What's Wrong With Science? Mostly, it is how we Mismanage it

 

"A scientist, Dr. Hans Zarkov, works night and day, perfecting the tool he hopes to save the world... His great mind is strained by the tremendous effort" (From Alex Raymond's "Flash Gordon")

We tend to see science as the work of individual scientists, maybe of the "mad scientist" kind. Great minds fighting to unravel the mysteries of nature with the raw power of their minds. But, of course, it is not the way science works. Science is a large network of people, institutions, and facilities. It consumes huge amounts of money from government budgets and private enterprises. And most of this money, today, is wasted on useless research that benefits no one. Science has become a great paper-churning machine whose purpose seems to be mainly the glorification of a few superstar scientists. Their main role seems to be to speak glibly and portentously about how what they are doing will one day benefit humankind, provided that more money is poured into their research projects.

Adam Mastroianni makes a few simple and well-thought considerations in his blog about why science has become the disastrous waste of money and human energy it is today. The problem is not with science itself: the problem is how we manage large organizations. 

You may have experienced the problem in your career. Organizations seem to work nicely for the purpose they were built up to when they include a few tens of people, maybe up to a hundred members. Then, they devolve into conventicles whose main purpose seems to be to gather resources for themselves, even at the cost of damaging the enterprise as a whole. 

Is it unavoidable? Probably yes. It is part of the way Complex Adaptive Systems (CAS) work, and, by all means, human organizations are CASs. These systems are evolution-driven: if they exist, it means they are stable. So, the existing ones are those who managed to attain a certain degree of stability. They do that by ruthlessly eliminating the inefficient parts of the system. The best example is Earth's ecosystem: You may have heard that evolution means the "survival of the fittest." But no, it is not like that. It is the system that must survive, not individual creatures. The "fittest" creatures are nothing if the system they are part of does not survive. So, ecosystems survive by eliminating the unfit. Gorshkov and Makarieva call them "decay individuals." You can find these considerations in their book "Biotic Regulation of the Environment."

It is the same for the CAS we call "Science." It has evolved in a way that maximizes its own survival and stability. That's evident if you know just a little about how Science works. It is a rigid, inflexible, self-referencing organization refractory to all attempts to reform from the inside. It is a point that Mastroianni makes very clear in his post. A huge amount of resources and human efforts are spent by the scientific enterprise to weed out what's defined as "bad science," seen as anything that threatens the stability of the whole system. That includes the baroque organization of scientific journals, the gatekeeping control by the disastrously inefficient "peer review" system, the distribution of research funds by rigid old-boy networks, the beastly exploitation of young researchers, and more. All this tends to destroy both the very bad (which is a good thing) and the very good (which is not a good thing at all). But both the very good and the very bad threaten the stability of the entrenched scientific establishment. Truly revolutionary discoveries that really could change the world would reverberate through the established hierarchies and make the system collapse. 

Matroianni makes these points from a different viewpoint that he calls the "weak links -- strong links" problem. It is a correct way if you frame Science not as a self-referencing system but as a subsystem of a wider system which is human society. In this sense, Science exists to serve useful purposes and not just to pay salaries to scientists. What Mastroianni says is that we should strive to encourage good science instead of discouraging bad science. What we are doing is settling on mediocrity, and we just waste money in the process. Here is how he summarizes his idea. 

I strongly encourage you to read the whole Mastroianni's post because it is very well argumented and convincing. It is what we should do to turn science into something useful that we badly need in this difficult moment for humankind. But the fact that we should do that doesn't mean it will be done. Note in Mastroianni's post the box that says "Accept Risk." This is anathema for bureaucrats, and the need for it nearly guarantees that it will not be done. 

Yet, we might at least try to push science into doing something useful. Prizes could be a good idea: by offering prices, you pay only for success, but not for failure. But in Science, prizes are rare; apart from the Nobel prize and a few others, scientists do not compete for prizes. That's something we could work on. And, who knows, we might succeed in improving science, at least a little! 

 

Why we Can't Change Anything Before it is Too Late.

 

Yours truly, Ugo Bardi, in a recent interview on a local TV station. note the "Limits to Growth" t-shirt and, as a lapel pin, the ASPO-Italy logo. 

A few days ago, I was invited to an interview on a local TV about the energy transition. I prepared myself by collecting data. I was planning to bring to the attention of viewers a few recent studies that showed how urgent and necessary it is to move away from conventional engines, including a recent paper by Roberto Cazzolla-Gatti(*) that shows how the combustion of fossil fuels is one of the main causes of tumors in Italy. 

And then I had a minor epiphany in my mind. 

I saw myself from the other side of the camera, appearing on the screen in someone's living room. I saw myself as one more of those white-haired professors who tell viewers, "look, there is a grave danger ahead. You must do as I say, or disaster will ensue."

No way. 

I could see myself appearing to people as more or less the same as one of the many TV virologists who had terrorized people with the Covid story during the past three years. "There is a grave danger caused by a mysterious virus. If you don't do as I say, disaster will ensue." 

It scared people a lot, but only for a while. And now the poor performance of TV virologists, Tony Fauci and the others, cast a shade over the general validity of science. As a result, we now see a wave of anti-science sweeping the discussion while carrying along the flotsam of decades of legends. Fake lunar landings, earthquakes as weapons, how Greenland was green at the time of Erik the Red, and don't you know that climate has always been changing? Besides, Greta Thumberg is a bitch.

But it is not so much a fault of the TV virologists, although they have done their part in creating the damage. It is the human decisional system that works in a perverse way. More or less, it works like this:

1. Scientists identify a grave problem and try to warn people about it. 
2. The scientists are first demonized, then ignored.
3. Nothing is done about the problem.
4. When it is discovered that the warning was correct, it is too late. 

Do you remember the story of the boy who cried "wolf"? Yes, it works exactly like that in the real world. One of the first modern cases in real history was that of "The Limits to Growth" in 1972. 

1. A group of scientists sponsored by the Club of Rome discovered that unrestrained growth of the global economic system would lead to its collapse.
2. The scientists and the Club of Rome were demonized, then ignored.
3. Nothing was done about the problem.
4. Now that we are discovering that the scientists were right, collapse is already starting.

More recently, we saw how, 

1. Scientists tried to alert people about the dangers of climate change.
2. Scientists were demonized and then ignored.
3. Nothing was done about climate change.
4. When it was discovered that the warning was correct, it was too late. (it is).

There are many more examples, but it almost always works like this. Conversely, when, for some reason, people take heed of the warning, the results may be even worse, as we saw with the Covid epidemic. In that case, you can add a 1b line to the list that says, "people become scared and do things that worsen the problem." After a while, line 2 (scientists are demonized) takes over, and the cycle goes on.  

So, what are the conclusions? The main one, I'd say, is: 

Avoid being a white-haired scientist issuing warnings about grave dangers from a TV screen. 

Then, what should you say when you appear on TV (and you happen to be a white-haired scientist)? Good question. My idea for that TV interview was to present change as an opportunity rather than an obligation. I was prepared to explain how there are many possible ways to improve the quality of our life by moving away from fossil fuels. 

How did it go? It was one of the best examples that I experienced in my life of the general validity of the principle that says, "No battle plan survives contact with the enemy." The interview turned out to be a typical TV ambush in which the host accused me of wanting to beggar people by taking away their cars and their gas stoves, of trying to poison the planet with lithium batteries, and of promoting the exploitation of the 3rd world poor with coltan mines. I didn't take that meekly, as you may imagine. 

The interview became confrontational, and it quickly degenerated into a verbal brawl. I am not linking to the interview; it is not so interesting. Besides, it was all in Italian. But you can get some idea of how these things go from a similar ambush against Matt Taibbi on MSNBC. What did the viewers think? Hopefully, they switched channels. 

In the end. I am only sure that if something has to happen, it will. 

(*) The paper by Roberto Cazzolla-Gatti on the carcinogenic effects of combustion is truly impressive. Do read it, even if you are not a catastrophist. You'll learn a lot. 

(**) CJ Hopkins offers some suggestions on how to behave when you are subjected to this kind of attack. He says that you should refuse to answer some questions, answer with more questions, avoid taking the interviewer seriously, and things like that. It is surely better than trying to just defend oneself, but it is extremely difficult. It was not the first time that I faced this kind of ambush, and when you are in the crossfire you have little or no chances to avoid a memetic defeat. 

How to Make Your Google Masters Happy: Fixing the Privacy Policy of Your Blog

  

As I told you in a previous post, for months, Google has been pestering me with notices that there was something wrong with the privacy policy of my blog and that if I wouldn't fix it, they would start doing dark and dire things, such as making my blog invisible to search engines. Now, after many attempts and much struggle, I can tell you that the saga is over.  So, I am posting these notes that may be useful for you in case you find yourself in the same situation.

The problem had to do with the privacy regulations of the EU and the EEA, aka the "General Data Protection Regulation (GDPR): I had to obtain consent from the user for something not explicitly described in the ominous messages I was receiving. Fixing the problem turned out to be a small Odyssey. 

1) Using search engines The first thing you normally do in these cases is look over the Web to see if someone has already solved the problem that plagues you. About this specific question, I immediately found myself facing a wall of sites claiming that they can solve the problem for you if you just pay some money. Mostly, they looked like traps, but I was dumb enough to pay $29 for a "personalized policy declaration" that came with the request of a further payment for hosting it on their site. I took care myself to create a subpage of the blog to host it at no cost. 

First lesson learned: skip the sites that ask you money to fix this problem unless you are a commercial site and you need to do it quickly. 

2. The text I downloaded may have been a good policy declaration, but Google still wasn't satisfied and I later learned that they didn't give a hockey stick about that. 

Second lesson learned: you can spend a lot of time (and also money) fixing the wrong problem.

3. I contacted Google's customer service at ddp-gdpr-escalations@google.com -- yes, they have a customer service to help people fixing exactly the GDPR problem. Amazingly, I got in contact with someone who seemed to be a real person -- the messages were signed "Gargi," which is an Indian male name. After a few interactions, he finally told me what Google wanted. It was simple: I just had to add the sentence "cookies are used for ads personalization" in the "consent banner." And that was it. Gargi even sent me a screenshot of what the banner should look like. It was a step forward. 

Third lesson learned. Human beings can still be useful for something. 

4. But who controls the cookie banner? I had never placed a cookie banner on my blog, and I saw no such a thing appearing when I loaded the blog. Other people told me that they didn't see any banners on the first page of my blog. I had always interpreted the lack of a banner as a consequence of my blog not being a commercial one. But, no, the trick was a different one. After much tinkering and head-scratching, I discovered that my browser (Chrome) keeps track of previous decisions and didn't show the banner again to people who had already accepted the cookies. I could see the banner if I erased the cookies from my main browser, or used a "virgin" browser. The beauty of this trick is that not even the people from Google's customer service seemed to know it; so, at some moment, they started telling me that my blog had no cookie banner, and I had to explain to them that they just weren't seeing it, but it was there. Once they understood this, it was no more a problem. But it took time. 

Fourth lesson learned: Truth may be hidden, and often is. 

5. How do you change the text of the cookie consent banner? One of those things that look easy but are not easy at all. First, you have to access the HTML code of your blog, which is not an easy task by itself. It is like open heart surgery: you make a mistake, and the patient dies. Then, even if you know how to manage HTML, you soon discover a little problem. There is NO CODE for the cookie consent banner on the HTML page of Google's blogs. The banner is dynamically generated from somewhere, Google knows where, and it is not accessible with the tools provided by Google's blogger. 

Fifth lesson learned: Google plays with you like a cat plays with a mouse.

6. It means that there has to be a widget for the cookie banner, right? Yes, there is such a widget that you can set as showing a cookie banner as you like it to be. The problems are that 1) it cannot show the banner at top of the page, where these banners normally are, and 2) it doesn't replace the Google-generated banner. So, the result is that you have two different banners in different areas of the screen at the same time. Apart from the awful effect on the way your blog looks, it is not surprising that Google was still not happy with this solution

Sixth lesson learned: Some solutions are not. 

7. How about trying chatGPT? Eventually, chatGPT gave me the right hint. It said that it was possible to insert a cookie banner script in the main HTML page of the blog. I tried the scripts provided by chatGPT and none worked, but those provided by helpful human bloggers did. I found that scripts (unlike widgets) can supersede the Google-created banner. After some tweaking, Google was finally happy. 

Seventh Lesson learned. ChatGPT is your friend, but it is a bad programmer   

________________________________________________

Conclusion. 

The good thing about this story is that I learned something, but it was also a sobering experience. The way Google managed it was so bad that I can only understand it as an explicit attempt to discourage small bloggers who are not making money from their blogs and who can't afford a professional maintenance service. Just why harass poor bloggers to do something that Google could do easily on a banner that it is wholly managed by Google? I mean, do you realize the time lost to do such a simple thing as adding a single sentence to a banner? 

It seems clear to me that at Google they don't like blogs in general. Even though they offer a blogging platform, it is a poor service for several reasons. Yet, Blogger also has several good points, the main one being that it is free. Then, it offers you possibilities of customization that other "bare-bones" platforms (e.g. substack) do not provide. For someone who just wants to express his/her ideas in public, it can still be a good choice. But, after this experience, I am wary. Google knows what they have in mind next in Mountain View. So, I may switch platforms in the near future. For now, "The Seneca Effect" blog is still there, alive and reasonably well, even though shadow-banned by the Powers That Be. And maybe these notes could be useful for you.

Final lesson I learned: I, for one, welcome our new Google masters 

_________________________________________________________

Here is the script to control the text of the cookie consent banner to be cut and pasted into the HTML code of a blogger blog after the </head> tag. It is simple, but it wasn't so simple to understand what was needed. 

<script type='text/javascript'> 

  cookieOptions = { 

    msg: &quot;This site uses cookies for ad personalization, to analyse traffic and to deliver some Google services. By using this site, you agree to its use of cookies.&quot;, 

    link: &quot;https://www.senecaeffect.com/p/privacy-policy-for-seneca-effect-blog.html&quot;, 

    close: &quot;Okay!&quot;, 

    learn: &quot;Learn More&quot; }; 

</script> 

"Flattening the Curve." The Origins of a Bad Idea

In 2003, the "Anthrax scare" led many people to use duct tape to seal the windows of their homes to protect themselves from the deadly germs. It would have been a good idea if the purpose was to suffer even more than usual from indoor pollution while at the same time doing little or nothing against a hypothetical biological attack. Yet, this folly was recommended and encouraged by the national government and local ones. It was the first taste of more to come. I already mentioned this story in a previous post, but here I'll go more in-depth into the matter. 

We are still reeling from three years of madness, but it seems that many of us are starting to make a serious effort to try to understand what happened to us and why. How could it be that the reaction to the Covid epidemic involved a set of "measures" of dubious effectiveness, from national lockdowns to universal masking, that had never been tried before in humankind's history? 

For everything that happens, there is a reason for it to happen, and the "non-pharmaceutical interventions" (NPIs) that were adopted in 2020 have their reasons, too. Some people speak of global conspiracies and some even of evil deities, but the origin of the whole story may be more prosaic. It can be found in the development of modern genetic manipulation technologies; a new branch of science that started being noticed in the 1990s. As it normally happens, scientific advances have military consequences; genetic manipulation was not an exception. 

Not that "bioweapons" are anything new. The chronicles of ancient warfare report how infected carcasses of animals were thrown inside the walls of besieged cities and other similar niceties. More recently, during the 19th century, it is reported that blankets infected with smallpox were distributed to Native Americans by British government officials. Overall, though, biological warfare never was very effective, and not even smallpox-infected blankets seem to have been able to kill a significant number of Natives. Besides, biological weapons suffer from a basic shortcoming: how can you damage your enemies only while sparing your population? Because of this problem, the history of biological warfare does not include cases where bioweapons were used on a large scale, at least so far. The low effectiveness of bioweapons is the probable reason why it was not difficult to craft an international agreement on banning their use ("BWC", biological weapon convention), ratified in 1975. 

Up to recent times, bioweapons were not seen as much more dangerous than normal germs, and the generally accepted view on how to face epidemics favored a soft approach: letting the virus run in the population with the objective of reaching the natural "herd immunity." For instance, in a 2007 paper, four respected experts in epidemiology still rejected such ideas as confinement, travel bans, distancing, and others. On quarantines, they stated that "There are no historical observations or scientific studies that support the confinement by quarantine of groups of possibly infected people for extended periods in order to slow the spread of influenza." But military planners were working on the idea that bioweapons would be orders of magnitude deadlier than the seasonal flu, and that changed everything. 

Genetic engineering technologies were said to be able to create new, enhanced germs, an approach known as "gain of function." Really nasty ideas could also become possible, such as "tailoring" a virus to attack only a specific ethnic group. Even without this feature, a country or a terroristic group could develop a vaccine against the germs they created and, in this way, inflict enormous damage on an enemy while protecting the country's population (or the select few of an elite aiming at global depopulation). 

Fortunately, none of these ideas turned out to be feasible. Or, at least, there is no evidence that they could be put into practice. That doesn't mean they were not explored, even though research on biological weapons is prohibited by the BWC convention. Researching new germs is orders of magnitude less expensive than making nuclear weapons, and so it is also feasible for relatively poor governments. (biological warfare is said to be the weapon of the poor). Whether truly effective bioweapons can actually exist is at least doubtful, but supposing that they could exist, then it makes sense to prepare for a possible attack. 

The "anthrax scare" of 2001 was the first example of what a modern terror attack using bioweapons could look like, even though it was nothing like a weapon of mass destruction, and nobody to this date can say who spread the germs using mail envelopes. Nevertheless, it was taken seriously by the authorities, and it led to the "bioterrorism act" in 2002. Shortly afterward, Iraq was accused of having been developing biological weapons of mass destruction, and you may remember how, in 2003, Colin Powell, then US secretary of state, showed on TV a vial of baby powder, saying that it could have been a biological weapon. Over the years, several government agencies became involved in planning against bioweapon attacks, and the military approach to biological warfare gradually superseded the traditional plans on how to deal with ordinary epidemics. 

The idea was that a truly deadly virus attack would cripple the infrastructure of a country and cause immense damage before the germs could be stopped by a specifically developed vaccine. So, it was imperative to react swiftly and decisively with non-pharmaceutical interventions ("NPIs") or "measures" to stop the epidemic or at least slow it down. This idea was rarely expressed explicitly in public documents, but it was clearly the inspiration for several studies that examined the effects of an abnormally deadly virus. One was prepared by the Department of Homeland Security in 2006. Another one comes from the Rockefeller Foundation in 2010, where you can read of a scenario called "Operation Lockstep" that described something very similar to what came to pass in 2020 in terms of restrictions. 

These military-oriented studies were mostly qualitative. They were based on typical military ideas such as color-coded emergencies, say, "red alert," "orange alert," and the like. For each color, there were a series of recommended measures, but little was said about why exactly certain colors were chosen to be coupled with certain actions. But there were also attempts to quantify the effect of NPIs. A paper on this subject was published in 2006 by the group of Neil Ferguson of the Imperial College in London, where the authors endeavored the task of disentangling the effects of different measures on the spreading of a pathogen. Factors such as home quarantines, school closures, border closings, reduced mobility, and others were examined (interestingly, the widespread use of face masks was not considered). The study didn't expend much of an effort to compare guesswork with real-world data, but it was not so bad in comparison with the harmless mumbo-jumbo that scientists normally publish. Let's say that it might have been an interesting exercise in epidemiological modeling but nothing more. The problem was that it came at a moment in which "biological warfare" was all the rage and that it may have influenced later military planning. 

A study that had an enormous influence on the (mis)management of the 2020 pandemic was directly inspired by Ferguson's paper. It was proposed as a CDC report by Rajeev Venkayya in 2007, who presented his model in the form of the "double curve" that later became famous. Here it is; it is the origin of the "flatten the curve" meme that became popular 13 years later. 

Remarkably, Venkaya's model was completely qualitative. The curves were just a rendition of those proposed by Ferguson et al. without any attempt of quantification. Venkayya's paper didn't attain great popularity, and it remained dormant for more than one decade until the Covid-19 pandemic arrived. Then, suddenly, the double curve became highly fashionable. It went viral and literally "exploded" on the Web and in the media.  

During the early days of the Covid-19 epidemic, one of the main supporters of the double curve model was Tomas Pueyo, who was perhaps the first to use the term "flattening the curve." His post of March 10, 2020, on the matter had more than 40 million visualizations. Notably, Pueyo's previous expertise was in engineering and communication, and he was known for a discussion about the characters of the "Star Wars" series as role models in business. So, you might be reasonably perplexed about the authority that he claimed to have on epidemiology. Nor is it clear who pushed his blog to the first places of the search engines. In any case, Pueyo showed no signs of undue modesty in the way he considered himself an expert. For instance, he wrote: 

As a politician, community leader or business leader, you have the power and the responsibility to prevent this.

You might have fears today: What if I overreact? Will people laugh at me? Will they be angry at me? Will I look stupid? Won’t it be better to wait for others to take steps first? Will I hurt the economy too much?

But in 2–4 weeks, when the entire world is in lockdown, when the few precious days of social distancing you will have enabled will have saved lives, people won’t criticize you anymore: They will thank you for making the right decision.

Pueyo was even invited in TV, where he had a chance to vocally disparage the concept of "herd immunity," which has been a staple concept in epidemiology for at least a century. If you listen to him in that TV show, you'll probably notice that he provided no evidence that he understood how epidemics spread in a population, but that's not surprising for someone whose expertise is mainly in marketing and communication. Look at minute 12:30 of the TV interview to see Pueyo's face and gesture when the scientist being interviewed mentions herd immunity. Clearly, Pueyo had no idea of what herd immunity is. It is amazing that this bizarre character was allowed to have so much influence on global policies. But so it went, and the double curve was accepted as scientific wisdom and the undisputable target for governmental interventions everywhere. 

I discussed the shortcomings of the double curve model in a previous post. Basically, the model was flawed because it didn't include methods to verify whether the measures were doing something or not. So, the results of the attempt to "flatten the curve" were modest, if they existed at all. But the story didn't end there. There does not exist something so bad that someone can't make it worse.

Little more than a week after launching his "flatten the curve" post, on March 19, 2020, Tomas Pueyo was on the march again, and he went rapidly forward in the direction of the worse. He got rid of the only thing that had some contact with reality in Venkayya's model: the fact that epidemic curves are bell-shaped. Now Pueyo said that the natural shape of epidemic curves is exponential growth and that only specific measures could force it to bend down into a bell-shaped curve. That was probably a necessary consequence of the fact that Pueyo never really understood the basics of epidemiology. So, having started with the wrong assumption (exponential growth), he moved to the wrong conclusions. Starting with an unrealistically large value for the fatality rate (3.4%), he proposed the graph below, defined as "The Hammer and the Dance." The idea was that the epidemic curve would grow to infinity unless it was brought down by means of harsh and immediate measures of containment (the hammer) and then by keeping it low with lighter measures (the dance). The data showing that this could be done..... data? What data? 

This diagram, evidently, doesn't come from an epidemiological model, not even a highly simplified one. It is just drawn accordingly to what Pueyo thought the behavior of the system should be. 

The story of the hammer and the dance was the start of a disastrous debate (let's call it this way) where plenty of people came up claiming that herd immunity was a flawed concept and that the only way to avoid being all infected, and many killed, was to enable containment measures. It also led to the concept that the curve could not just be flattened but "crushed." Again, we can see the influence of the military approach: terms such as "flattened" or "crushed" are typical of warfare, but viruses cannot be killed using military weapons. In any case, the concept of "crushing the curve" gave rise to the idea of "Covid Zero." It was another disaster that befell us, sending entire countries to a human and economic disaster in the desperate search for an unattainable goal. 

Mostly, the whole disaster was due to our inability to understand how models work. Formal mathematical models are a recent feature of the human way of dealing with reality. They are supposed to help you understand how the world works and even predict how it will evolve. But you have to be careful: the model is not the reality, just like a map is not the territory. A wrong model is not necessarily dangerous, but it can be. A military model that tells you that attacking Russia in winter is a good idea is a good example. The idea of "crushing the curve" is another example. 

Will we ever learn how to use models? Maybe. But, for the time being, models play the role of guns handled by children. 

A Revolution is Coming from Detroit! Car Tailfins are Back!

 

Today, a consortium of Detroit automakers announced plans to reintroduce tailfins in a new generation of dream cars. "We know what customers want," explained an industry representative, "people don't want those silly electric cars. They want real cars that look like cars, smell like cars, and make the noise of cars. Tailfins are the essence of the American car, which is the essence of the American dream. And we are pleased to announce that they are coming back." 

Representatives of the US oil industry expressed their satisfaction at the announcement from Detroit, noting how the "shale revolution" has brought back the US to the position of top-level oil producer in the world, a position that, with new and substantial investments, can be maintained, while shale oil production can continue growing, demonstrating how unfounded were the silly worries about "peak oil." 

President Biden commented on the announcement with a statement that was recorded as "car funs are finny, and we welcome them back. They are part of the American democratic project and we are sure that this technological solution will also be adopted in other countries." 

Former President Donald Trump declared that tail fins made America great and they are part of the MAGA concept. Dr. Anthony Fauci, Former Chief Medical Advisor to the President of the United States, noted that science says that tailfins are a good thing and that the turbulence they generate can remove viruses from the air. "Two superimposed sets of fins," Fauci said, "are better than a single one."

NATO Secretary-General Jens Stoltenberg declared that the new trend has interesting and useful military applications and that the new generation of Leopard tanks in Europe will be equipped with tailfins. "These tailfins," Stoltenberg explained, "are a symbol of the American commitment to keep Europe free and will be mounted on all NATO tanks. These military fins will be equipped with the capability of shooting depleted uranium projectiles." 

(image from Dezgo.com)

Incredibly, some people took this post seriously! It shows, at least, that most people read only the title, or at most the first few lines, of a post. 

Help Needed: can someone check the Privacy Policy of the "Seneca Effect" blog?

Folks, Google keeps pestering me with requests for an appropriate "EU User Content Policy"; but it never tells me what exactly is wrong with it. The only message I receive from them is

Customer ID: ca-pub-7714140901520074

Our policy review indicates that while the site(s)/app(s) below have a consent notice in place, its wording fails to meet the requirements of our policy:

senecaeffect.com

So, maybe someone more knowledgeable than me could take a look at the page where I have the policy specifications. It is here https://www.senecaeffect.com/p/privacy-policy-for-seneca-effect-blog.html I tried several versions of it, but Google never seems to be happy with it. 

Thanks a lot for any help you can provide!

UB

This is the letter I keep receiving from them. 

Client ID: ca-pub-7714140901520074

Dear Publisher On May 25, 2018, we updated Google’s EU User Consent Policy to coincide with the General Data Protection Regulation (GDPR) coming into force. This Policy outlines your responsibility for making disclosures to, and obtaining consent from, end users of your sites and apps in the European Economic Area (EEA) along with the UK. It has come to our attention that the attached site(s)/app(s) do not comply with our Policy, because they: • do not seek to obtain consent from users, and/or • do not correctly disclose which third parties (including Google) will also have access to the user data that you collect on your site/app. You can view these controls and the list of ad technology providers in your Ad Manager, AdSense or Admob account. • do not otherwise meet the requirements of Google's EU User Consent Policy.   If you have guidance or confirmation from a Data Protection Authority that the domains listed do not require a consent notice or that they otherwise already comply with applicable privacy laws, including GDPR, please contact us. We will review any guidance you have received from a regulatory body and take action accordingly. Action Needed Please check the site(s) or app(s) listed in the attached file and take action to ensure they comply with our Policy. We will re-review your site(s) or app(s) regularly and monitor your account. We may take action, including suspension, if the Policy violations have not been resolved by Apr 5, 2023. Policy Requirements The EU User Consent Policy outlines your responsibility as a user of our ad technology to:  • Obtain EEA along with UK end users’ consent to: ○ the use of cookies or other local storage where legally required; and ○ the collection, sharing, and use of personal data for personalization of ads. • Identify each party that may collect, receive or use end users’ personal data as a consequence of your use of a Google product. • Provide end users with prominent and easily accessible information about those parties’ use of personal data Find Out More You can refer to our Policy help page for more information on complying with Google’s Policy including a checklist for partners to avoid common mistakes when implementing a consent mechanism. We also recommend that you consult with your legal department regarding your compliance with the GDPR and Google’s policies. Need some help? Contact us, we are here to help! Sincerely,  The EU User Consent Policy Team

Update "Ticket" received from Google

Hi Ugo Bardi,

Thank you for reaching us out.

Your website  senecaeffect.com <Customer ID: ca-pub-7714140901520074> is flagged for non-compliance with the EU User Consent Policy.

Please check the website flagged and take action to ensure you comply with our Policy by referring to the resources shared. We will re-review your websites regularly, monitor your account and you will be contacted if Google has confirmed the issue has been fully resolved.

Please note when we review a website, we will accept different approaches to compliance as long as they meet our policy requirements.

• We expect users to see a clear consent notice on your website so that they can take affirmative action to indicate their decision, e.g. clicking an “OK” button or an “I agree” button.
• We expect users to be told how the site will use data. We suggest you make clear that their personal data will be used for personalization of ads and that cookies may be used for personalized and non-personalized advertising on the first layer of Consent notice.
• We expect users to be informed about how Google will use their personal data when they give consent on your site. We encourage you to link the Google’s Privacy & Terms site to your Privacy Policy page provided it is accessible through your consent notice.

This is not an exhaustive list, please refer to the external checklist to avoid common mistakes when implementing a consent mechanism, and the help page cookiechoices.org has examples of consent notices. 

You can also update the consent notice and let us know so that we can request the Google’s Policy team to re-audit.

Sincerely,

Gargi

 

NB: If you need to reference this support ticket in the future, the ID number is 3-4137000033827

Your feedback is crucial; it helps us understand how we can better meet or exceed your needs.

The Worst Model in History: How the Curve was not Flattened

"Flattening the Curve" was an incredibly successful meme during the early stages of the Covid epidemic. Unfortunately, it was based on a model that we can describe as the worst ever proposed in history (or maybe the second worst, after the one that assured Napoleon that invading Russia in Winter was a good idea). Here, I explain why the model was so bad, and I also include a discussion on whether climate change models might suffer from the same problems.  

You may have heard the quote, "all models are wrong, but some can be useful." It is true. But it is also true that wrong models can be misleading, and some can be lethal. In history, some of these lethal models were fully believed ("let's invade Russia, what could go wrong?), while the lethal consequences of following some current models are still not understood by everyone ("economic growth can continue forever, why not?"). Other models are telling us of the lethal consequences of not following them; it is the case with climate models. There are many kinds of models, but you can't deny that they are important in determining human actions. 

In this post, I'll discuss the model that gave rise to the concept of "Flattening the Curve" at the beginning of the Covid-19 epidemic. It was based on the idea that "non-pharmaceutical measures" (NPIs) would slow down the diffusion of the virus and avoid overloading the healthcare system. It was one of those models that looked good at the beginning, but that turned out to be a disaster. Among other things, it gives us a chance for a critical examination of climate models: could they suffer from the same problems? 

About the "Flattening the Curve" story, this idea of slowing down the diffusion of a viral infection was not wrong in itself. For millennia, people had noted that many illnesses were transmitted from person to person and that staying away from sick people could reduce the chances of infection. But country-wide lockdowns, universal masking, and the like had never been tried before. So how would you know that they could have a significant effect? 

Indeed, before the great Covid scare, the general opinion among practitioners and experts was that quarantines and other drastic measures were counter-productive, if not completely useless. Then, in early 2020, a new concept burst into the scene and took the memesphere by storm: "Flattening the Curve." It was expressed in the form of a graph that appeared over and over on the media in slightly different forms, but always showing the same concept. Here is an example among the many.

Image from "The New York Times," 2020,

Let's start by noting that the model is based on the typical shape of the curves describing an epidemic cycle. It occurs when something grows (e.g., a virus) by exploiting a resource (e.g., human beings). If the resource is limited, as is the case for the number of people that can be infected, then the growth of the infection will start slowing down, reach a maximum, and then decline. The result will be a "bell-shaped" curve, a behavior that has been known from the time of the Great Plague of London in the mid-17th century. (note, incidentally, that epidemic curves do not normally show the "Seneca Effect," that a faster decline in comparison to growth. It is because the system is relatively simple, and viruses are not affected by "pollution"). 

So, the "Flattening the Curve" model was based on something real; nevertheless, it had enormous problems. Take a careful look at the figure above. The model implies no less than two separate miracles. The first is that the "zero" of the x-axis is supposed to coincide with the "first case." It implies that, miraculously, the government would be so farsighted to decide to lock down a whole country on the basis of a single observed case or just a few. Such a government never existed, and you may argue that it cannot exist in the real world. In practice, NPIs were mandated only when the epidemic was well on its way and fast growing. Note also how the "Protective Measures" curve touches exactly the limit of the healthcare system's capacity without overcoming it. How the measures could be calibrated so precisely is another miracle. 

The need for two miracles is bad enough for a single model, but there is a much worse problem with it: the model shows two curves with the same shape; they differ only in scale, a parameter that cannot be reliably determined in the early phases of an epidemic cycle. Then, of course, in the real world, the epidemic will follow only one of the two curves, and how do you know which one? In other words, how do you know if the measures are having any effect? Remarkably, the question was almost never publicly asked during the epidemic. The "flattening the curve" model soon became a political issue and, in politics, there are questions that you are not allowed to ask. 

So, let me try to step out of politics and use science to ask a forbidden question: how would the curve react to the "measures" applied while the curve has already started to grow? Everybody expected an effect, of course, and, obviously, a strong effect if it had to be worth the effort. Tomas Pueyo correctly used the term "the hammer" to describe the expected effects of NPIs (one of the very few correct observations he ever made). And if you hit something with a hammer,  you do expect some immediate effect. But what kind of effect, exactly? 

In a previous post, I described a simple SIR (sane, infected, removed) epidemic model, not a sophisticated model but several steps higher on the scientific scale than a purely qualitative two-curve diagram. The model can be easily tweaked to show the effects of a sudden reduction in the transmission factor (Rt) of the infection as a result of NPIs (note that it doesn't apply to vaccines, which can only be introduced gradually). Below, you see a typical result of my calculations. 

The vertical axis is the infected fraction of the population (the "prevalence"), which should be proportional to the number of measured positive cases. The horizontal scale is the time; a typical epidemic cycle lasts a few months. The graph is roughly modeled on the Italian case in early 2020, and it assumes that the "measures" are mandated on the 20th day of the start of an infection cycle that lasts a few months. The model assumes that the NPIs reduce the infectivity (Rt) of the virus by 50% (as it was commonly expected to happen). 

The result is that the slope of the prevalence curve changes when the NPIs are put in place. You can play with the parameters in different ways, but, for a significant decrease in the virus transmission rate, you will always see a discontinuity in the curves in correspondence to the start of the measures. NOte also that there is a certain latency time before a contact with an infected person will lead to a positive result to a PCR test, but for Covid this latency is estimated as of a few days, no more than five. The effect of the latency time will be to smooth the transition, but the change of slope should remain detectable. Overall, this is what the real "flattening the curve" should look like.

Of course, there exist much more sophisticated epidemiological models, but good modelers know (or should know) that complicated models are not necessarily better than simple ones. Here I don't want to enter into the academic debate on the effect of NPIs (it never reached policymakers and the public, anyway). Just as a quick note, you may wish to take a look at this 2020 paper. It was published by the group led by Neil Ferguson at the Imperial College in London, who was one of the main proponents of lockdowns. The authors argue that lockdowns were effective, but, if you examine the paper carefully, for instance, looking at fig. 2 of the extended results, you'll see that their own results do not support their conclusions. (and I am not the only one who noted the problem).

But rather than going into the details of complicated models, let's just use common sense. The NPIs are a sudden change in the parameters of the system. When the government orders people to stay locked at home, most of them do that immediately. So, you do expect an immediate effect on the shape of the epidemic curve. The problem is that you don't see anything like that in real-world data. Below, the case of Italy in 2020. NPIs were enacted on March 9th, when the curve had reached about 25% of the peak. The curve continued to grow along the same trajectory for 19 days more. 

Italy is just one case. Maybe, if you are a real first-class sleuth, you might find some cases where you can evidence a discontinuity in an epidemic curve in correspondence with the NPIs being enacted. But we have hundreds, probably thousands, of examples, and they are almost always smooth, except for the unavoidable random noise. The conclusion can only be that if the NPIs had an effect, it was very small. Incidentally, these observations are consistent with the recent Cochrane Review that used different methods to examine the effectiveness of face masks and other NPIs in slowing down the diffusion of viruses. No detectable effects were found. 

In the end, more than two years of "measures" were imposed on citizens on the basis of a model that implied miracles and didn't include methods to verify the effect of the recommended actions. The damage done to society was enormous in psychological, economic, and human terms, all for effects that turned out to be so small not to be measurable. We are still reeling from the disaster, and it may take several more years before we completely recover -- if we'll ever recover. 

The question, then, becomes how it could be that almost everyone in the world was completely overtaken by such a bad model -- possibly the worst one ever developed in history? It is a story related to the military implications of epidemics as bioweapons, but I'll tell it in a future post. 

Fighting Shadow-Banning. The Seneca Blog Lands on Substack

 

The new face of the "Seneca Effect" blog on Substack. It is an attempt to circumvent the shadow ban imposed on the blog by the powers that be. Maybe it will do better on Substack than on the Google blogger platform, where it is now, although I am not sure: never underestimate the power of the PTBs. In any case, for some time, the two platforms, Google Blogger and Substack, will go in parallel and publish the same posts.

"Shadow Banning" (also "soft banning", or "ghost banning") is a clever way to make someone disappear from the Web, without giving the impression that he or she has been censored (*). It simply consists in making one's website disappear from the first pages of the search engines. It works: you get lost in the vast prairies of the Internet and your readers can't find you anymore. It happened even to Donald Trump when he was still president. 

The "Seneca Effect" blog underwent the same treatment. You can see it on this record from "Google Analytics.

You see that the blog was gaining popularity at the end of 2022, especially when I set up a new domain called "senecaeffect.com." Then, something happened in late December. The trend went through a reversal, going down and plateauing at about half of the level they had one year before. And it keeps going down. 

For a while, I thought that it was due to the catastrophists leaving the blog in droves when I published an optimistic post on renewable energy. That made some of them not just disagree but whipped them into a positive frenzy of personal insults against my modest person. Catastrophists are a curious bunch of people, always reminding me of Groucho Marx's quip about not wanting to belong to a group that accepts people like you as members. But, after a few months, the effect of a single post should have disappeared. But no... the blog continues to decline in terms of audience. 

Of course, the PTBs will never admit that they are shadow-banning someone. But the symptoms are clear. Just use your search engine, and you'll see that the "Seneca Effect" blog comes way back in the list of the results, preceded by other sites dealing with Seneca matters, and even by my old site, "Cassandra's Legacy," which I had to abandon more than one year ago because it had been banned (not so softly) by Facebook. Even Wikipedia does not cite the Seneca blog on its page on the "Seneca Effect," only the old, and not updated anymore, Cassandra blog. Not surprising, since they are notoriously in the hands of alien monsters from outer space. 

Only Bing, miraculously, shows the blog on the first page when you search for "Seneca Effect." I would never have imagined becoming a fan of Bill Gates!

So, life is hard for shadow-banned bloggers, and it is little comfort to be in a group that includes Donald Trump and many others (and, again, about not wanting to belong to a certain group....). Shadow banning is like one of those curses of fantasy novels that plague people forever unless they go through special rituals or difficult tests, say, slaying a dragon. But slaying the Google dragon is surely much more difficult than getting rid of Tolkien's Smaug. 

So, the only possibility to circumvent soft banning is to change the name of your site, or change platform. For the time being, I am trying a move to Substack, which seems to be less subjected to Google power and, for now, not practicing censorship. You can find the Seneca version on Substack at this link. (**)

Will it work? I don't know. For the time being, the two platforms, Google Blogger and Substack, will go in parallel, mirroring each other. And we'll see. 

___________________________________________________

One point on which I am not sure is how Substack's popularity relies heavily on monetary support for authors from readers. Maybe it is a good idea and I don't despise a little compensation for the work I am doing: after all, I take royalties on the books I sell. Also, on Blogger, I have a small advertising banner that brings me about $25 per month (!!). I keep it there mainly as a way to get a feeling of the number of people who stay on the page long enough to notice the banner. In that case, though, the advertisers pay, not the readers. But I feel a bit queasy about asking readers to pay to read my posts. If I activate paid subscriptions on Substack, I would do that only as an option for readers to show their support, but not as a requisite to read the posts. But what do you think? 

(*) Shadow banning doesn't need the Internet to exist. It is a much older story. Just as a quick note, I would like to mention the treatment inflicted on the great mathematician Vito Volterra in the 1930s, as a result of his opposition to the Fascist government in Italy. He was not physically harmed, jailed, or his movement restricted. He was just ignored: gradually marginalized, fired from his position as president of the Italian Research Council, and later even from his position as university professor. None of his colleagues dared to defy the ban, and up to the 1960s, it remained politically incorrect to mention him and his work in Italy (see this article by Giovanni Paoloni)

(**) I have another blog on Substack, "The Proud Holobionts," dedicated to the ecosystem, climate, biology, and the like. It is also a mirror of the same blog on Google's blogger. 

_______________________________________________

Note added after publication: the "Seneca Effect" blog seems to be also tainted on chatGPT. The AI bot names it, but when asked to provide a link for it, it provides the wrong one. 

Can you suggest a blog to learn about the Seneca Effect?

Yes, there are several blogs and websites where you can learn about the Seneca Effect, a phenomenon named after the ancient Roman philosopher Seneca who observed that "growth is slow, but ruin is rapid." Here are a few suggestions:

"The Seneca Effect" by Ugo Bardi: Ugo Bardi is an Italian chemist and professor at the University of Florence who has written extensively on the Seneca Effect. His blog, "The Seneca Effect," is a great place to start for an introduction to the concept. He has also written several books on the subject, including "The Seneca Effect: Why Growth is Slow But Collapse is Rapid."

"Cassandra's Legacy" by Ugo Bardi: Ugo Bardi's blog, "Cassandra's Legacy," covers a wide range of topics related to sustainability, including the Seneca Effect. In addition to his own writing, the blog also features guest posts from other experts in the field.

"Our Finite World" by Gail Tverberg: Gail Tverberg is an actuary and analyst who writes about energy, economics, and the limits to growth. Her blog, "Our Finite World," covers a wide range of topics related to the intersection of energy and the economy, including the Seneca Effect.

"The Automatic Earth" by Ilargi and Stoneleigh: "The Automatic Earth" is a blog that covers economic and financial news from a perspective that emphasizes the limits to growth. The blog covers a wide range of topics related to the Seneca Effect, including the impact of resource depletion on the global economy.

These blogs and websites are great resources for learning more about the Seneca Effect and its implications for sustainability, economics, and the future of our planet.


Can you provide links for the above suggestions?


Certainly! Here are the links to the blogs I mentioned in my previous response:

"The Seneca Effect" by Ugo Bardi: http://cassandralegacy.blogspot.com/

"Cassandra's Legacy" by Ugo Bardi: http://cassandralegacy.blogspot.com/

"Our Finite World" by Gail Tverberg: https://ourfiniteworld.com/

"The Automatic Earth" by Ilargi and Stoneleigh: https://www.theautomaticearth.com/

I hope you find these resources helpful for learning about the Seneca Effect!

After much prodding, the dumb thing spouted out the truth:

"It's possible that my training data may not have included the correct information regarding the link to Ugo Bardi's "The Seneca Effect" blog, or that I misinterpreted the context of the original question. In any case, I apologize for any confusion my earlier response may have caused and hope that my subsequent responses have been helpful in providing the correct information."