious?] U.S.

Come to think of it, the US’s formidable Surveillance State should have known about Blue Dot technology, but I guess the program doesn’t appear to harvest personal data, only anonymized data, thus holding no appeal to the opportunistic overlords referred to reverentially as “the U.S. intelligence community.”

Neither does the Blue Dot computer rely on official statements from state actors in tracking an outbreak. It seems to be a mighty analyst and information aggregator. Thus, by the dates mentioned, “Their algorithm was already churning through data, including medical bulletins, even livestock reports, to predict where the virus would go next.’

Canada should certainly have even fewer deaths from coronvirus given that one of its companies had some of this most sophisticated, foolproof methods to track a pandemic before it hits (Canada likely chose not to stop flights from China, even though it knew the score well before our covidiots):

When you’re fighting a pandemic, almost nothing matters more than speed. A little-known band of doctors and hi-tech wizards say they were able to find the vital speed needed to attack the coronavirus: the computing power of artificial intelligence. They call their new weapon “outbreak science.” It could change the way we fight another contagion. Already it has led to calls for an overhaul of how the federal government does things. But first, we’ll take you inside BlueDot, a small Canadian company with an algorithm that scours the world for outbreaks of infectious disease. It’s a digital early warning system, and it was among the first to raise alarms about this lethal outbreak.

It was New Year’s Eve when BlueDot’s computer spat out an alert: a Chinese business paper had just reported 27 cases of a mysterious flu-like disease in Wuhan, a city of 11 million. The signs were ominous. Seven people were already in hospitals.

Almost all the cases came from the city’s sprawling market, where live animals are packed in cages and slaughtered on-site. Medical detectives are now investigating if this is where the epidemic began, when the virus made the leap from animals to us.

… Chinese officials were secretive about what was happening. But BlueDot’s computer doesn’t rely on official statements. Their algorithm was already churning through data, including medical bulletins, even livestock reports, to predict where the virus would go next.

It was also scanning the ticket data from 4,000 airports.

BlueDot wasn’t just tracking flights, but calculating the cities at greatest risk. On December 31, there were more than 800,000 travellers leaving Wuhan, some likely carrying the disease.

In a matter of a just seconds, the Blue Dot computer can “analyze and visualize all this information across the globe in just a few seconds.”

“The virus wasn’t just spreading to east Asia. Thousands of travelers were heading to the United States too. … Most of the travel came into California and San Francisco and Los Angeles. Uh, also, into New York City. And we analyzed that way back on December 31. Our surveillance system that picked up the outbreak of Wuhan automatically talks to the system that is looking at how travelers might go to various airports around Wuhan.”

The virus spread across Asia with a vengeance. BlueDot has licensed access to the anonymized location data from millions of cellphones. And with that data it identified 12 of the 20 cities that would suffer first.

Dr. Kamran Khan: What we’re looking at here are mobile devices that were in Wuhan in the previous 14 days and where are they now across East Asia. Places like Tokyo have a lot of devices, Seoul in South Korea–

Bill Whitaker: So you’re following those devices from Wuhan to these other cities?

Dr. Kamran Khan: That’s correct. I do wanna point out these are also anonymized data. But they allow us to understand population movements. That is how we can understand how this virus will spread.

To build their algorithm, Dr. Khan told us he deliberately hired an eclectic mix: engineers, ecologists, geographers, veterinarians all under one roof. They spent a year teaching the computer to detect 150 deadly pathogens.

Dr. Kamran Khan: We can ultimately train a machine to be reading through all the text and picking out components that this is talking about an outbreak of anthrax and this is talking about the heavy metal band Anthrax. And as you do this thousands and thousands and thousands of times, the machine starts to get smarter and smarter.

Bill Whitaker: And how many different languages does the computer understand?

Dr. Kamran Khan: So it’s reading this currently in 65 languages, and processing this information every 15 minutes, 24 hours a day. So it’s a lotta data to go through.

Within two hours of detecting the outbreak on December 31, BlueDot had sent a warning of the potential threat to its clients: public health officials in 12 countries, airlines and frontline hospitals, like Humber River in Toronto.

The US was too dumb and callous to buy Blue Dot’s AI program.

MORE: “The computer algorithm that was among the first to detect the coronavirus outbreak.”

Told You So About Testing: Now, Italian Experts Are Getting Testy, Too

Argument, Critique, Europe, Healthcare, Intelligence, Reason

Today, April 17, Dr. Anthony Fauci finally explained what I EXPLAINED on April 9, a week ago, in the column, “Kung Flu Is A Killer, All Right, But So Are The Bureaucrats“:

“… COVID testing [is not] an amulet against the dreaded disease. It isn’t. All testing does is give an individual a snapshot in time of his COVID status. As soon as he drives out of the testing facility, a COVID-free person could become infected. Unless they engage in prevention, a single testing in time doesn’t in any way give individuals a clean bill of health.
Prevention protects people.”

Testing is, however—at this stage of spread—helpful in giving medical researchers a grip on the symptomless-sick phenomenon, as well as an idea of how the disease is disseminated and distributed in the population.

Test and keep testing large enough representative samples, and you’ll get good prevalence data.

Maybe Anthony Fauci got a whiff of what his Italian colleagues in Lombardy were saying, for they preceded his belated, simple, overdue insight about the limits of testing:

“… some doctors at the Italian epicentre of the health crisis doubt that testing is their way out of confinement.”

“It is a nonsense,” Milan’s Polytechnic Institute professor Davide Manca said. “Conceptually, I am sceptical.”

The reason for Manca’s scepticism is plain to see in the math.

Milan’s Lombardy region has 10 million people and 11,142 officially registered COVID-19 deaths.
The economically strong area, the size of Belgium, has been under one of the world’s strictest lockdowns since early March.

Yet Lombardy has been conducting just 6,500 tests daily over the past 10 days.

Manca estimates it would take more than five years for everyone in Lombardy to get tested just once.
“And you need people tested every 15 days for it to have any meaning,” Manca said in a phone interview. [My point here exactly.]”

“Even if you raise that number 10 times, that would still take 200 days for one test. That’s six or seven months.”

“Manca said he still did not understand how the end of confinement would work.”

“Herd immunity is very difficult to achieve with COVID,” the professor said.

“You need 90-95 percent (of the population) to have COVID for immunity. That number is too high to reach.”

More candidly, in Italy, they are not talking dishonestly about “opening up the country.” They are talking about “coexisting with the coronavirus.”

Well, yours truly beat the good doctors to it on April 9, with “Kung Flu Is A Killer, All Right, But So Are The Bureaucrats.“

However, these medical heroes were busy saving lives. Bless them.

* Photo by Miguel MEDINA / AFP

Mainstream Is Catching Up With Mercer On Masks, N95 & Surgical

Argument, Healthcare, Intelligence, Journalism, Media, Pseudoscience

I try to tell people This Column is always ahead of the curve, in war and peace, and that, sometimes, they ignore the analysis offered here at their peril. Alas, most covidiots I know insisted on relying on their “smarts,” refusing to delegate their thinking.

The covidiots insisted that, because the “experts” had said so, masks were futile. But on March 5, this column unpacked the lies and illogic underlying the contention that masks (surgical & N95) were worthless:

While the coronavirus is indeed minuscule, smaller than 0.3 microns (likely between 0.1 and 0.2 microns), COVID-19 is delivered in a larger medium of bodily fluids or spray. Certainly, some barrier to the spittle in which the coronavirus is dispersed is better than none.

No surprise then, that world health authorities can’t seem to get their story straight on masks. At times, they concede “that N-95 face masks are protective.” More frequently, they scratch the proverbial proboscis (ostensibly a sign of lying) and say “No, of course, they’re ineffective.” In other words, “they work for me, the healthcare worker, but not for thee.”

For honesty’s sake, the country’s health-care functionaries might appeal to consumers on the ground of dire shortages. But on the basis that no protection is better than some protection? Please! …

THERE’S MORE. READ on: “Unmasking Statist, Socialist Propaganda About ‘Face Masks,’” March 5.

What do you know? Mainstream is, 23 days later, catching up. Writes the New York Post: “Experts say face masks can help slow COVID-19, despite previous claims.”

As my mom likes to say, “Good morning, Elijah.”

The expert always knew this to be true, they just misled the Covidiots, who willingly partook in the charade. (Who will hold the liars accountable?)