News bits & chunk: The latest impeachment; Regarding high drug costs; Predicting the future

The New Republic reports about why cynical, morally rotted authoritarian House Republicans impeached Mayorkas:

On Tuesday, Republican Representative French Hill announced the party’s bald-faced political motivations for impeaching Mayorkas. .... “We need to shut the border.… The president could take executive action to do it today—doesn’t need more money. It needs action, and this is what’s disappointing to people, and that’s why Mayorkas is gonna pay this public relations price by being impeached for the first time since 1876,” Hill said. Notably absent from Hill’s explanation was any description of high crimes and misdemeanors committed by Mayorkas.

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We all know this, but it bears repeating. Ars Technica reports about a report about outrageous drug prices in America:

Big Pharma spends billions more on executives 

and stockholders than on R&D

Senate report points to greed and "patent thickets" as key reasons for high prices

When big pharmaceutical companies are confronted over their exorbitant pricing of prescription drugs in the US, they often retreat to two well-worn arguments: One, that the high drug prices cover costs of researching and developing new drugs, a risky and expensive endeavor, and two, that middle managers—pharmacy benefit managers (PBMs), to be specific—are actually the ones price gouging Americans.

Both of these arguments faced substantial blows in a hearing Thursday held by the Senate Committee on Health, Education, Labor and Pensions, chaired by Sen. Bernie Sanders (I-Vt.). In fact, pharmaceutical companies are spending billions of dollars more on lavish executive compensation, dividends, and stock buyouts than they spend on research and development (R&D) for new drugs, Sanders pointed out. “In other words, these companies are spending more to enrich their own stockholders and CEOs than they are in finding new cures and new treatments,” he said.  

A report this month by the US Department of Health and Human Services found that in 2022, US prices across all brand-name and generic drugs were nearly three times as high as prices in 33 other wealthy countries. That means that for every dollar paid in other countries for prescription drugs, Americans paid $2.78. And that gap is widening over time.  

The powerful pharmaceutical trade group PhRMA, published a blog post before the hearing saying that comparing US drug prices to prices in other countries “hurts patients.” The group argued that Americans have broader, faster access to drugs than people in other countries.

Right, comparing US drug prices to those in other countries hurts patients. Just like it is not time to discuss gun safety laws right after another school massacre with an AR-15 freshly bought by a known enraged freak who should not be allowed to own a gun. Got it. 

 

Bernie raging against the machine

(the machine ignores him, then giggles and raises prices)

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An article Vox published discusses the art and science of predicting future events. It really is a combination of art and science and most “experts” (pundits, academics, corporations, lobbyists, etc.) are so bad at it that statistical analysis of their prognostications, show they are barely better than random guessing. Just a squeak better. 

Vox writes about a group of extraordinary human prognosticator freaks calling themselves the Samotsvety group. Samotsvety was the name of a Russian rock group of 50 years ago. I posted about this prediction phenomenon before, e.g., here and here. 

People with extraordinary ability to predict future events were called Superforecasters. The Samotsvety group, a recent phenomenon, are the best of the best Superforecasters. My guess is that maybe about 1 in 10 million people have this talent, whether they know it or not. My estimate is that probably about 1 in 10,000 to 100,000 people have regular Superforecaster-level talent. These Samotsvety people are truly extraordinary. Dylan Matthews at Vox writes:

How a ragtag band of internet friends became the 

best at forecasting world events

I wanted to hang out with Samotsvety for a bit because they were the best of the best, and thus a good crew to learn from.

They count among their fans Jason Matheny, now CEO of the RAND Corporation, a think tank that’s long worked on developing better predictive methods. Before he was at RAND, Matheny funded foundational work on forecasting as an official at the Intelligence Advanced Research Projects Activity (IARPA), a government organization that invests in technologies that might help the US intelligence community. “I’ve admired their work,” Matheny said of Samotsvety. “Not only their impressive accuracy, but also their commitment to scoring their own accuracy” — meaning they grade themselves so they can know when they fail and need to do better. That, he said, “is really rare institutionally.”

A common measure of forecasting ability is the relative Brier score, a number that aggregates the result of every prediction for which an outcome is now known, and then compares each forecaster to the median forecaster. A score of 0 means you’re average; a positive score means worse than average while negative means better than average. In 2021, the last full year Samotsvety participated, their score in the Infer tournament was -2.43, compared to -1.039 for the next-best team. They were more than twice as good as the nearest competition.

The literature on superforecasting, from Tetlock, Mellers, and others, finds some commonalities between good predictors. One is a tendency to think in numbers. Quantitative reasoning sharpens thinking in this context. “Somewhat likely,” “pretty unlikely,” “I’d be surprised.” These kinds of phrases, on their own, convey some useful information about someone’s confidence in a prediction, but they’re impossible to compare to each other — is “pretty unlikely” more or less doubtful than “I’d be surprised”? Numbers, by contrast, are easy to compare, and they provide a means of accountability. Unsurprisingly, many great forecasters, in Samotsvety and elsewhere, have backgrounds in computer science, economics, math, and other quantitative disciplines.

That leads to another commonality: practice. Forecasting is a lot like any other skill — you get better with practice — so good forecasters forecast a lot, and that in turn makes them better at it. They also update their forecasts a lot. The [China invades] Taiwan numbers I heard from the team at the start of our meeting? They weren’t the same by the end. Part of practicing is adjusting and tweaking constantly.

The article is quite long and discusses all of this and more in greater detail. 

So what?

I post this as just a reminder about how error-prone, most (~99.99% ?) self-professed pundits, opinionators, experts, cable news blowhards, demagogues, kleptocrats, blind, raging ideologues, preachers, politicians and the like are telling us when they bloviate and tell us they know what their ideas will do for our own good in the future. They are usually wrong, often lying, often ignorant or misinformed. That is why it is so rare for such people to track their own success and failure rate. They know they are mostly full of crap or simply bullshitting. They will never track their own professional performance, much less make it public. In fact, our media and political systems tend to reward blowhards who are confident in their usually over-simplified and/or distorted simplified, nuance-free narratives. They are rewarded not because they are right, but because they seem credible, attract attention and/or are convincing. 

And they want us to trust them? Pfft.