It Was Like a Beggar Bragging About His Income 100 Reincarnations in the Future

In my post "Some Brain Wave Analysts Are Like 'Face of Jesus in My Toast' Claimants" I compared certain neuroscientists to someone who looks at his toast every day, year after year, looking for something that might look like the face of Jesus. A person looking for the face of Jesus in his toast might be frustrated after many days and years of such activity with no success. He might then resort to taking pictures of his toast every day, and playing around with image manipulation algorithms such as sharpening, contrast adjustment, color alteration, saturation adjustments, solarization, Gaussian blur, and so forth. Finally, after torturing the photographic data every day in many different ways, for hundreds or thousands of days, he might announce he has a photo that looks a little like the face of Jesus. 

Such "keep torturing the data until it confesses" tactics are extremely dubious. But they go on abundantly in neuroscience and fields such as astrophysics, evolutionary biology and cosmology. The modern neuroscientist has 1001 ways to play around with data until it rather seems to suggest some story to his liking. 

Such "keep torturing the data until it confesses" funny business also goes on abundantly in the field of cosmology. We saw a big example of that recently in an article on the Big Think website, a site which  often gives us very bad examples of bad reasoning and misleading language. The article by a scientist is entitled "The Case for Dark Matter Has Strengthened." Nothing of the sort has happened, just something like "keep torturing the data until it confesses," or even worse.

The theory of dark matter arose because scientists observed stars rotating around the center of our galaxy at a rate different from the rate predicted by gravitational theory. To try and resolve this discrepancy, astrophysicists created the theory of dark matter: the idea that each galaxy such as ours is within a much larger cloud of invisible matter. The theory required very specific assumptions about the distribution of this dark matter: the idea that our disk-shaped galaxy is surrounded by a spherical halo of dark matter. 

For decades scientists "bet the farm" on the Lambda Cold Dark Matter theory, a move which made little sense. There were never any direct observations of any such thing as cold dark matter, so scientists had to claim it was invisible.  And even though cosmologists and astrophysicists believed in it with a fervor, cold dark matter never had any place in the Standard Model of Physics. How ironic that scientists often blast people for having faith in important invisible realities, when they have put such unquestioning faith in things they say are important, invisible and never directly observed: dark matter and dark energy.  Maybe their thinking is: "you can believe in important invisibles but only OUR important invisibles." 

One of the biggest reasons for rejecting this theory of dark matter is that the location of our galaxy's satellite galaxies does not match the location predicted by dark matter theory. Our Milky Way galaxy is surrounded by more than a dozen much smaller "dwarf galaxies." The Dark Matter theory predicts that such satellite galaxies should be randomly distributed in a spherical volume surrounding our galaxy. But instead our galaxy's satellite galaxies are found in a disk-like distribution, near the plane of our disk-like galaxy. The Big Think article confesses, "There has been one observation that is extremely difficult for the dark matter camp to explain: the distribution of small galaxies surrounding bigger ones."  

The article makes this confession:

"The Milky Way is a spiral galaxy, which means it looks a little like a spinning disk, about 100,000 light-years across and 12,000 light-years thick — essentially a cosmic pizza pan. This is the shape of the visible stars and galaxies. However, dark matter theory says that dark matter is essentially a big, spherical cloud, maybe 700,000 light-years across, with the Milky Way located at the center. Because dark matter is important in galaxy formation, dark matter theory suggests that the satellite galaxies of the Milky Way should also be spherically distributed around it. On the other hand, if dark matter isn’t real, and the correct explanation for speedily rotating galaxies is that the laws of physics must be modified, scientists predict that the satellite galaxies should orbit the Milky Way in roughly the same plane as the Milky Way — essentially extensions of the Milky Way itself. When astronomers measure the location of the 11 known satellite galaxies of the Milky Way, they find that they are located in the plane of the Milky Way. Furthermore, the observed configuration is very improbable from a dark matter point of view."    

Instead of favoring the dark matter theory, the positions of our galaxy's satellite galaxies favors a different theory, the theory of MOND (Modified Newtonian Dynamics), an alternate theory of gravity. So how does our Big Think scientist attempt to deal with this embarrassing situation? In a section most ridiculously titled "Another Win for Dark Matter," we read this (referring to Leo galaxies that are two of the 12+ satellite galaxies of our galaxy):

"Both Leo galaxies are currently located approximately in the plane of the Milky Way. However, the other, closer satellite galaxies are more spherically distributed, although not completely so. If the Leo satellites are excluded from the analysis, the data no longer strongly favors the modified physics hypothesis. Importantly, when the motion of the Leo galaxies is measured by the Gaia satellite, the authors found that their location in the plane of the Milky Way is a temporary one. When they project their location a billion years into the past or future (a blink of an eye, cosmologically speaking), these galaxies are no longer located in the galactic plane."

Here we have several ridiculous maneuvers or errors:

(1) The first ridiculous maneuver is an appeal to some analysis in which you simply ignore two of the 12+ satellite galaxies of our galaxy. That is utterly senseless. There are more than 12 of these satellite galaxies, and you should be paying attention to all of them. Arbitrarily excluding two of the 12+ dwarf galaxies from the analysis is like some male saying to his girlfriend, "If you exclude from your analysis my $150,000 college debt and my $35,000 credit card debt, you'll see my financial picture looks pretty good."

(2) The second ridiculous maneuver is making some projection of satellite galaxy positions a billion years into the past and a billion years into the future, in order to try to escape the embarrassing present data that contradicts the theory you are arguing for.  We don't know what the position of satellite galaxies will be a billion years from now, nor do we know what their position was a billion years ago. All we know is what their position is now, and that is all we should be considering. Asking someone to ignore the present position of the galaxies and consider some projected position a billion years from now is like some male (whose income is from street begging) asking his girlfriend to ignore his current financial condition, and to consider his financial condition 100 reincarnations in the future, when he may be a billionaire. It is also utterly deceptive to be referring to a billion years as "a blink of an eye." Even in cosmological terms, a billion years is one thirteenth of the age of the universe, something vastly different from "a blink of an eye."

(3) The author has erroneously claimed that the Milky Way has 11 satellite galaxies, even though the article here tells us that the Milky Way has at least 14 satellite galaxies, and the paper here gives in Figure 1 a chart listing the names, masses and luminosities of 18 satellite galaxies of the Milky Way, while stating "The Milky Way has at least twenty-three known satellite galaxies." The author refers to a paper here that has arbitrarily chosen to analyze only 11 of these satellite galaxies, apparently failing to recognize the paper was analyzing only a subset of the Milky Way's satellite galaxies. 

The Big Think article show an extreme example of some of the worst tendencies of today's scientists: their tendency to try to slice, dice, twist, shake, contort and distort beyond recognition observational data they don't like. It would be charitable to call such tactics "keep torturing the data until it confesses." A better description would be "keep torturing the data like crazy until you get the faintest hard-to-understand mumble or whisper, and then claim that sound you didn't understand was a confession."

This type of thing goes on all the time all over the place in the world of science:

• What happens when an animal experimental study produces merely a null result? The data is "fixed" by throwing out certain observations, which is justified on the basis of "excluding outliers."
• What happens when a human experimental study fails to produce anything but a null result? The data is "fixed" by throwing in some new "qualification criteria", which is used to exclude certain subjects that helped to prevent a reporting of a positive result. 
• What happens when a genome did not have the right characteristics wanted for some evolutionary story line? The problem is "fixed" by replacing that genome with some "projected genome" using the guesswork called phylogenetics. 
• What happens when astronomical objects have some position not matching what is predicted by some favored theory? The problem is "fixed" by replacing the current known positions with projected positions thousands, millions or billions of years into the past or future. 
• What happens when a study fails to support the hypothesis it was trying to support? The problem is "fixed" by creating a new hypothesis in the middle of doing the study. This example of Questionable Research Practices (called HARKing or Hypothesizing After Results are Known) is not possible when a study is pre-registered or a "registered report." But most studies are not pre-registered or a "registered report."
• What happens when a study looking for some effect fails to find any good evidence for the effect? The problem may be "fixed" by gathering more data, or trying a different set of test subjects. As soon as the effect barely shows up, the gathering of data is stopped, lest things be spoiled by having the "statistically significant" result disappear when still more data is gathered.  

In the paper "The Dubious Credibility of Scientific Studies" by Natalie Ferrante of Stanford University, we read this:

"The current process of undertaking, implementing, reviewing, and finally publishing a scientific study is riddled with flaws, as study results are subjected to many biases and interpretations at every level between inception and publication. As a result, when these studies finally reach the public, they are often depicted in ways that fail to reflect the genuine results and are at times utterly incorrect. Industries touting their products, scientists influenced by grants and prestige, reviewers adhering to personal

political agendas, and journalists pressed to sell papers all in turn contribute to the inherently skewed depiction of scientific results to the public. These factors have allowed for a highly unpredictable credibility in scientific reporting, an observation that has been highly overlooked and disregarded. The dissemination and publicity of this incorrect or skewed information, which is believed to be scientifically accurate, can have a detrimental effect on the public in their everyday lives." 

Do Scientists Prefer That Science Writers Lack Deep Knowledge of Topics They Write About?

Science journalism is currently in a bad state. Most days when I read science news sites, I read at least one article written by some science journalist making untrue claims. Science journalists routinely write articles with triumphal click-bait headlines that are not justified by anything reported in the article. Science journalists routinely parrot unjustified boastful claims made by scientists. Instead of acting like good journalists who critically analyze the claims of people with a motive for boasts and self-promoting claims, our science journalists tend to act like credulous cheerleaders. 

The result is often what we can call a North Korean style of journalism. Just as North Korean journalists reverently pass on every claim from their government officials, treating such proclamations rather like sacred revelations not to be doubted, our science journalists reverently pass on every claim from professors, treating such proclamations rather like something written on stone tablets by the finger of God. 

Key facts are very often withheld in the stories of science journalists, and misleading language is often used. An example we see again and again is when a story reports that some life-related chemical is found in space. The key relevant fact in all such stories is: in what abundance was the chemical detected? But the science journalist will typically give no mention of such a key fact. The reason is that the abundance found is typically some negligible amount, maybe something like one atom per cubic kilometer. There will be typically some phony headline such as "Key Building Block of Life Found in Space." The chemical mentioned will typically not be an actual building block of life. 

The visual below shows some of the main sins of today's typical science journalist:

There are economic reasons that help explain such poor behavior by science journalists. The science journalist is part of a profit complex that I have called the Academia Cyberspace Profit Complex. Within such a complex, misleading but interesting-sounding or triumphal headlines or science paper titles are strongly encouraged. Web sites have "science news" headlines, and clicking on such headlines leads to pages containing ads. The more people view those pages, the more ad revenue the web site gets. Such a situation strongly encourages the writing of stories with misleading but interesting-sounding or triumphal headlines. The more such stories appear, the more money a web site can make. Scientists are also incentivized to write papers with misleading but interesting-sounding or triumphal headlines. Such headlines tend to increase the number of paper citations the paper receives, and the number of such citations is a performance metric used to judge the success of scientists. The diagram below shows some of the economics going on in this Academia Cyberspace Profit Complex, with profit events depicted in yellow.

An author describes the situation like this:

"The rise of mass marketing created the cultural substrate for the so-called post-truth world we live in now. It normalized the application of hyperbole, superlatives, and untestable claims of superiority to the rhetoric of everyday commerce. What started out as merely a way to sell new and improved soap powder and automobiles amounts today to a rhetorical infrastructure of hype that infects every corner of culture: the way people promote their careers, universities their reputations, governments their programs, and scientists the importance of their latest findings. Whether we’re listening to a food corporation claim that its oatmeal will keep your heart healthy or a university press office herald a new study that will upend everything we know, radical skepticism would seem to be the rational stance for information consumers."

Some of the reasons for the poor quality of science journalism are economic reasons hinted at above. Another major reason for the poor quality of science journalism is that science journalists very often lack deep knowledge about the topics they are writing about.  In the US most science journalists seem to lack any science degree, even a bachelor's degree with a major in one of the sciences. The Global Science Journalism Report for 2021 got responses from 600+ science journalists, after trying to get answers from 800 of them. On page 16 we read this:

"Almost all participants who provided information about their training background (n = 617) report having a university degree (96%). Of these, most have a university degree in science (42%), a third have a university degree in journalism (37%) and 17% have a university degree in other areas."

On the same page we are told that only 43% of the science journalist respondents in the US and Canada have any degree in science. We may presume that the actual number of science journalists in the US having a bachelor's degree or higher in science is probably less than 40%, because about 25% of the people sent the survey did not answer, and people lacking science training would probably be among the most likely not to answer a survey that included questions asking about qualifications. 

Some science journalists have a Master's Degree in "Science Communication," which does basically nothing to establish them as being qualified to write about most of the deep topics they write about. For example, Stony Brook University of SUNY offers a Master's Degree in Science Communication, which requires only 33 credits (1 or 1.5 years of study).  None of the courses are regular science courses.  

Do we hear scientists complaining about the depth of science knowledge of science journalists? I have never heard a scientist make such a complaint. We may wonder whether scientists actually want for science journalists to be people who lack deep knowledge about the topics they write about. Why is that? It seems that the greater a person's knowledge on a topic, the more likely that person would be to challenge dubious and unwarranted claims from scientists, and the more likely they would be to report skeptically when scientists make dubious boasts.  

Imagine you are a neuroscientist who has just produced another one of those poorly designed experimental studies involving rodents, fear and memory. If you have made some triumphal claim such as "New evidence for memory engrams discovered," the last thing you want is for some press release on your study to be written by someone who is very knowledgeable about neuroscience and the many dire problems in current neuroscience research. For then instead of getting the desired press release or news story with a headline like this:

        Scientists Locate Cells Storing Memories

you might instead get a story with a headline like this:    

       Scientists Claim to "See Memories," But Was It a False Alarm?

On page 28 of the Global Science Journalism Report we have a sobering response from the survey of 600+ science journalists. Roughly half of them agree with the statement "Science journalism is primarily 'cut, paste and translate' from US and UK science outlets." So about half of our science journalists apparently think their role is mainly to just parrot whatever claims they receive, rather that critically judging them. 

Nowhere in the Global Science Journalism Report do we get any indication that our science journalists regard themselves as having a role of presenting balanced views or critically analyzing the claims made by scientists. It seems our science journalists have been conditioned to act like North Korean journalists, who reverently pass on all claims they receive from government officials. One of the responsibilities of a good journalist is to ask people tough questions. When our scientists are interviewed by science journalists, it seems the science journalists ask nothing but the softest of softball questions. 

The online Quanta Magazine supplies us with endless examples of appalling science journalism, often written by writers who seem to have no deep knowledge of the deep topics they are talking about. We endlessly read on this site descriptions of junk science studies that are trumpeted as great breakthroughs. The latest example of such journalism is an article entitled "How the Brain Distinguishes Memories From Perceptions." Right after the title we have this subtitle claim: "The neural representations of a perceived image and the memory of it are almost the same." There is actually zero evidence that there exists in the brain any such thing as a neural representation of a perceived image or a neural representation of a memory. The only evidence we have for any type of representation in a brain is the DNA representation of very low-level chemical information such as amino acids, which occurs through combinations of nucleotide base pairs. Such representations are found in pretty much all cells in the body.  When they scan brain tissue, scientists never see anything looking like representations of remembered or perceived objects. Any claims to the contrary are examples of pareidolia, rather like people claiming to see the face of Jesus in their toast. 

We then have in the Quanta Magazine article the groundless claim that some paper "has identified at least one of the ways in which memories and perceptions of images are assembled differently at the neurological level." Neuroscientists have no understanding at all of how memories could be assembled at the neurological level, and no credible theory of how such a thing could occur. An examination of the paper  being touted ("Perception and memory have distinct spatial tuning properties in human visual cortex") quickly reveals that some severe cases of Questionable Research Practices are occurring. It's a brain scan study that used only 9 subjects, which is way, way too small for any kind of reliable result. Another paper tells us that even study group sizes of 200 are too small to produce a reliable result in brain scanning studies, telling us this: "These findings suggest that samples consisting of ~200–300 participants have in reality still low power to identify reliable SBB-associations [structural brain behavior associations] among healthy participants."  Similarly, another paper was entitled "Reproducible brain-wide association studies require thousands of individuals." So if you need thousands of brain scan subjects for a reliable, reproducible result, and your study only used 9 subjects, how big a shortfall did you commit? A shortfall of hundreds of times. It's like trying to build a house not with 3-meter-long 2-by-4's, but with wood strips the size of match sticks. 

Having no blinding protocol (very much needed for a study like this), the paper being hailed by Quanta Magazine confesses its own lack of statistical power, saying, "Given the small sample size of both our study and that of Breedlove et al., and the small size of the expected effect, future work should adjudicate between the predictions of these models with a highly powered experiment." That's basically confessing that your study bungled, but crossing your fingers that maybe someone in the future will get something similar after following proper research standards. The paper tells us how it used four different types of datasets that it calls "artificial datasets," which is another word for fictional data. If you took a Science Procedures 101 course, one of the first things you might learn is: analyze real data coming from your observations, not fictional data you simply made up out of thin air. Do we hear in the Quanta Magazine story hailing this junk study that only 9 subjects were used? No. It's rather like the operating rule of such stories is "hide the dirty laundry and never list the tiny sample size." 

And so it goes on, again and again and again in Quanta Magazine: science journalists enthusiastically hailing poorly-designed junk science research that is suitable for little more than wrapping fish and lining the bottom of bird cages.  It's rather like our Quanta Magazine writers never learned a single principle regarding how to distinguish robust science from junk science. Such are the kind of science writers our universities like to have, particularly when employed as press release writers. 

Do college press offices fill job openings with ads like this?

In the recent post here by Scientific American columnist John Horgan and the recent post here by Peter Woit of the widely read Not Even Wrong blog, you can read about Quanta Magazine's ridiculously  credulous coverage of a baloney story claiming that physicists had created a spacetime wormhole, one of the staples of science fiction. It seems that someone at that magazine had passed on this not-actually-true story (which physics expert Woit calls a mere publicity stunt) as real news. Similar stuff goes on in their coverage of biology.  The supposed "wormhole" merely existed in some speculative computer simulation. Hilariously, the Quanta Magazine writers call themselves "the best team in science journalism." 

US COVID-19 Deaths = 1 Million+, Lessons Learned = 0?

Smithsonian Magazine recently had an article entitled "Six Lessons We’ve Learned From Covid That Will Help Us Fight the Next Pandemic." The items listed as "lessons learned" from COVID-19 are:

(1) "We need to rapidly scale up testing."

(2) "We need to leverage data more effectively."

(3) "We need to seek out a diversity of voices."

(4) "We need to continue making big bets on vaccines."

(5) "We need to actively crowd out bad information."

(6) "We need to infuse public health communication with vulnerability."

I rather doubt whether any of these statements list any of the most important lessons that should be learned from the COVID-19 fiasco. Item #3 sounds like something rather promising, but it is basically neutralized by Item #5.  The explanation of Item #5 gives us some language that indicates that the author has failed to learn one of the biggest lessons we should have learned from the COVID-19 fiasco, which is: don't demonize people you are trying to persuade to take a particular action. 

An article at the Yale Medicine web site lists these "lessons of COVID-19," none of which is any of the chief lessons of the pandemic:

Lesson 1: Masks are useful tools.

Lesson 2: Telehealth might become the new normal.

Lesson 3: Vaccines are powerful tools.

Lesson 4: Everyone is not treated equally, especially in a pandemic.

Lesson 5: We need to take mental health seriously.

Lesson 6: We have the capacity for resilience.

Lesson 7: Community is essential—and technology is too.

Lesson 8: Sometimes you need a dose of humility.

We already knew before the pandemic that masks are useful tools during a pandemic, and that vaccines are powerful tools; and most of the other items are platitudes. 

Reading about ten different articles after doing a Google search for "lessons learned from the COVID-19 pandemic," I can find no sign that our authorities have learned some of the main lessons that should be learned from the COVID-19 fiasco. Below is my list of some of the lessons that should have been learned. 

Lesson #1: Don't recklessly experiment with the genomes of lethal viruses in laboratories lacking the highest possible security measures, and don't fund foreign experimentation with lethal viruses.

We still don't know whether the COVID-19 vaccine originated from some purely natural event or as a leak from a laboratory that was recklessly experimenting with virus genomes.  Referring to Intelligence Community elements (IC elements) such as the CIA, a US government document stated that "four IC elements and the National Intelligence Council assess with low confidence that the initial SARS-CoV-2 infection was most likely caused by natural exposure to an animal infected with it or a close progenitor virus," but that another intelligence community element concluded with higher confidence ("moderate confidence") that "the first human infection with SARS-CoV-2 most likely was the result of a laboratory-associated incident, probably involving experimentation, animal handling, or sampling by the Wuhan Institute of Virology." A US Senate report favored the lab leak hypothesis. But the origin of COVID-19 is still an unanswered question. As long as there is still a  large chance that COVID-19 arose from a lab leak, the supreme lesson that must be drawn from the COVID-19 fiasco is a lesson to take every measure to minimize the chance that any genetic laboratory will release a pathogen in the future. All signs are that the scientific community has failed to heed this lesson. Apparently nothing has been done to improve security at gene-splicing labs, or to reduce the chance of future pandemics arising from scientific experimentation. 

Lesson #2: Pay the greatest attention to important-seeming novel phenomena, rather than ignoring such phenomena or trying to minimize their importance.

In the US we had the most enormous failure to pay attention to  COVID-19 when it was spreading in January and February 2020.  In a January 27, 2020 interview on Fox News, Anthony Fauci stated this about coronavirus spreading in the United States (at the 1:42 mark): "The risk right now in the United States is really low." Rather than raising a loud-and-clear alert to the graveness of the threat, Fauci said that in the interview "I'm saying don't worry, and don't be afraid."  He failed to alert the public health system to the coming danger on January 27 in any kind of noticeable way that would attract attention.  By mid-February it should have been all the more clear to any forward-thinking epidemologist that the United States faced a grave peril from coronavirus. On January 30, 2020, the World Health Organization had officially declared coronavirus a "global health emergency." But Fauci predicted on February 3, 2020 that there would be a "dampening down" of US coronavirus cases. And in a February 17, 2020 interview with USA Today, Fauci suggested that coronavirus was nothing much to worry about in the US.  In the USA Today article from February 17, we read: "Fauci doesn't want people to worry about coronavirus, the danger of which is 'just minuscule.' "  In a February 13, 2020 statement, the CDC issued an extremely weak statement about coronavirus that failed to attract much of any attention, saying nothing more alarming than this vague assertion: "There will likely be additional cases in the coming days and weeks." By February 26, 2020 the CDC had detected evidence that coronavirus was spreading in the US. But rather that issuing a very strongly-worded "scream bloody murder" warning that people would pay attention to, the CDC issued a mild-sounding statement failing to alert anyone of a grave public threat. 

A failure to pay attention to many types of novel important-seeming phenomena has been the most gigantic failure of most of the scientific community for a very long time. For more than two hundred years there have occurred a wide variety of paranormal phenomena, phenomena which are of very great importance in assessing such basic questions as whether humans have a soul or whether the human mind is purely the product of the brain. For two hundred years the policy of mainstream professors has been essentially "just ignore anything that doesn't fit in with my view as to how reality works." There have been disastrous intellectual and moral results of such a failure to pay attention to phenomena, with generations of people getting wrong ideas about the nature of themselves and other humans. But at least such failure to study things did not produce any medical disasters. Finally in the year 2020 the nation ending up paying for our scientist's long habit of being inattentive to important-seeming novel phenomena.  While our scientists were "asleep at the switch," COVID-19 spread all over the country between January and April 1, 2020. But no lesson has been learned here. The "ignore important-seeming novel phenomena" principle still seems to prevail in academia, where professors continue to ignore a host of important psychical phenomena they should be paying very great attention to. 

Lesson #3: When extremely important public health advice is to be presented to the public during a pandemic, make sure it is presented by figures of maximum credibility and consistency who have no record of error on the topic they are speaking about. 

When a pandemic occurs it is of the utmost importance to have the government's message being delivered by advocates of the highest credibility. If you want people to be wearing face masks and you want people to be taking vaccines, then the officials urging such things on our TV screens should be figures with the highest credibility and figures with an unblemished record of competence relating to the pandemic they are talking about. But during 2020 and 2021 the dominant TV spokesman on these topics was Anthony Fauci. 

By May of 2020 Fauci's credibility on COVID-19 had been severely damaged by at least two problems (I won't mention a third big issue that is widely discussed):

(1) Fauci's failure to properly alert the public about COVID-19 during early 2020, as shown by the statements of his I quoted above. 

(2) The bad advice about wearing face masks Fauci gave during March 2020, when he stated, "There's no reason to be walking around with a mask," at a time when COVID-19 was spreading like wildfire in New York City.

The US television coverage about COVID-19 during 2020 and 2021 seemed to be dominated by the appearances  of Anthony Fauci. Changing my channel between the 6:30 evening news on ABC, CBS and NBC during 2020 and 2021, I would often seem to see Fauci on all three programs. It quickly became evident that Fauci was a polarizing figure who many millions did not trust, and polls showed that fewer than 50% of Republicans trusted him. But it seemed that whenever the main television networks wanted to interview a government official, it was most often Anthony Fauci showing up on our TV screens.  We also often saw a surgeon general who had changed his advice about whether we should wear masks. 

The US airwaves should have been presenting us public health authorities who had always taught the same thing about COVID-19, and who had an unblemished record of advising us correctly on this topic. As you can see here, the death rate of about 332 per 100,000 in the US ended up being several times greater than in most of the world's countries, suggesting a massive failure of the government to persuade sufficiently. 

Lesson #4: Don't demonize people whose behavior you are trying to change. 

Hillary Clinton won the popular vote in the 2016 election, but lost the electoral college vote to Donald Trump. Part of the reason she lost was a big political mistake she made, referring to people supporting Trump as a "basket of deplorables." When you are trying to change the behavior of people (whether it is getting them to vote a particular way or to wear a face mask or get a vaccine shot), it makes no sense to demonize such people. Doing such a thing will backfire, making it less likely than ever that their behavior will be changed. In the mainstream's attempt to get people to wear masks and take vaccines, endless examples of demonization attempts occurred, in which various demeaning insults were hurled by authority figures at those people whose behavior such authority figures were trying to change.  This was very bungled politics. 

Nowadays the term "anti-science" is a demonization term. The term is not correctly applied to people reluctant to take vaccines.  Science with a capital S means facts established by observation. Science with a lower S means the process of determining truth through systematic efforts such as observation, experimentation and classification. A person who chooses not to take a vaccine he should be taking is a person who may be guilty of an ethical error, but it is groundless to call such a person "anti-science." Similarly, it is groundless to call a person who chooses not to purchase some particular technological product "anti-technology," and it groundless to call a person who declines to have some particular operation "anti-medicine." Nowadays many people in the medical and scientific communities are being extremely careless in throwing around the demonization term "anti-science" towards people who disagree with them on scientific topics, often applying such a term to people who are pro-science in the sense of being supporters of attempts to establish truth using observations and experiments. 

Lesson #5: When new pandemics are getting started, we need all the watchdogs and "eyes and ears" we can get, without such sources becoming "sleeping watchdogs" because of follow-the-leader timidity.  

The failure of the press at the start of the COVID-19 pandemic was enormous. There was a failure by newspaper authorities, television authorities and internet information sources that could have alerted the US to enormity of the peril it faced in February and March 2020. In general such sources acted like "sleeping watchdogs" as our national house was invaded, maybe because of some timidity about "going out on a limb" by raising concerns that had not yet become "common wisdom." The post here documents the failure of one major science publication (the online Quanta Magazine) to properly alert the public to the COVID-19 peril in the spring of 2020.  The  post here documents the failure of another major science publication (the online version of The Scientist Magazine) to properly alert the public to the COVID-19 peril in the spring of 2020. The lesson for the watchdogs of the press is simple: as soon as you smell smoke, start barking loudly. 

Lesson #6: Don't forget that "never" can be much worse than "late."

There's an old expression "better late than never," and it applied during the COVID-19 pandemic. Millions chose to wait until quite a few millions had taken their COVID-19 shots, to make sure there wasn't any side effect showing up massively.  Once many millions had got their COVID-19 shots with few reported serious side effects, the "wait and see" rationale was gone, and there was little rationale for not getting a shot. Too many of the "wait and see" thinkers ended up never getting a vaccine. A "wait and see" rationale does not justify a "never" course of action. 

Lesson #7: Don't pretend to understand things you don't understand, and don't make knee-jerk dismissals of reasonable hypothetical explanations while unfairly characterizing supporters of such explanations. 

Perhaps the biggest blunder of today's scientists is their very frequent claims to understand things that they do not understand, such as the origin of human minds, the origin of adult human bodies, and the origin of mankind. COVID-19 gave us many further examples of such a tendency. For example, soon after COVID-19 appeared scientists immediately started making claims that they knew COVID-19 had a purely natural origin, at a time when they did not actually know how COVID-19 originated. Our scientists made knee-jerk dismissals of a reasonable hypothesis of a lab leak origin for COVID-19, while unfairly painting anyone supporting such a hypothesis as a "conspiracy theorist." The hypothesis of a lab leak origin was not actually a conspiracy theory, but a theory of human error and overconfidence.  A lesson we should draw from such a thing is: don't rule out reasonable hypothetical explanations of something while making mudslinging stereotype caricatures of reasonable people suggesting such explanations. That is very much a lesson our professors and experts have yet to learn; for they continue to haughtily dismiss many a reasonable hypothesis while making mudslinging stereotype caricatures of those presenting such ideas (the post here discusses one of many examples I could give of such behavior). 

The Court System Puts Its Trust in the Layman Not Experts

A certain type of writer will scold the independent thinker from forming opinions that may differ from the supposed majority opinion of some group of scientists. Such a writer will evoke a principle of "We must follow the experts, because they know their subject best." Such a principle is rarely recommended in any kind of universal way, but only in a very selective way. For example, the writer who wishes us to believe in the origin of mankind by mere random mutations will ask us to believe as evolutionary biologists believe, on the grounds that they are the experts in evolution. But such a writer will never ask us to form beliefs about the Catholic Church matching those of the main experts on the Catholic Church (Catholic clergy members), or ask us to form beliefs about psychic abilities matching those of the main experts on psychic abilities (parapsychologists).

There is a very good reason why we should not in general blindly follow a principle of "We must follow the experts, because they know their subject best." The reason is that people who have most thoroughly studied some subject matter tend to belong to belief communities that greatly affect their impartiality. Rather than getting objective impartial opinions on Topic X from some people who have most immersed themselves in Topic X, what we may be getting are opinions from people who are parroting speech customs and boasts of a belief community that has organized itself around a study of Topic X. The Topic X experts may be vested interests who very much stand to gain or lose based on the opinions the public has on Topic X. Such partiality may mean such experts may tend not to issue objective impartial opinions on Topic X. I can give a simple example. Do you want an objective impartial opinion about whether string theory is a grand insight into nature or mostly a waste of time for physicists? You are unlikely to get such an  objective impartial opinion from a physicist who has spent decades writing papers about string theory. Such a person is very much a vested interest. 

It is very interesting to consider that a very crucial part of modern American society is not at all based on any principle of "trust the experts," but is based on an opposing principle of "trust the layman." I refer to the American court system.

Let us consider how the American court system would act if it were organized around a principle of "trust the experts." Suppose a man named John Doe was put on trial, charged with the murder of Mary Roe.  If the American court system were organized around a principle of "trust the experts," then the guilt of John Doe might be decided by a jury composed like this:

(1) Seeking out what could be called experts on the topic of the defendant (John Doe), the jury might consist of John Doe's wife, John Doe's father, John Doe's mother, John Doe's brother, and so forth. The rationale would be that these were the ones that were most familiar with how John Doe would act, and therefore most qualified to judge whether John Doe had committed the crime. 

(2) Or, the jury might be composed of various professionals deemed to be experts. For example, if it were claimed that John Doe had killed Mary Roe using a knife, the jury might consist of the detective who had examined the crime scene, the doctor who had performed the autopsy, some expert on knife homicides, some blood expert who had studied blood at the scene of the crime, and so forth. 

(3) Or, the jury might consist of a mixture of the people who best knew John Doe (family members considered John Doe experts), and the professionals listed in the paragraph above. 

These would be the top experts on the defendant

Nothing of the sort occurs. Relatives of a defendant are not allowed to serve on a jury deciding the guilt of a defendant. And while a professional such as a detective or a coroner may be called to give expert testimony in a trial, such people are never allowed as jurors involving cases that they are involved with. If you were the detective investigating the death scene of Mary Roe, you will never be put on a jury deciding the fate of someone tried for murdering Mary Roe. And if you were the coroner doing the autopsy of Mary Roe, you will never be allowed on the jury deciding the fate of someone tried for murdering Mary Roe.

Why is this? Because in the court system "the impartial layman is king." Courts recognize, for example, that a relative of a defendant will tend not to be impartial, but will tend to be more likely to vote that such a defendant is innocent.  Courts also recognize that a detective who helped arrest a defendant is not impartial about the defendant's guilt, but will be more likely to vote in favor of the defendant's guilt, rather than telling his fellow juror members, "Oops, it looks like I made a big mistake by arresting the wrong guy." Courts also recognize that a coroner reaching some particular judgment during an autopsy would not be impartial during a jury deliberation, but would tend to vote in whatever way conformed to the autopsy judgments he had previously made. 

Following a rule of "the impartial layman is king," the court system arranges for the guilt of a defendant to be decided by a group of randomly selected persons, each of whom is a layman, not an expert. Very wisely, the court system recognizes that anyone can learn enough about some important matter by hearing a certain number of hours or days of testimony about the matter, pro and con. Also, very wisely the court system recognizes the supreme importance of exposing people to a balanced case, pro and con. Both the prosecuting attorney and the defense attorney are allowed to call witnesses, and to make opening arguments and closing arguments. So during the trial of John Doe, a witness will hear both the case for John Doe's guilt and the case for John Doe's innocence. 

We may contrast the wisdom of the court system with the foolishness of the "kneel to the experts" writers. Such writers try to suggest that the layman should never form his own belief on some topic that might differ from what the experts supposedly tend to think on the topic.  Such a suggestion is contrary to the practices of the court system that have prevailed for hundreds of years, in which layman are regarded as qualified to reach sound judgments after analyzing evidence independently. The worst foolishness of these "kneel to the experts" writers comes when they say we should not be exposed to balanced debate in which we hear from both those agreeing with the opinion supposedly popular with the experts and those disagreeing with such an opinion. Writers advancing such opinions are as silly as those claiming that when people are tried for a crime, the trial should allow only the prosecuting attorney to call witnesses and make a closing and opening argument, without allowing the defense attorney to even appear in the court room.  

What happens in modern academia is typically just as if the absurd opinions of such writers had prevailed. Our science textbooks do not provide balanced presentations on crucial topics such as biological origins, the nature of the human mind, and the evidence for psychical and paranormal phenomena. Instead the college student is given a textbook that is as one-sided and impartial as a trial presentation in which only the prosecuting attorney presented evidence. Such presentations are justified on the grounds that we should not shake the student's confidence in our experts.  A similar argument would be the ludicrous reasoning that when people are put on trial for murder, we should hear only the arguments of the prosecuting attorney, lest the public's faith in the district attorney and the police be shaken.