A chief tool used by industry to deceive was to cast doubt on independent science and scientists. A popular book on misuse of statistical methods, one that I'd read and liked myself, How to Lie With Statistics, turns out to have been part of that effort, as detailed by Tim Harford in his own book, How To Make The World Add Up

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 His unpublished sequel, How to Lie With Smoking Statistics, was paid for by a tobacco-lobby group.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.

Absolute certainty is impossible, that is not an argument to not act. Completely agree.

I don't really understand your argument. Are you trying to say that "How to Lie with Statistics" is wrong? That's an unbelievably bold assertion to make on an engineering-focused site where we regularly work with deceptive stats that the public eats up.

It is deceptive and misleading with an intent to promote specific goals and agenda.

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.

https://en.wikipedia.org/wiki/Sophist

The primary rule of successful propaganda is "Don't lie about facts, control the interpretation."

False facts will get caught out. All you can do with an interpretation is argue about it.

There are various methods. Control is one. The Big Lie another, direct attacks on trust and truth another. Sheer overlwhelming and distraction as well.

You sure? Have you read/watched any news since 2016?

You don't? It's crystal clear to me: that book was paid for, as was its sequel, so industrialists could argue that statistics from independent researchers were not to be trusted. Whether or not the book was right or wrong is not part of that contention.

Wait, are you trying to say it's not wrong?

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.

I think that's taking things a little too far. How I see it, Darrell Huff was a writer, not an academic, and he wrote a number of books over the years about all sorts of stuff.

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.

Even worse, now we have the actual anti-science narrative where, say, the Big Evil Climate Lobby is making up global warming in the hopes of getting more grant money while your friendly neighborhood petrochem megacorporation is just trying to make do and provide jobs and petrol in your tank.

The scientific method is absolutely trustworthy. People, however, are a different story.

It's genuinely hard to know how to make sense of information. I'm generally skeptical of "big anything", whether that's business or government. Incentives can be screwy at any scale, but once you get to very large numbers, incentives seem to simply go off the rails. Industry and governments have a pretty terrible track record of skewing data to suit their needs-- sometimes with a truly tragic consequences.

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.

I don’t know if it is really that incentives change when you get very big, as much as it is that you become more capable of achieving desires that are counter to the public good.

At smaller scales, your power isn’t enough to override the preferences of the masses. Get big enough, and you can.

While not impossible, it’s much harder to create false stats when going through clinical review with the FDA. Super double extra when the lives of the world are at stake and the total eyeballs on a single vaccine are so high.

But the processes are very flawed leading to the wrong stats being used to make decisions.

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.

> For example, an experimental vaccine isn't given out widely till there is good data that it is safe (often taking years).

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 believe that undergoing safety trials with control groups is a bad thing because they take time?

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 the vaccine is causing a drop in IQ, affecting birth rates, etc.?

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.

That's literal whataboutery and FUD.

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.

What other reasonable choice is there?

The US in particular seems to be full of either such naive types (where enterprise, state, science, NGOs, law, etc can do no wrong, and even if something happens, it's just some individual bad apples at worst) or the other extreme (pizzagate-aliens-they're coming for us conspiracy nuts).