All models are wrong, but some are completely wrong
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No matter how many variables you include, you can never capture the utterly massive and unpredictable amount of variables that exist in reality. But they're not supposed to. They're tools that are supposed to be used to help get an idea about how something might happen, that's marginally better than just guessing, due again to models always being incomplete, despite any amount of best efforts.
Like any tools, using models incorrectly, fucking around with them until you just get what you want to see or using the wrong one for the wrong task can be potentially dangerous, especially when those models are used to guide large decisions with serious consequences and impacts.
Reasoning and common sense need to be used alongside models and if the models don't seem to reflect reality, the problem is with the model and not reality and the model needs to be adjusted or thrown out otherwise continuing to use it will just lead to lousier and lousier decisions.
If you tell people you don't know what causes their respiratory illness, they may think you are incompetent, and feel helpless.
If you tell them they have acute bronchitis, suddenly they feel empowered. It just means they have an inflammation of the bronchi. It says nothing of the direct cause, nor the indirect cause: a virus, tobacco, dust, air pollution or asthma. It says nothing about how bad it is. They don't even know really what it implies for their body or their treatment.
But now they think they know.
Call something a democracy, and nobody will check if it is.
Call something a privilege, and people will start to want it, working hard for it.
Models can be used to help your interact with the world. But they are also used to avoid interacting with the world: if you use them as labels, instead of comparing the model with reality, you get a shortcut to take decisions. It becomes a mere name to justify a decision process instead of a tool for the decision process.
While technically bronchitis could be any inflammation of the brochial tubes, a diagnosis of bronchitis usually means that that it's the patient's major problem. It'd be odd to describe a cancer as "bronchitis" even if it involved brochi. So you do learn something, in a Griceian sense, from the relatively uninformative diagnosis. There's also the implication that there are some tools for managing it, the doctor's seen it before, etc all of which are reassuring.
Agreed, on the medical front this also leads to a focus on sophisticated diagnostic tools and numbers versus a 'true' cure.
>Call something a democracy, and nobody will check if it is. >Call something a privilege, and people will start to want it, working hard for it.
Let me add one more to the list. Call something a 'right' and people feel denied if they are not given it. Eg. voting rights. Even where one can vote, consent is generally manufactured but people feel empowered when they vote.
Let's enumerate rights: "Life." Okay. "Liberty." Gotcha. "Pursuit of happiness." Yep. "Private property." Might need some asterisks on that one, but sure. "Carry a weapon around in case I might need to murder another human being very quickly." ???
It's been this incredible PR campaign based around the fact that people are illiterate and don't know what "bear arms" means (jargon for "serve in a militia"[1].)
In legal terms, the standard for restrictions on free speech in US is "strict scrutiny" for this exact reason. So while we have time and place regulations, there are also many safeguards in place to ensure that those aren't abused. To give one example, permits can only be required once disruption reaches a certain level (e.g. a solo demonstration on a sidewalk shouldn't need one), and for cases where fees are associated with said permit, it cannot be imposed on somebody unable to pay, or for whom it would be a considerable burden.
I can assure you that the vast majority of proposed gun control legislation would not pass strict scrutiny. This is evident even from the degree to which policies vary in other countries - for example, when it comes to "assault weapons", the definitions vary significantly even in US state laws. Yet there's no obvious correlation with any practical effects if you compare, say, UK (which bans all semi-autos) and Germany (where you can own an AR-15).
The laws that do seem to matter are mostly those regulating the owners directly, and even then it depends a lot on the policy. E.g. universal background checks for each purchase sound rational in theory, but evidence on their effectiveness is lackluster. OTOH a license to possess, that has to be periodically renewed, has a much more profound effect.
Czechia is a particularly interesting case, being very permissive wrt "what" - comparable to US, even with shall-issue concealed carry! - but much more stringent on "who", and this seems to work just as well as UK's tight-fisted approach: https://en.wikipedia.org/wiki/Gun_law_in_the_Czech_Republic#...
But the history of comments is certainly not dull. Look at my profile, and see if the link mentioned in it catch your fancy, if it does, shoot me an email.
Psychology in particular seems to have come to the conclusion that if you can name an assortment of 4 out of 10 symptoms, that counts as having identified single disease.
I think part of the problem is that we're so good at applying various techniques that no one bothers to think anymore.
One path of medicine closest to that sort of symptom vs disease separation being practical is phage therapy. It could be called true alternative medicine as an actual alternative as opposed to a euphemism for "false or unproven" but is generally less practical in spite of its other virtues. Because a proper phage needs to be selected per target pathogen. As opposed to not caring what strain of virus it is and just treating the symptoms so the patient can recover and not die.
In the The Imaginary Invalid (17th century) Molliere makes fun of it. Doctor explains how opium works through its "dormitive virtue."
We all know that hill climbing algorithms are often naive and sometimes hilariously wrong. Nobody will disagree with you about this, until you start talking about prioritizing work, and then everyone vigorously defends their favorite hill climbing algorithm, from task management to performance tuning.
My preferred strategy for optimization more closely resembles how a fruit grower would pick fruit, and the term, “low-hanging fruit” galls me because you would go bankrupt using that strategy. And probably lose most of your trees to disease. It could be a quite good analogy, if the lessons taken from it weren’t just so childishly naive.
We miss a lot of opportunities, and not taking them has lingering consequences.
Plenty of that going around.
Perf analysis was how I got through some of my most mundane college homework assignments instead of (or sometimes, in addition to) procrastinating.
Then during my formative years I saw the following script play out several times:
Management and sales have a problem. They say the customers are upset that the code is so slow (maybe the customer has expectations, or maybe a competitor or their old system went a lot faster). It's taking 300 units of time now and they think it should take 100. So the leads and the heavies wander off and come back with 20% easy, the next 10 harder, 6, 4, and then they declare that they've done all they can. So now we're around 180 units of time. That's all the customer gets. See this <flame chart precursor> chart? Everything is nice and flat. Our hands are tied now. Business is... not happy. They're glad they have something to show the customer, but it's really just a bone.
So between tasks I'd start poking around, because why not. A pinch here, an architectural tweak there, and maybe 25% just gruntwork, and I'd find another 40% out of the "we've done all we can" code, which is just a hair away from what the business asked for.
You can imagine that you invite a tremendous amount of well-deserved scrutiny on yourself doing stuff like this. But that's okay: the most important part of optimization is not the code speed but the bang for the buck. You can certainly interpret "Low hanging fruit" to fulfill that concern, in practice most people don't (for some, lack of imagination, for others, ego-protection). But once you consider everything, including, for instance, externalities on QA, or the misapprehensions of customers who expect every release to be faster... there are a lot of more complicated things to worry about than how to rearrange this block of code to improve branch prediction. Not touching it for 10% is just a heuristic.
When you are way over budget, every cost needs to go on the table, but your end goal is one of the most important pieces of information. That should go on the wall, in large block letters.
Look at a real budget. If you are deep in the red, it doesn't matter that your car is only 10% of how much you spend a month. What matters is that the car is 25% of your target. That is a ridiculous amount to spend on your car, even though your house is way more. Even if you spend an ungodly amount on dry cleaning or coffee, you're going to have to trade down for a cheaper car. You don't need charts to tell you this. In fact all the charts can do is convince you that nothing needs to be done. They allow you to bargain.
Therefore, I don't give a shit if you think that this function which accounts for "only 5%" of the current run time "is fine". It's 13% of our time budget on some mundane task that doesn't really make us money. It is not fine. You cannot justify 1/8th of our budget for this thing. It's gonna be fixed, and if you have no idea how, you'd better start thinking about it now, because we're gonna come back to it soon and if you don't have a solution then you might find that code is now someone else's responsibility.
But I said something about the 'fruit tree' analogy and I'm a full page of text in without a peep.
So the thing is that when you're thinking about big budgetary changes, it's more manageable to do it one subject matter at a time. Pick a 'ripe' area and glean it for everything it's worth. So I might pitch that I think I can get 30% improvement out of the edit/update code. Can I have this much time to do it? Okay. I might get half of that goal in the first couple weeks. Half of the rest in the next, but at the end of it, the last thing I touch is probably only going to get 3%. But 3% is 10% of what I promised, so I can justify it, and if they aren't complaining about the timeline, I may try to squeeze in some 1-2% things at the end in a way I can pull the plug if it looks too risky.
The important thing to note here is that it will never, ever be as cheap as it is right now to touch that 3% code. Everyone is already thinking about it, everyone knows to keep an eye on it, and new test plans are being developed, documentation and customer training plans are being updated. If I don't touch it now, that target of opportunity might never come again. That 3% plays out everywhere in the code, and I will never be able to get budget to fix any of them (I'll have to sneak them in on a refactor or leave them forever). A dozen of these is not that hard to end up with, and our code is 40% slower than it could be (or worst of all, than a competitor). If that's just the time for a button click, fine. If it's on our slowest operation and things time out, customers with larger data can't function, or they have to buy the absolute most expensive machines instead of slightly better than average? That's not fine. But everyone feels perfectly justified in never doing anything about it.
Next release, I can pitch for 25% in some other functional area, and another, and another. Last time I did this, it took over 20 months before I ran out of functional areas to work on. Every release for 'years' was faster than the previous. At the end, I knew that code better than anyone (an important point I omitted - focusing that intently on one section teaches people a hell of a lot about the code they otherwise would never know). I probably could have swung through for another 10% in every area, but by then I was ready for a new gig.
We probably should be repeating that a lot to make sure people hear it.
Yes, absolutely. If an epidemiologist identifies and models a trend in human disease around substations, or a trend in failures of substations, or a new way of modeling the ways electrical demand can change over time and influence demand in other times and places, etc., then their input should absolutely be considered.
Just as it's annoying when a total outsider claims to know everything about a field, it is equally problematic when insiders refuse to acknowledge anyone on the outside.
It may be time to add a third error category[1]
I. False positive
II. False negative
III. Deliberately skewed off the map for propaganda reasons.
[1] https://en.m.wikipedia.org/wiki/Type_I_and_type_II_errors#Ty...
You'd want health organizations around the world to be publishing every possible detail (anonymized) so that the disease can be better understood. Yet three months in, with over a million cases worldwide, we still have experts disagreeing about things like asymptomatic transmission, use of masks, droplets vs. aerosol, how much distance one should stand from another, viability on surfaces, etc. etc. Even for treatment options rather than insisting on randomized double blind trials start by using the natural experiments that are already happening.
We should have the data to answer a lot of these questions (or at least draw out some probability distributions), or at least someone has it. This stuff is going to be critical in informing exit strategies.
If you're publishing every possible detail, then your data isn't anonymized. Anonymization consists of the removal of almost all of the details.
The headline "Coronavirus may have infected half of UK population — Oxford study” is not really out of line with the preprint the article talks about. What's questionable is that it was a good idea to write about the preprint at all.
"Importantly, the results we present here suggest the ongoing epidemics in the UK and Italy started at least a month before the first reported death and have already led to the accumulation of significant levels of herd immunity in both countries."
"Our overall approach rests on the assumption that only a very small proportion of the population is at risk of hospitalisable illness. [...] Three different scenarios under which the model closely reproduces the reported death counts in the UK up to 19/03/2020 are presented in Figure 1 . [...] [In two of those scenearios] By 19/03/2020, approximately 36% (R 0 =2.25) and 40% (R 0 =2.75) of the population would have already been exposed to SARS-CoV-2. [...] [The third scenario] suggests that 68% would have been infected by 19/03/2020."
The secondary headline “New epidemiological model shows vast majority of people suffer little or no illness” was much worse as that's the assumption in the model and not the result. It was changed to "New epidemiological model shows urgent need for large-scale testing" in the amended article.
> Since its publication, hundreds of scientists have attacked the work, forcing the original authors to state publicly that they were not trying to make a forecast at all.
"Attacked" sounds as if the criticism was unwarranted.
I agree with you completely, but the flip side of the coin is that experts can be blinded by assumptions that the field has. Sometimes outsiders aren't aware of these basic assumptions and so are less biased.
There's also the simple issue that sometimes expertise comes from places you least expect for reasons you might not anticipate.
For me there's as many problems in this pandemic related to appeals to authority (at least in the US) -- problems with testing related to FDA regulation and the CDC, problems with lack of healthcare providers due to long-term rent-seeking monopolies in licensing and practice scope, problems related to academic fraudulence and incentives (see: Didier Raoult) -- that I think it's dangerous to raise appeal to authority as anything but a bias.
For me there's multiple levels of problems to this, the first of which is the conspiracy and anti-science culture surrounding the pandemic. Above that is an appeal to medical and scientific expertise and authority that has sometimes been helpful but sometimes harmful. Above that still is an appeal to rigorous thinking and risk management, which transcends expertise boundaries.
Likewise now with hydroxychloroquine--if you listen to the epidemiologists all you'd hear is how it's an UNPROVEN drug. What we need instead is coverage of sample sizes, p values, bayesian predictions of effectiveness (in the absence of controlled studies) and serious modeling of the number of ICU beds and ventilators required with and without various levels of treatment, from emergency care to prophylactic use.
The epidemiologists have their head in the sand and think we can just wait 6 months for a proper set of randomized trials. It's the less attached data modelers you need to turn to get predictions that are useful for effective policy choices.
https://thehill.com/changing-america/well-being/prevention-c...
Which model? Your article mostly dwells on the Oxford model in the FT which is as mainstream as it gets. The Daily Mail article is about a prediction by an Imperial academic.
There doesn't appear to be any "mainstream" in epidemiology. This kind of false-consensus argument is one I've seen before and frankly it undermines people's respect in both academic and journalism. How exactly is the "mainstream" established, in your mind? And don't talk about vague, easily manipulated non-metrics like reputation. Mainstream models should come from a single thing: success. Your insistence on rigid academic segmentation is the very thing that makes academia brittle and riven with non-replicable papers.
You know which kind of modellers I respect the most? Actuaries. They have skin in the game. They don't try to predict pandemics or sell insurance products against them, implying they think pandemics can't be modelled. So far based on what I've read about the history of epidemiology, I can't disagree with them.
https://www.newyorker.com/news/q-and-a/the-contrarian-corona...
You're requiring cooperation from multiple different parties here (scientists, journalists, policy makers, readers, etc.) and any of these parties can warp the results in any number of ways regardless of the cooperation of other parties.
Climate science still hasn't solved this problem despite trying to implement what you're talking about.
It's an age-old problem, if a priori you're looking for something hard enough you're bound to find it.
The number of people who agree with something tells you, as a rational person, practically nothing - it reminds me of the absurd compilation argument “One Hundred Authors Against Einstein”: https://archive.org/details/HundertAutorenGegenEinstein/mode...
Einstein’s famous reply: “If I were wrong, then one would have been enough!”
I prefer though to look at problems through the lens of incentive structures (keeping in mind humans generally heavily time discount incentives and what incentivizes people is not always obvious! Death isn't always much of a disincentive beyond a rather short time horizon). And here I'm having a hard time seeing easy ways to tweak the incentive structure.
Which is fine. It'd be far better if people weren't trying to model COVID-19 at all. It's clearly far beyond our societies capabilities today. We can't even get useful data let alone feed it into a simulation of society.
I think in fact it would be better to go even further: not speak from a position of superiority (even if one knows more), but try to acknowledge the audience and persuade effectively. Here's a recent article on the topic: https://undark.org/2020/03/19/coronavirus-myths/ and here's one of my favourites (in a different field of science) from three years ago: https://deansforimpact.org/why-mythbusting-fails-a-guide-to-...
If that scenario was “completely wrong” too, it seems like it would serve as a perfect example of the consequences of this kind of (still hypothetical) misinformation.
As we should expect, because data scientists and quants are EXACTLY the people with the set of skills necessary to make such predictive models. At best, it's an ancillary skill for epidemiologist, and we've seen many cases in this pandemic where they have wielded these tools incorrectly.
Given that "people with background in infectious diseases" have largely failed, as a group, to warn us in January-February about this pandemic (see this Twitter thread for a slew of concrete examples https://twitter.com/RokoMijicUK/status/1246509433145917443), my conclusion is that unless someone has a background in hard quantitative field (regardless of what that field is), that person should not be let anywhere near quantitative models.
What I have found, so far, is that if we look at current daily growth (averaged over seven days) and use exponentiation to predict future growth based on the previous week’s figures, the numbers are too high (usually by a factor of two, but the error amount is all over the place).
Point being, we’re seeing a more complicated growth model than simple exponential growth; the actual growth is lower.
My work so far is on GitHub: https://github.com/samboy/covid-19-html
This is a work in progress and I’m nowhere near being able to make a simple easy to read graph showing a reasonable projection of COVID-19 growth in the United States.
https://docs.google.com/spreadsheets/d/1PqMVPU0VYcDWrUnDh1Cs...
Basically, it uses the fact that mean time from contagion to death is 17,3 days. For France, it gives reasonably accurate predictions. Best than almost any other model I've seen, in fact.
Collectively many people seem to be referring to that as "curve flattening", but my understanding is that flattening the curve means slowing the growth rate overall, so that it takes us longer to reach peak daily new cases. It is not intended to indicate a particular point along the x axis. In fact if we are actually flattening the curve, it will take us LONGER to reach our peak. Also, its difficult to measure whether we have been successful or not, because the only thing we have to measure against would be hypothetical worse case scenarios.
What we do know is that "doomsday style" models from IHME that just last week were predicting 50K beds needed in NY are off by a factor of 3-4, and hospitalization are starting to flatten out already. You can guess the direction they were wrong in. And before you start an uninformed argument, yes, these models assume the current isolation measures.
In the meanwhile NY hoarded the ventilators and medical supplies because it anticipated this prediction to be true. To be clear, I don't blame NY - they used the best information they had, which turned out to be bullshit. Better be safe than sorry.
These are not harmless errors. When this is over, someone should study these fiascos and estimate the death toll just from bad models alone.
1. Scientific literacy is super low in the general population.
2. Motivated reasoning is rampant. People will believe anything that enables them to do what they wanted to do anyway.
This is an important point. Scientific scrutiny is extremely important, but there is still a difference between a judge that is stern but fair - and one that actively wants you to fail.
Motivated reasoners have no problems holding opposing parties to impossibly high standards while accepting claims without any evidence as valid arguments for their side.
Today, climate scientists have learned the lessons and improved communication and modeling considerably, even to the point where we now how "attribution science" we we can discuss climate change in the context of particular weather events. We also start seeing changes in weather patterns that are hard to ignore even for laymen.
Nevertheless we are still having the same discussions as before.
Hard to ignore by motivated reasoners! Changes in weather patterns observed by individuals using their own experience are not evidence of global climate change. If there's science showing that, then yes, but personal experience doesn't add any value to the conclusion, it just reinforces whatever the person already wants to believe.
Or do we? This sounds like a Fermi problem
https://en.wikipedia.org/wiki/Fermi_problem#Explanation
I may be wrong, though.
https://www.nytimes.com/2015/08/24/opinion/the-case-for-teac...
I kind of disagree with this point. The models we see are mostly statistical models. Anybody with a statistics background (mathematician, physicist, chemist, biologist, engineer, computer scientist, epidemiologist) can have enough of an understanding to make valid points.
Discarding opinions based on somebody's background is an argumentative fallacy in and of itself. You should of course check if somebody is trustworthy, but epidemiologists should be scrutinized under this aspect like everybody else.
No, this isn't enough. This whole way of thinking isn't enough. It's a big part of the reason for the current situation.
Journalists should report what's true, not what Tom, Dick or Harry said. If a journalist isn't qualified to make object-level claims on a given topic, don't write on that topic. For example, if Bob says there's a forest fire, then instead of publishing "Bob says there's a forest fire", you must do enough legwork to tell your readers "There's a forest fire" or "There isn't".
I allow myself to ignore all journalism that don't follow that guideline, and it makes me happier.
- 3 million people lost their jobs <citation link>.
- 3 million people lost their jobs, according to <expert>
- 3 million people lost their jobs, according to <expert>, while <another expert> estimates as many as 5 million during the same time frame.
Which one of these is the best framing of "the truth?" Because rarely is something worth reporting on some axiomatic statement of fact. Not only because boolean states don't normally exist - they're not compelling.
A journalist's job isn't just to tell you something happened. But to give you understanding and context, and make it compelling. What you're asking for is Wikipedia, not the news.
What you can do is write an article about projections of how many people will die. In it you talk about the data sources being used in the model(s), the assumptions being made in the model(s), and the result they give including likely major sources of error..
You can put more or less detail depending on your audience. But it should always include enough detail that your audience understands that it is an estimate based on assumptions and likely flawed data, and you should always understand the model you are writing about even if you don't explain it.
Instead of journalists demonstrating the effect of Dunning-Kruger in a manner similar to what many computer scientists and engineers love to do about unrelated fields, they should rather listen to the experts and try to gather multiple opinions in order to triangulate what is probably correct.
2) What you are describing is exactly what I mean: There are dozens of experts ("engineers") who have done their calculations but have come to different conclusions. To presume, as a journalist or expert, one's own calculations will provide the "truth" in such a situation is not only extremely arrogant but also, when it comes to a pandemic, extremely dangerous.
It reminds me of that electrical engineer at Imperial College who thought epidemiology is a cake-walk and wrote a paper predicting 5000 deaths in the UK, which stood in stark contrast to that modeling effort by a large group of actual, renowned experts in the field (epidemiologists, virologists, public health scholars) also at the Imperial College, whose estimates have at least estimated 20,000 deaths. The electrical engineer had to quickly backtrack on his claims after hundreds of scientists wrote in. Now imagine, every journalist would do that and directly publish it. That would be far worse than an article that brings up that 5,000 deaths study but also mentions other estimates.
Especially they should not give 33% plausibility to Tom, 33% to Dick and 33% to Harry. Which is what they typically do, and call that "professional journalism."
If Tom represents 95% of scientists and Dick and Harry the fringe 5% also financed by (let say) tobacco industry or oil corporations, or Boeing, or those paid by the CIA, they should not even mention Dick and Harry in the same article (or TV a show), especially not in anything worth a major headline. They should appear with the smallest possible note in some smallest possible corner and with the title like "oil corporations paid these persons to support them again."
Sadly, but that sounds like a dream. The world would be very different then.
What actually happens is this:
1. Journalists have a story they want to write. They probably already decided what the message is going to be, but let's be generous and assume they didn't.
2. They consult a rolodex of, almost exclusively, government funded academics. This is true even if the story they're writing is about activity or science that takes place only in the private sector and for which the academics in question have no actual experience. They may consult two or three grant funded academics if they want their story to seem especially robust. If they give the private sector a chance to reply at all (often not) they will cite one or two sentences of a brief phone call in which the person being talked to doesn't know what they're trying to defend themselves against and is probably just confused. It's not a real interview with an actual in-house expert.
3. This story is then published as "Experts say, ..." even if what the chosen experts say flatly contradicts common sense or things that can be checked with 10 minutes and a search engine.
4. Readers comment below the line, pointing out the flaws in the story. If a specific company is involved, they may do a blog post explaining their side of the story which the journalists will either completely ignore, or if they think they can get away with it, selectively quote one or two sentences in a misleading way.
Industrial scientists/engineers are sometimes assumed to be inherently evil and untrustworthy. But the whole idea that journalists are untrusted because they very rarely quote people in industry is a saw of the left; it's not true, which is why the examples given always seem so curiously weird and out of date. Tobacco industry? when was the last time you even read a newspaper article about them? Oil corporations? Those firms that have spent the last 15 years rebranding themselves as energy companies because they now make solar panels too?
There's a lot of really good analysis of the trouble journalism has got itself in for, and a significant part of the blame is laid at the feet of journalists uncritically reporting anything academics say as the Whole Truth and Nothing But The Truth, when in fact they routinely contradict each other, make up statistics, report obvious common sense as "findings", are hugely over-confident in their own predictive abilities, mis-use statistics and so on.
A good book to read on the topic is "Wrong" by David Freedman:
https://www.goodreads.com/book/show/8134625-wrong
He's a former journalist and so has direct experience of this problem. He cites many examples where expert testimony caused misleading or wrong stories to be published, but IIRC none of them involved corporate scientists. Mostly academics like nutritionists, psychologists and so on.
So it's completely unrelated to the topics I refer to. What I refer to is:
https://www.amazon.com/Merchants-Doubt-Handful-Scientists-Ob...
Claiming that the misinterpretation of science happened only in the distant past is intentional attempt to obscure the real problem.
There is objective truth and it is far from what some people with a lot of money peddle as the truth and what gets replicated across the media. And the media definitely don't cover what effectively advertising campaigns are as such -- paid disinformation for the benefits of some specific corporations or interest groups.
I suspect it comes from academic propaganda about 'free thought', being able to pursue any line of questioning they desire, etc. It's obviously not true. Academics find it impossible to reach a simple conclusion that's reached all the time in the corporate world: "we don't know the answer and cannot know anytime soon".
I have many more issues with current journalism than the author of the blog post, rooted in their "fire & forget" nature of publications (no visible revisions, no corrections, almost all currently accessible articles are too old to be useful or even correct).
Is that statement 100% true for the low-level models that physicists use and develop? In particular, I'm curious if quantum-physics models are 100% right, just not 100% precise.
One of the best ways to look at this is through the Standard Model of particle physics, which essentially defines how the fundamental particles of the universe are related. Between the number of observations and large-scale experiments dealing with high-energy collision products, astrophysics, neutrino detectors, etc., some people consider the Standard Model to be the most thoroughly-tested and verified framework in all of science. That's a pretty grand claim, but hey.
But it still falls short in some ways--for one, it starts breaking down past a certain scale. Classical field theory as defined by general relativity (another model that has had enormous success under test both theoretically and experimentally) and particle physics don't get along. Neither one fully explains reality, and the interface between those two models of reality hasn't been found. That's why people research things like string theory--they're attempting to find a mathematical framework that can resolve those two frameworks, among other things.
So while each of them describes the universe extremely accurately in their own domain (check the sigma values and number of observations of experiments run on the LHC), they're not 100% right, since they can't be correctly extended to cover all scales and frames. The models remain just that--models which provide a useful framework to interpret reality, but don't fully describe the physical reality itself.
Perhaps you have heard of the idea that "the map is not the territory" [0]. Models can never be exactly descriptions of reality, not without some sort of special rationale and argument from the outside of reality.
In particular, QM models aren't 100% right. Gravity is missing almost entirely from the model (!) and there are some glaring experimental discrepancies, particularly around the vacuum catastrophe [1]. We know that the combination of QM and relativity gives a hybridized model that cannot work at all scales but explains things like the color of gold [2], so we know that there ought to be a single unified model which does work at all scales and has the same explanatory power.
[0] https://en.wikipedia.org/wiki/Map%E2%80%93territory_relation
[1] https://en.wikipedia.org/wiki/Cosmological_constant_problem
[2] https://en.wikipedia.org/wiki/Relativistic_quantum_chemistry
https://en.wikipedia.org/wiki/Precision_tests_of_QED
However, we know it cannot be completely accurate, as it has no way of explaining gravity.
- Models are deliberate simplifications of reality, in order to guide thinking and otherwise pull in only important information
- Formulations (formalizations) are encapsulation of principles into a mathematical framework
While there is significant overlap, the two categories do not overlap 100%. I see formalizations of physics as the latter, and we use the former to help keep our understanding of the latter clear.
In "QED" Feynman states that the predictions are as precise as being able to measure the distance between (points in) New York and Los Angeles accurately to within the width of a human hair.
https://en.wikipedia.org/wiki/QED:_The_Strange_Theory_of_Lig...
But this information is already contained in the model itself. Therefore people should be reading the models, not their results.
The models should of course be verified by comparing their results to empirical data. But that does not often exist with global things like pandemics and climtae change.
It would work like this:
For each field there has to be a committee similar to the ones medical practitioners already have. If the behavior is not up to standards they do an inquiry and if need be the credentials are stripped.
Someone with credentials may sign-off on articles written by journalists and must do so for laws made by law makers.
Such articles and laws stay active for as long as the credentials are valid. If the person dies a new one has to sign off on it. If that doesn't happen the law is abolished automatically and the archived news article will have to clearly state at the top that such validation is missing as-of [say] march 2043. It may also solicit such review.
We can make a convenient api that allows people with credentials to stick our their neck to approve a publication. The list of professionals endorsing the perspective must be made available from the article or law.
Well, it's tricky. If you say "I don't believe covid-19 is a serious problem", that can't be punishable as there is a large spectrum of legitimate thinking as to its severity and what trade-offs we should want to make. Such a statement is not remotely like practicing medicine without a license, but some will argue that it is if it could help them shut up the speaker. While saying that "chloroquine phosphate is a good prophylactic for covid-19" to someone who would believe it certainly should be punishable (as attempted murder perhaps! and regardless of whether the speaker is a licensed physician!).
> This could easily be extended to include journalists and politicians as well as other areas of science (if the stakes are high enough)
Journalists? Eh, maybe, but government officers generally have privileges and immunities -- good luck getting them to let those go.
Anyways, the rest of your comment reads like 1984. Quis custodiet ipsos custodes and all that. Regulatory capture and all that. There's no Objectivity. There's no way to set up a mechanism that yields objectively-correct results. All systems will be susceptible to collective delusions and other failures. There's no silver bullet here, and free speech should be part of the mix. Reactionary thinking is fun for the angry, but not good for society.
We have professional communities who get things wrong regularly but the rest of the time they do a very good job. Professionals have a tendency to get things right sometimes.
In the media we see journalists interview experts and twist their words into click bait. Journalists loves to attribute the work to professional sources. There is an abundance of professionals who could operate a thumbs up/down interface. Doing this comes with a certain risk to their career. When hiring someone you can pull the articles endorsed from the database. The choice to voice their opinion depends on how much they care about a topic.
The article can be published regardless. The banner will just say something like: "Zero security experts endorsed this article."
Then we will see how many dieticians are willing to put their name under the "Eating chocolate every day can help you lose weight" publication. The endorsement doesn't have to be permanent but the log will be.
I would disagree. As an example in the history, saying "The Earth is a sphere" was once punishable by death. Fake news and pseudo science has always existed, but censorship is not a solution. Only research, education and communication can help, and even then, each generation will always have his own set of questions without answers.
I don't agree with the parent' solution either, for the same reasons.
Assuming the author has better things to do others could provide value by endorsement. We have star ratings and thumbs all over the web, it works but the rocket scientist gets as many votes as the 12 year old under an article about rocket science.
I've often had the discussion on wikipedia. The funniest one was 4 so called established editors repeatedly overruling the Nobel prize winner in his area of expertise on an issue that according to the guidelines is left up to editors. Initially he argued the text he added was common sense. When trying to add sources there was only cursory mention in top journals (they assumed it was common sense for their reader) everything else was considered not RS. It struck me how easy it would be to use [for example] university profile pages to host a public key. It doesn't even have to be visible. The WP editors argued it impossible but its easy.
Then them professors can go around and rate peoples publications the way they always do. As a reader I would much enjoy the endorsements.
It's much better than just my own opinion crudely put together without expertise. The journalist probably doesn't know anything either. I wonder, what are we even doing? (me and the journalist) If neither of us can see the false-positives or -negatives nor can do the probability calculations... what is the point of the exchange? I see much greater potential with little extra effort.
Granted, if you're just dumb and ignorant and choose to take it yourself, that's no crime. But telling others to take poison, without telling them it's poison, should be a crime. Of course, in the case of chloroquine phosphate, if you look at the packaging, you'll see it's poison.
Chloroquine phosphate is a fish tank cleaner. On the other hand, chloroquine phosphate is a medicine.
Or former software company CEOs for that matter
We just don't know because we just don't have the data or heck, even anecdotal evidence from similar events in the past
However, the utility of the models is to give us a sense of how the different parameters interact. There are parts of the model were we can have a lot of trust, for example that people with severe conditions will need hospitalization, or that people will react quite similar as they reacted yesterday. So for the short term, the models give us quite good guidance, and for the long term, they help to map out scenarios.
So if you actually look at the report in question, you will see that they are actually trying to estimate the impact of various non medical interventions, like encouraging social distancing, by comparing different countries. It is just that newspapers as usual just run with the most immediately digestible number, independent wether that number is important or useful.
The study in question:
https://www.imperial.ac.uk/media/imperial-college/medicine/m...
Some overview video from Dr. Campbell on youtube: (in general, I think his youtube channel is quite good)
If you‘re looking at a simple population infection model, lockdown efficacy is just a factor affecting the contact rate among uninfected actors. You run multiple scenarios for multiple levels of this factor, and see where that gets you.
Or did you mean something else?
(Source: I‘m not an epidemiologist, but as an ecological modeller I work with very similar tools.)
My point is that we can't reasonably predict how people will behave in lockdown past a certain point. We've never had similar lockdowns in a world that was as globalized, as hyper connected as ours. You could go from 2 to 8 weeks of lockdowns if everyone was living in isolated villages a la 1918 Spanish Flu, but that's not our present world.
How do you model a situation where after 4 weeks of lockdowns, a social media post about food shortages goes viral, causing mass panic and breaking of quarantine?
We can't because we've never had a situation like this, or the tools for spreading (mis) information as we currently do.
tl;dr not much
We have old data from 1918.
This is a white swan, not a black one.
More importantly, the mortality, while much higher than flu, it's still relatively low.
Now imagine a virus as contagious as this one, but with 10% mortality over all age groups. That would be unprecedented and probably cause society meltdown.
Anecdote: someone was trying to convice me to panic about Coronavirus because "three hundred and [something] people died just today!"
$ units
8 billion / 80yr
/day
It's nearly 3 million in the US.
Again, our data for all older epidemics is applicable to the epidemic in isolation. But there is no way to accurately model how the epidemic interacts with people simply because the way people live has changed drastically from past epidemics.
Just perspective, and I'm very happy to know the reference now.
Journalists, and the newsmedia corporations and organizations that employ them, don't run with the most inflammatory headline possible as an accidental fluke of a mistake that they were too careless to catch. Even public sector newsmedia organizations use measures of how widely read their articles are, as a figure of merit to how well they are performing. Private sector newsmedia are rewarded financially in more or less direct proportion to how widely read (or at least clicked on) their articles are, not how well informed the reader is after they're done reading it (if they even do read past the headline).
If there is one less to be learned from this whole Covid-19 debacle (and I'm sure there are several), it is that our entire news ecosystem, public and private, is fundamentally structured wrong for doing what is supposed to be its purpose, which is to make people better informed. It's not bad at it by mistake, it's bad at it as an inevitable consequence of its design.
This is the reason for the enduring power of the filter bubble: it is a stable equilibrium because it serves both the purposes of the demand and supply side.
You can test this by making high-reliability websites that state honest priors. You'll get an audience but the audience will be pretty specific to your subject matter and not be popular. No information source has had all of the following characteristics:
* Broad-based popular support
* High information content
* Novel information, i.e. information you can't get elsewhere
* Sustained presence
This may actually be desirable. Novel reliable information is an advantage, but it may not be a present sufficient advantage, and species survival may depend on presently boosting those capable of acquiring and utilizing information advantage. i.e. a time may come when we need to be good at it - if we have more people with this characteristic then, it'll lead to better outcomes.
The horrible thing about online advertising is that it allows people to make profit from making you look at something, even if it immediately makes you disappointed. From that moment, the need to write non-disappointing articles has decreased significantly.
Its ideal purpose is to provide people with nourishing, healthy, enjoyable food.
But its actual incentive is to give people the food they choose to buy, which often isn't nourishing or healthy.
How does its viewership compare to that of gossip-based media like E! or anger-based media like Fox or CNN?
You speak of a failure in design as the root cause of the failure to achieve the purpose of “to inform”.
From a teleological perspective, viewing the media as a tool designed “to inform” would be a mistake, it would amount to nothing more than a supposition.
Having “better informed” people was never the stated purpose of mass media so it would be wrong to say it is not fulfilling its design objectives. What would be applicable here to help us better understand the actual purpose of the media is POSIWID: ”the purpose of a system is what it does”[0]
[0] https://en.wikipedia.org/wiki/The_purpose_of_a_system_is_wha...
Clearly the person you're responding to wants a system that makes people better informed, and I think there's a lot of other people (myself included) who want the same thing. So the question is obviously, how do we change the news ecosystem from what it is, to a system that makes people better informed?
People tend to want their worldview confirmed. If you want people to be better informed, one way would be to make them angry when they encounter things designed to manipulate them.
I think that other than marginal gains, this is a pipedream. The reason the news media is the way it is is due to the choices of the people consuming it. A change in the industry itself is unlikely to put a dent into this, because people will just go elsewhere to get the 'news' they want to hear.
We would need some kind of a fundamental change in society. Maybe if we completely revamped the style of childhood education, it would be possible to change what people look for in the news. I think that practically such a fundamental change is next to impossible. People talk a lot about how we need changes to the education system, but they're usually either spewing hot air or only want small changes.
If that was already true, there never would have been an Enquirer or Weekly World News.
Ultimately, I'm not looking to blame the supply side, either: certainly there's some blame for the demand side too. In fact, I don't believe blame is a productive thing to do in this situation or most situations. But I am trying to change it from the supply side, because when you try to create change from the demand side, you run into more issues with affecting free choice which makes this and many other problems more intractable.
I also think you're wrong about why the Enquirer et al exist: some people take these as just humor and get their information elsewhere, and others want to be informed, but due to bugs in the human brain, think that sources like the Enquirer are good sources of information. Neither of these are "people not wanting to be informed".
By bettering basic education. People could learn the relationships and interdependecies of the system and society itself, including the role of information. Why not learn everything through RPGs?
This would create a demand for better news sources in the long term.
Because education increases environmental awareness, and informative news provides it. So you'd want informative news to remain environmentally aware.
Each time I encounter this, I am stunned. But it still happens.
From the CBC's mandate: the Canadian Broadcasting Corporation, as the national public broadcaster, should provide radio and television services incorporating a wide range of programming that informs, enlightens* and entertains*
From PBS's mission statement: PBS is a membership organization that, in partnership with its member stations, serves the American public with programming and services of the highest quality, using media to educate, inspire, entertain and express a diversity of perspectives. PBS empowers individuals to achieve their potential and strengthen the social, democratic, and cultural health of the U.S.
You'll find that kind of language repeated for most public broadcasters. The corruption of those ideals by private enterprise in the name of profit should not come as a surprise.
I and perhaps many other people think the media should inform people; that is a statement of its purpose, and it appears that the collective actions of people in society have redesigned it to eliminate most of the informing.
It doesn't have to have ever been designed to inform by specific and aware human intention; if it informed as a side effect of being unoptimized for disinformation, then in that sense it was designed to inform.
By analogy, natural foods are not designed, in one sense, to keep you healthy, as evolution can make some things good for you and others bad.
...but the purpose of eating them is healthy nutrition, and if we started systematically only eating the toxic ones, then we would say something about our society is structured wrong for the purpose that we have of getting nutrition.
Your expectation that the media should inform people is reasonable but unrealistic. The original designers had fairly specific design goals in mind and it did not explicitly include “to inform”, this can only be tacked on.
Today we have newspapers, radio, TV and of course the Internet as tools of (mass) media.
If you were among the original designers of the newspaper[0], which was the first tool of mass media for centuries, but your preference to inform was out-weighed by competing interests (aka politics), then of course you are well within your rights to be outraged — you are entitled to criticize the design for falling short of your expectations.
In other words, unless you were personally part of the design team, you can’t really speak about what the design should be or should have been, since you are in no position to influence the system’s purpose before it was built.
You can only deal with the consequences of the designers’ creation, which includes working around the limitations of the system as designed, or building a new system from scratch.
A new system that addresses those limitations would not only be expensive to build from scratch, it would also have to compete for attention and funding to be sustainable — the market has to decide if they truly care about being better informed or not.
Facebook, which is perhaps the most modern type of media, is as vulnerable as the others when it comes to ability to misinform.
[0] ”News was highly selective and often propagandistic. Readers were eager for sensationalism, such as accounts of magic, public executions and disasters; this material did not pose a threat to the state, because it did not pose criticism of the state.” culled from Wikipedia: https://en.wikipedia.org/wiki/History_of_newspaper_publishin...
I wrote "should"; I am not predicting in my comment that that the media will inform people [more] in the future; therefore calling my "expectation" unrealistic is uncalled for.
Referring to "the original designers" is confusing to me. You seem to be implying that "the media" was designed by some person or entity as a monolith, which is a theory that is unfamiliar to me and not mainstream (that I'm aware of).
Also, you seem to be positing that "the media" was not only created as a monolith but is controlled as one today, since you say that it can only be worked around or replaced. It really seems like a heterodox and far out theory, that "the media" is not subject to to change. Perhaps you could elaborate, since I thought the discussion was about recent changes to the media?
On the one hand, media businesses are, in most cases, for-profit enterprises similar to other enterprises.
On the other hand, “to inform” or to have better informed citizens is in the public interest. “To inform” essentially an altruistic goal. Something done for the greater good is hard to monetize unless you ask for donations. Altruism as a business model will not pay the salaries of journalists.
My argument is that the two goals: “for profit” and “to inform” are incompatible goals — either you found a non-profit media entity with the altruistic goal of better informing people, or you found a for-profit without the pretension of altruism.
By arguing that “I and perhaps many other people think the media should inform people”, that the media’s collective purpose is to better inform, essentially what you are really saying is that you want for-profit enterprises to behave in the manner expected of non-profit enterprises? As I said, this is a noble but unrealistic ask. This is the crux of our disagreement.
I mean, I do want them to behave differently that they have been previously, I don't know how you could interpret my comments otherwise.
I feel like you are arguing by definition - you have some definition of "for profit entities" that excludes morality. A definition can be anything you like, but I don't think that particular one has a referent in the real world - and it's obvious to me that it shouldn't.
So, for profit businesses operate under constraints already, and the only debate I can imagine is under what sort of constraints.
Sometime's that's informing from a real benevolent perspective of let's get everyone on the same page for what's best to the best of our knowledge. Other times it's an obfuscation scheme to allow some to profit off of the rest of us.
Having spent a lot of time working for and with governments I can assure you that most of the time, behind closed doors, they truely hate the press, and wish it would go away. And this is true of even the most open and democratic governments.
Autocratic governments, again and again have shown what they think of a free press.
The idea that mainstream media is a mouthpiece of government just doesn’t add up.
Newspapers may pester governments with annoying questions about specific institutional failures and corrupt individuals, but they'll tend to be aligned on what the institution was supposed to achieve, what faithfully executing an office would look like.
The New York Times will ask the NYPD, "Why did you beat up that guy in a routine traffic stop?" or "How is it possible that you billed more overtime hours than there are in a week?". Not "Why haven't you shot the rich yet?"
The way you can particularly see this is in the suppression of news that doesn't ultimately help out _any_ of the current leaders with it's dissemination, only the populace.
Can we either make a reasonable-sounding word or phrase that means the thing or just say the thing? Who is going around really saying “POSIWID”?
This is clearly true, but I wonder if must always be so.
In academia, lying in a publication can be career-ending, which acts to broadly 'scare them straight'. For academics, it's desirable to be highly read and cited, but to be seen to be dishonest is the end of the road. Could it be possible to create similar incentives for journalists?
Can be. Among others, Matthew Walker still has a job. https://yngve.hoiseth.net/why-we-sleep-institutional-failure...
The problem is that these incentives for academics aren't created out of purity of heart, but because of the system to which they belong; you will no longer be highly read and cited once it is clear that your results can't be trusted. Unfortunately, this seems not to be true in journalism—you can purvey intentionally, and explicitly, wrong information, and it will still be consumed actively by those whose biases are confirmed by it. We can discuss how to change that, but changing what kind of news people want to read is surely even harder than changing what kind of news journalists write and publishers publish.
https://en.wikipedia.org/wiki/Claas_Relotius
But he did so very brutal so to say. The problem with journalism is mostly not straight lying, but missleading and bending the truth until it fits the agenda. So a classic journalist should not have another agenda than the truth. But this type seems to be very rare today.
https://appleinsider.com/articles/19/10/04/editorial-a-year-...
That's a feature, not a bug. A system which depends on people being saints, isn't going to work.
> changing what kind of news people want to read is surely even harder than changing what kind of news journalists write and publishers publish
Agreed, I think that's the root here.
So truth ethics etc. are all secondary values.
This seems like a fairy tale you tell young naive business majors with no experience. The real world isn't like that.
You think oil companies, tech companies, defense companies, tobacco companies, banks, etc have been profitable for decades because of integrity and ethics? No you become profitable and wealthy by being amoral and cutthroat then paying PR firms to spread the news about how good you were all along.
Do you think Google, Facebook, Apple, etc are so profitable because they are moral? Do you think Nike became Nike by having integrity and ethics or by exploiting cheap labor overseas?
> But in reality, having integrity and ethics in business is actually more profitable over the long term.
Both your parent's view and your view could spring from a belief about how the world is, rather than from non-anecdotal hard data. I'd like to believe the more optimistic version, but I find it hard to do so. Do you have some data to support it?
More generally, plenty of companies cause negative externalities, profiting by causing damage that they don't have to pay for.
https://www.theverge.com/interface/2020/4/1/21201162/amazon-...
https://www.cbsnews.com/news/inside-an-amazon-warehouse-trea...
"The only way that I can see to deploy this much financial resource is by converting my Amazon winnings into space travel. That is basically it." - Bezos
Gates's philanthropy is fine, but my comment was on his business dealings. He has a long history of anti-competitive behavior, completely void of morals.
Name anyone who died from a single thing 90s Microsoft did.
The modern tech giants take actions every day that are far more anti competitive than anything Microsoft ever did.
Fallacy of relative privation (also known as "appeal
to worse problems" or "not as bad as") – dismissing
an argument or complaint due to what are perceived
to be more important problems. First World problems
are a subset of this fallacy.
Illegal? Sure. Evil? So some other millionaires didn't get to become billionaires. Meanwhile the world got a single API to write software against for almost two decades, how many ISVs existed because Microsoft provided an insanely stable (in regards to API churn) platform to develop against?
Hell right now with 2 major mobile OS players there is a huge tax on developers, imagine if the 90s had been a wild west and there had been 4 or 5 major players.
One can also note that given how mobile played out, there is a good chance that the desktop market would have coalesced around a single dominant OS and a secondary minor OS anyway.
And yeah I know everyone is pissed about BeOS, but they also had their chance to be a player until they tried to hard bargain with Apple and Apple walked away!
Let's not go to the other extreme and downplay what they did. If they had their way, the Internet wouldn't be an open platform and open source would be illegal.
Personally I don't care about exclusive OEM deals. What I care about were the dirty campaigns against open source and them trying to leverage their huge patents portfolio against Linux and later Android. Or them planting shills inside Nokia, weakening it enough for a takeover of their mobile division and then running it into the ground, thus destroying one of Europe's top tech companies. A conspiracy theorist would say that this was economic warfare, maybe sponsored by the US, but for me incompetence is enough for blame.
Or how about their long battle against open standards, like ODF and their use by public institutions?
And the Microsoft of today, in spite of popular belief, isn't very different. Their priorities may have shifted, but even post Balmer they continued to use their patents portfolio against Android and they continued to fight against the adoption of ODF. Their predatory culture is still there and as seen by the ads and aggressive telemetry in Windows 10, as soon as they can gain some economic advantage, they'll take it, regardless of cost to society.
Their "Microsoft changed" marketing campaign has been genius in its execution. On the other hand I'm glad that they are doing well, because otherwise they have the potential to become the biggest patent troll. Just like when their Windows Phone failed to gain traction, "if you can't innovate, litigate" seems to work well.
With the current system, we're reliant on the whims of a couple of billionaires. Some are relatively benevolent, but far more are on the level of the Kochs, Larry Ellison or the Sacklers. Business schools have taught the "fiduciary duty" doctrine for a long time, which is basically "maximize profit above all else, or we'll find someone else who will".
I don't think "reliant on the whims of a couple of billionaires" is a fair characterization. In what way does the average person rely on the whims of Larry Ellison?
Who gets to decide when someone is lying? What happens when that power to determine truth from lies is obtained by a bad actor to create a new truth?
No. What is wrong is that people believe the news industry exists to make people better informed. That is an industry PR lie such as "Do no evil", "Fair and Balanced", "Serve and Protect", etc. The truth is that newspapers have always lied because they were created to lie.
"Nothing can now be believed which is seen in a newspaper. Truth itself becomes suspicious by being put into that polluted vehicle."
"I will add, that the man who never looks into a newspaper is better informed than he who reads them; inasmuch as he who knows nothing is nearer to truth than he whose mind is filled with falsehoods and errors." -- Thomas Jefferson
The NY Post was created by Alexander Hamilton solely to attack his political opponents. The lies hamilton printed in the ny post about aaron burr is one of the reasons why he got killed in the duel.
Your frustration stems from a false premise : News industry exists to keep you informed.
Instead of banging your head trying to make your conclusions fit a false premise, why not do away with a false premise?
All men are good. Harvey Weinstein is a man. Therefore, Harvey Weinstein is good.
Would you waste your life trying to find ways to show Weinstein is good? Of course not. You'd work your way through your logic and conclude your premise was wrong and that all men are not good.
That being said, I think content aggregators are partly to blame. I mean if you’re just reading the daily paper, maybe the front page has exaggerated headlines, but once you’re in the issue it can mellow out. But content aggregators are always trying to find the latest splash.
Sometimes the design is deliberately setup that way by an individual or group with something to gain, but other times it is just because the system contains different parties with competing interests.
Anytime I see a clearly inefficient or ineffective system the first question I try to figure out is whether it works that way by design. In many cases once I learn more about it, the answer is yes.
On the other hand, it is pretty standard mainstream news when in the same presser, the doctors are saying the opposite of what the President is saying.
Birx, too. The difference in messaging and information content when she's on that podium or on Fox programming, versus when she's on normal-people programming, is stark.
They're being leaned on and it is starkly apparent when you're not coming in with priors that tend towards conspiracy.
Fauci is a professional. That's why he's actively correcting what Trump says at every opportunity. He's downplaying that he's correcting Trump--but he is, and it's necessary, and it speaks to the complete mindfucked stupid coming out of the White House and it should alarm you a lot more than what you're handwringing about throughout all of your comments.
Stooging for these dirtbags will not look any better in the light of history than it does in the light of today. Stop.