>industry steamrolled the science.
Not only that, industry paid for "science" that hid the dangers. People today however seem to strangely think this doesn't happen anymore.
Not only that, industry paid for "science" that hid the dangers. People today however seem to strangely think this doesn't happen anymore.
https://timharford.com/books/worldaddup/
The ultimate cautionary tale here is Darrell Huff’s 1954 classic, How to Lie With Statistics. Huff’s book is clever, insightful, and impish, and it may be the best-selling book about statistics ever written. It is also, from cover to cover, a warning that statistics are all about misinformation, and that one should no more believe in them than in stage magic. Huff ended up testifying at a Senate hearing that the evidence linking smoking and cancer was as spurious as the evidence linking storks and babies. His unpublished sequel, How to Lie With Smoking Statistics, was paid for by a tobacco-lobby group.
https://www.theatlantic.com/ideas/archive/2021/03/the-conspi...
People are very well aware that the war over what is truth and real continues to be fought. And that it is not merely corporations engaged in it, as control over truth and perception is at the heart of power. "All warfare is based on deception."
https://suntzusaid.com/book/1/18/
As a hint, if one side has a long record of lies, and another a long record of honest relations and owning their errors --- the smart money takes counsel from the second. It's wise to assess one's own sources on this basis from time to time.
It was specifically paid for and used to cast widespread doubt on smoking leading to lung cancer. It tried to convince people that "the science isn't settled" when the evidence was overwhelming.
It's an incredibly disingenuous and cynical piece of work that posits truth does not really exist b/c all "experts" are just lying to you with an agenda. Therefore, you can't ever really know the truth, therefore keep smoking.
The salient characteristic of propaganda is not that it is (entirely) false. It is that it serves a specific interest and agenda rather than being a good-faith, best-effort attempt to convey truth.
It's a fundamental conflict in communications dating at least to Plato and the philosophers vs. the sophists.
Propaganda is most effective when it wraps its intended payload in an attractive, largely truthful message, and acts to nudge its intended targets in a direction they're inclined to go already.
False facts will get caught out. All you can do with an interpretation is argue about it.
I presume he got a bee in his bonnet about statistics at some point, and wrote his 'How to lie with Statistics' and because this became such a hit, it was assumed he know what he was talking about, and hence the interest from the cigarette manufacturers, the senate etc. This in fact was a mistake, and his credentials for appearing for the senate should have been checked.
So, the key take away from the book for me is that Statistics is hard, it's easy to confuse yourself or produce dubious results, but i'd look elsewhere for information about how to avoid pitfalls, and how to spot dubious conclusions beyond the most simplistic manipulation he points out.
That's why my initial stance on COVID vaccines was to be skeptical of the industry claims. This lumped me in with a lot of quacks, and with a political (US) group with whom that I don't normally align much.
It's been a strange few years. At this point, I'm not sure I know how to strike a balance between healthy skepticism and paranoia. Regarding the vaccines, I'm fully vaccinated, as enough time has passed to get me to a place where I think the stats bear it out.
At smaller scales, your power isn’t enough to override the preferences of the masses. Get big enough, and you can.
For example, an experimental vaccine isn't given out widely till there is good data that it is safe (often taking years).
However, for risky diseases (like COVID), as soon as there are even rough indications that it is safer than COVID, it makes sense to give it to everyone. Every month you spend doing more safety tests, millions of people die.
The same is happening right now for malaria treatments which are being trialled. Skipping the trial and handing it out untested will probably save more lives.
How is this an example of “the wrong stats being used to make decisions”? You believe that undergoing safety trials with control groups is a bad thing because they take time?
> However, for risky diseases (like COVID), as soon as there are even rough indications that it is safer than COVID, it makes sense to give it to everyone.
What if we find out several years down the road that the vaccine is causing a drop in IQ, affecting birth rates, etc.? Wouldn’t it have been nice to catch these things during the safety trials before injecting it into billions of people?
You can always do more trials and more studies, but at some point the cost of delays outweighs the risks. A blanket "this is the degree of safety testing needed" for every single intervention makes no sense if the cost of that testing differs significantly — and when you have a rapidly spreading disease killing millions of people, the cost of delays is much higher than it would be if you're trying to cure the common cold.
No testing at all would be a really bad idea, but "we'll spend just as long testing this one as this as we would on a common cold vaccine" is also a really bad idea.
I'd also drive faster if I were rushing to the hospital with a dying friend, even though speeding is risky. You have to weigh risks and benefits and do what has the best expected outcome.
What if we find out several years down the road that COVID-19 does these things? We have a better grasp on the potential side effects of the vaccine—which, after all, is much simpler than a virus—than we have on the potential side effects of the disease.
Covid is a relatively known relatively high risk which has killed millions and left tens of millions injured.
A vaccine may cause problems. Possibly. Or it could also not cause problems.
So far there is no evidence to suggest that problems are particularly likely, or that they have been happening at all at significant risk levels.
The rational decision - clearly - is to deal with a severe immediate threat. Not to worry about something that shows no signs of happening because what if maybe perhaps could happen y'know.