How to sharpen your bullsh*t detection skills

15 March 2021; updated 21 August 2023

The American philosopher Harry Frankfurt opened his 1986 essay, On Bullsh*t, with one of the most arresting sentences ever written in a serious philosophical work:

“One of the most salient features of our culture is that there is so much bullsh*t.”

On Bullsh*t

In this essay, and the subsequent bestselling book, Frankfurt defined bullsh*t as speech intended to persuade without regard for truth. And by that definition, we truly are living in the Age of Bullsh*t.

Given the giant steaming mounds of bullsh*t that are served up to us every day by the corporate media, social media, advertising (which is frequently indistinguishable from the former two), politicians, random YouTubers and Instagram ‘influencers’, and various persons who are designated as ‘experts’ (usually by people with no expertise in the subject matter), it’s absolutely crucial for all of us to develop an effective and reliable toolkit for detecting and defending ourselves against bullsh*t.

Fortunately, the legendary American astronomer, cosmologist, astrophysicist, astrobiologist, author and science communicator, Carl Sagan, provided just such a toolkit.

He titled a chapter of his 1995 book The Demon-Haunted World: Science as a candle in the dark, “The Fine Art of Baloney Detection”. (Perhaps Carl’s Mum raised him to be a nice boy who didn’t swear!)

The chapter is based on the “baloney detection kit” – a set of cognitive tools and techniques that fortify the mind against penetration by falsehoods – that scientists are (supposed to be) equipped with through their training.

Sagan stressed that this toolkit is equally applicable to non-scientists, as everyone needs to utilise healthy scepticism in their everyday lives.

With the manufactured COVID crisis now in the rear view mirror, all the usual suspects are attempting to drum up panic about ‘the next pandemic‘, which we’re assured is coming soon (from wild animals! Or from farmed animals. Or from… anywhere at all, really) and could be even deadlier than COVID (the horror, the horror).

Since one of the principal purposes of studying history is (supposed to be) to reduce the chances of the worst episodes repeating themselves, now seems like a good moment to work through the nine tools for baloney detection that Sagan shared, illustrating with specific examples from the COVID-1984 pandemic of bullsh*t.

Sagan’s Baloney Detection Toolkit

#1. Wherever possible there must be independent confirmation of the ‘facts’.

Remember back in the early days of the manufactured COVID crisis, when every time you watched news programs, or read a newspaper or online article on COVID-19, you were presented with various ‘facts’? ‘Facts’ like these:

  • SARS-CoV-2 is a novel coronavirus to which we have no pre-existing immunity. (But why would this be so, when the virus has many similarities to endemic coronaviruses that circulate every year, and the phenomenon of T cell cross-reactive immunity is well established?)
  • Infection with SARS-CoV-2 causes an entirely new disease entity called COVID-19. (But why was it called a new disease when all of its symptoms have been observed in other viral respiratory illnesses, and we already have a disease category – ‘influenza-like illness’ – to describe these symptoms?)
  • X number of ‘cases’ have been detected today. (Cases of what? Positive test results? Confirmed but as-yet asymptomatic infection? Clinical illness – as in people who actually have symptoms of illness?) And y number of people have died. (Of what, exactly? Did they show any signs of respiratory illness before they expired? Were they autopsied, or was their death merely assumed to be caused by infection with SARS-CoV-2 without any independent verification? Which criteria are being used to ascertain cause of death in that region, and how stringently are these criteria applied?)
  • We need to wear masks to protect ourselves and others. (But why, when all previous evidence reviews, as well as studies conducted during the manufactured COVID crisis, found no evidence that masks prevent the transmission of respiratory viruses?)
  • We have to maintain a specified distance from each other – 1 m according to the World Health Organization, China, Denmark and France; 1.5 m in Australia, Germany and Italy; and 6 ft [1.8 m] in the US – in order to ‘stop the spread’. (Is this even possible? If it was possible, would it actually be useful, or would it merely prolong the pandemic by delaying the development of herd immunity which protects the most vulnerable?)
  • The only way we can get our old lives back is for everyone on the planet to get vaccinated against the virus. (But why, when the vast majority of people who contract the virus either develop mild illness, or no symptoms at all? Wouldn’t we get a greater return on investment by developing more effective treatments for the small minority who become seriously ill?)
  • And on and on it went (and still goes).

Do you recall seeing a journalist ask for verification of these facts, rather than accepting the pronouncements of their interviewees at face value? Yeah, me neither.

Did the articles you were reading then, or are reading now, have references or hyperlinks to the source of those (purported) facts? If not, why do you read them? Journalists who do not cite their references, or – even worse – attribute them to an ‘expert’ without providing any means by which the reader can verify that the statements were actually made, or investigate whether the cited expert might be qualified to make them, are showing complete contempt for their readers and don’t deserve your attention.

If the articles you read do have hyperlinks to the source material, do you click on them, and read that source material to verify that the journalist’s representation of it was accurate? If not, why not?

I tell my clients, and members of my EmpowerEd health and nutrition education program, not to believe a word I say, but to follow up on the sources of information that I provide and check them out for themselves.

Please don’t give me the excuse that you don’t have time to do all this fact-checking for yourself. Decisions about your health are among the most important decisions you will ever make. They deserve your time and attention – far more so than the social media sites that the average person spends 151 minutes on per day. Invest your time in valuable activities, not bullsh*t.

#2. Encourage substantive debate on the evidence by knowledgeable proponents of all points of view.

One of the most disturbing aspects of the global response to the emergence of SARS-CoV-2 has been the determined suppression of scientific debate, which is the lifeblood of the entire scientific enterprise.

My ‘bullsh*t detector’ was activated back in March 2020, when Australia violated its own pandemic preparedness plan which was updated in August 2019, based on detailed evidence reviews. Notably, the word ‘lockdown’ does not appear once in this 232 page document, and ‘isolation’ is mentioned only in the context of ‘encouraging’ (NOT enforcing) the voluntary isolation of people with symptoms of influenza-like illness – not asymptomatic people who have ‘tested positive’ using a method that was not intended to detect infection.

However, my bullsh*t meter went deep into the red zone when I observed the vicious attack that was launched on Professor John Ioannidis after his article ‘A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data’ was published in March 2020 on STAT, an online health- and medicine-focused news website.

Ioannidis is a highly respected epidemiologist, counted among the 10 scientists worldwide whose published papers are currently most commonly cited by other scientists (6000 new citations per month).

His paper, ‘Why Most Published Research Findings Are False’, is the most-accessed article in the history of Public Library of Science, with over 3 million views.

So, even if we bear in mind point # 3, the airy dismissal of the important scientific questions that Ioannidis’ STAT piece raised by proponents of the previously untested (and therefore non-evidence-based) lockdown strategy, the use of the straw man argument and other logical fallacies by his critics, and the smear campaign that was unleashed upon him, was clear evidence that science had left the building, and politics had taken over.

After the shameful mobbing of Ioannidis, a roll-call of eminent scientists and doctors were subjected to similar treatment, with many losing their jobs, being banned from social media, and subjected to vicious attacks by the corporate media. (For a tiny snippet, see here, here and here.)

No serious debate on any aspect of the pandemic response was tolerated, and individuals who dared to raise important questions were pilloried, silenced, and deplatformed. And now, the Australian government wishes to shut down debate on all topics in which it has a stake, by passing legislation that will effectively ban social media and other ‘digital platform services’ from carrying content that it deems ‘misinformation’ or ‘disinformation’.

The constant chanting by our elected leaders and unelected health officers of the mantra “We’re following the science” is a hollow farce when they have abandoned the central pillar of not just the scientific method, but the entire basis of liberal democracy.

If this doesn’t activate your bullsh*t meter, I don’t know what will.

#3. Arguments from authority carry little weight — ‘authorities’ have made mistakes in the past. They will do so again in the future. Perhaps a better way to say it is that in science there are no authorities; at most, there are experts.

The appeal to authority is one of the most oft-used logical fallacies. When anyone urges you to mindlessly obey the ‘authorities’ who demand that you wear a mask, maintain a specific distance from others, or take a medical treatment, because they know what’s best for you, or because ‘it’s the law’, you should immediately suspect their motives and demand that they furnish verifiable facts that support their argument.

In July 2020, Forbes magazine published an article titled ‘You Must Not “Do Your Own Research” When It Comes To Science‘, alleging that non-scientists “lack the relevant scientific expertise needed to adequately evaluate that research on our own”.

The article then goes on to commit every mistake that it accuses the non-scientist of falling prey to when evaluating evidence, by overlooking, omitting and misinterpreting crucial data on the topics that it purports to analyse (including fluoride, vaccine safety, climate science and face masks for preventing transmission of SARS-CoV-2).

This entire execrable piece of anti-journalism is a paean of praise for the logical fallacy of appeal to authority, which would make Sagan roll in his grave (had he believed in life after death, which he did not).

After Forbes’ risible kick-off, everyone from The New York Times to The Conversation to a self-styledscience educator and communicator‘ to an Australian government-funded website called ‘The Healthy Male‘ to The Conversation (again) to no-name academics pompously prattling on about “epistemically suspect beliefs“, carried the ball down the field in their own unique way. The collective message was that you, stupid rube that you are, not only lack the intellectual firepower necessary to weigh the evidence for yourself, you’re too stupid to even be able to distinguish the right experts to listen to, from the wrong ones.

Jimmy Dore destroys the ‘don’t do your own research – trust the experts!’ narrative in two minutes of comedic genius:

The tagline of The X-Files says it best: “Trust no one.” Especially not someone who claims to be an expert but presents you with no evidence for their claims. This is one sure mark of the bullsh*t artist.

#4. Spin more than one hypothesis. If there’s something to be explained, think of all the different ways in which it could be explained. Then think of tests by which you might systematically disprove each of the alternatives. What survives, the hypothesis that resists disproof in this Darwinian selection among ‘multiple working hypotheses’, has a much better chance of being the right answer than if you had simply run with the first idea that caught your fancy.

Early on in the COVID-19 debacle, certain hypotheses were advanced as facts, and policies were formulated on the basis of those hypotheses.

For example, the hypotheses that the appearance of an unusual type of pneumonia in Wuhan, China in December 2019 was entirely attributable to a novel coronavirus, SARS-CoV-2, and that SARS-CoV-2 was a highly infectious and deadly virus to which humans had no pre-existing immunity, and which had the potential to kill up to 2.2 million Americans and 500 000 Britons, propelled the governments of both countries to enact control measures that were unprecedented in each country’s history.

Other countries, including Australia, rapidly followed suit.

Alternative hypotheses existed from the outset, but were summarily dismissed.

For example, Wuhan is known to suffer such high levels of air pollution that residents staged a two-week street protest in June and July of 2019, holding banners with slogans such as “We don’t want to be poisoned, we just need a breath of fresh air.”

Lombardy, the second region hit hard by COVID-19, ranks among the most air polluted areas of Europe, and hospitalisations for pollution-related respiratory conditions have been found to increase with age.

New York City, the third region severely affected by COVID-19, is one of the most polluted cities in the US, experiencing air quality that is ranked moderate or unhealthy for sensitive groups on 206 days per year.

Air quality in Iran, another early casualty of the pandemic, is considered unsafe according to World Health Organization guidelines, with fine particulate matter concentrations averaging close to 4 times the recommended maximum.

Additionally, the impact of advanced age and pre-existing health conditions (comorbidities), especially obesity, diabetes and cardiovascular disease, on the risk of developing serious or critical illness from SARS-CoV-2 infection was evident from the very first case series (involving over 70 000 patients) on the course of COVID-19 in mainland China, published in February 2020.

By early March 2020, therefore, there was ample evidence to support at least two alternative (and not mutually contradictory) hypotheses:

Firstly, the pathogenicity (ability to cause disease) of SARS-CoV-2 may be facilitated or exacerbated by air pollution – a hypothesis supported by research on other respiratory viruses – and therefore, less polluted regions could expect lower rates of serious illness and death, and hence would have little justification to enforce stringent control methods.

Secondly, SARS-CoV-2 infection may present very little danger to young and metabolically healthy people, and hence, special measures should have been put in place to protect the elderly (especially the frail elderly living in institutions) and metabolically unhealthy, while the remainder of the population continued life as normal.

As time went by, evidence accumulated for both of these hypotheses. The degree of air pollution is clearly linked to the risk of dying from COVID-19, with 15% of deaths worldwide linked to chronic exposure to air pollution.

And according to the US Centers for Disease Control and Prevention (CDC) at the height of the supposed pandemic, the risk of being hospitalised for, or dying because of, COVID-19 rises steeply with age:

Just four cardiometabolic conditions – obesity (BMI ≥30 kg/m2), diabetes mellitus, hypertension, and heart failure – accounted for almost two-thirds of hospitalisations for COVID-19 in the US. Reducing the prevalence of all four conditions by just 10 per cent would, the authors of this study calculated, have prevented 11 per cent of COVID‐19 hospitalisations.

To put that in layman’s terms, if you’re young, slim and metabolically healthy, the chances of you getting sick enough from COVID-19 to be hospitalised are pretty slight.

And they’re still quite low if you’re elderly but metabolically healthy and not frail. Hell, for that matter plenty of elderly, metabolically unwell individuals have had either mild illness or no symptoms at all, according to this article. And stories abound of centenarians who survived SARS-CoV-2 infection – like the world’s second oldest person, a 117-year-old blind, wheelchair-bound French nun by the name of Sister André, who tested positive for the virus in mid-January 2021 but was unfazed by the experience, commenting “I didn’t even realise I had it”.

Yet the ‘working hypothesis’ that SARS-CoV-2 is an existential threat to humanity, and could end up being as deadly as the 1918 Spanish Flu (which killed somewhere between 1 and 5.4 per cent of the world’s population, disproportionately affecting young, previously healthy people while sparing the elderly, quite possibly because these unfortunate individuals were poisoned with wildly excessive doses of aspirin) and therefore necessitates extraordinary and unprecedented – not to mention non-evidence-based – control measures, ‘caught the fancy’ of politicians, public health bureaucrats and the corporate media back in early 2020, and has not been dislodged by over three years’ worth of accumulated evidence to the contrary.

This working hypothesis is, quite simply, bullsh*t.

#5. Try not to get overly attached to a hypothesis just because it’s yours. It’s only a way-station in the pursuit of knowledge. Ask yourself why you like the idea. Compare it fairly with the alternatives. See if you can find reasons for rejecting it. If you don’t, others will.

Many people – both those in power, and ordinary citizens whose human rights have been egregiously infringed upon by those in power – attached themselves to the hypothesis that SARS-CoV-2 was an existential threat to humanity, with extraordinary passion.

Anyone who questioned any aspect of “The Science™” on SARS-CoV-2, COVID-19, or the measures that have been enacted in an attempt to ‘control’ it, was immediately labelled a granny-killer, or, with no apparent sense of irony, a ‘science-denier’.

Even at this point in time, when multiple authors have clearly demonstrated that there was no deadly viral pandemic, there is a solid core of people whom I interact with, both in person and online, who still cling to the deadly-virus-requiring-unprecedented-government-intervention-in-our-lives narrative.

This over-attachment to a dominant narrative should be treated with great suspicion that there is bullsh*tting at work.

#6. Quantify. If whatever it is you’re explaining has some measure, some numerical quantity attached to it, you’ll be much better able to discriminate among competing hypotheses. What is vague and qualitative is open to many explanations. Of course there are truths to be sought in the many qualitative issues we are obliged to confront, but finding them is more challenging.

There’s a crucial caveat to the sixth tool in Sagan’s baloney detection toolkit, and that’s context. Quantification of the impact of SARS-CoV-2 – the number of infections, percentage capacity of hospitals and ICUs, number of deaths – was (and still is) almost always presented without context.

In order to make sense of numerical quantities, we need to know what we’re comparing them to. For example:

  • How many people identified as ‘cases’ of SARS-CoV-2 infection were/are actually sick, and how many merely tested positive on RT-PCR test but display either mild symptoms, or none at all?
  • How many people identified as hospitalised ‘cases’ of COVID-19 were/are actually admitted for treatment of SAR-CoV-2 infection, and how many were admitted for treatment of other conditions but tested positive to SARS-CoV-2 before or during their admission?
  • How many cycles of the RT-PCR test were run before a positive test result was returned?
  • How many people are usually hospitalised for respiratory infection at this time of year?
  • What percentage capacity do hospitals, including ICUs, normally run at, and how does current hospital capacity at this time compare to previous years?
  • How many deaths normally occur in this region, at this time of year?
  • How many people die every day, week, month and year, in this country, or in the entire world?
  • Has the total number of deaths in this region, country or the world increased?
  • Have the numbers of deaths attributed to other common causes of death (for example, cancer or heart disease) dropped, and if so, how does the number of ‘missing’ deaths from these causes relate to the number of deaths attributed to COVID-19?

Numerical quantities make little sense if we have nothing to compare them to. Be wary of people who throw numbers at you without setting them in context. Chances are, you’re being bullsh*tted.

#7. If there’s a chain of argument, every link in the chain must work (including the premise) – not just most of them.

There are many examples of failure of the chain of argument in the COVID-19 debacle, but one of the most egregious is the claim – still believed by a surprising number of people – that the virus spontaneously arose from recombination of disparate coronavirus strains originating in different animal species – namely bats and pangolins – in the Huanan Seafood Market (wet market) in Wuhan.

The facts are that

  1. The first identified case of SARS-CoV-2 had no history of exposure to the market, or anyone working there;
  2. 13 of the first 41 patients hospitalised with confirmed SARS-CoV-2 infections had no epidemiological link with the markets;
  3. Neither bats nor pangolins were sold at the market; and
  4. The virus was not identified in any animals sold in the market.

In other words, every link in the chain of argument is broken. This would be sufficient for any intellectually honest person to dismiss the wet market origins claim. Unfortunately, the essence of bullsh*tting is that it’s intellectually dishonest.

#8. Occam’s Razor. This convenient rule-of-thumb urges us when faced with two hypotheses that explain the data equally well to choose the simpler.

Let’s take as a case study the rapid decline in cases of SARS-CoV-2 infection, hospitalisation and death from COVID-19 that was observed across the northern hemisphere in early 2021. Which is the simpler explanation for this phenomenon:

Was it that wearing face masks finally started working, despite the copious evidence that neither face mask mandates, nor rates of mask adherence, made the slightest difference to any country’s infection, hospitalisation or death rates at any previous point during SARS-CoV-2’s march across the planet?

Or was it that lockdowns finally started working, despite the fact that there is no relationship between the stringency of government policies and the COVID-19 death rate in any jurisdiction?

Or was it that, like every other respiratory virus before it, SARS-CoV-2 is highly seasonal, causing a predictable surge of respiratory illness during the cold, dry winter months and virtually disappearing when warmer and more humid weather – which interrupts aerosol transmission of viruses – arrives?

Six major respiratory viruses reported from PHE and NHS ...

The seasonal argument for declining rates of (purportedly) SARS-CoV-2-related illness clearly fulfils the test of Occam’s Razor. Defending the hypothesis that government policies were responsible for the drop, on the other hand, involves tying oneself into an intellectual pretzel. The alternatives to the seasonal argument are, frankly, bullsh*t.

#9. Always ask whether the hypothesis can be, at least in principle, falsified. Propositions that are untestable, unfalsifiable are not worth much. Consider the grand idea that our Universe and everything in it is just an elementary particle – an electron, say – in a much bigger Cosmos. But if we can never acquire information from outside our Universe, is not the idea incapable of disproof? You must be able to check assertions out. Inveterate sceptics must be given the chance to follow your reasoning, to duplicate your experiments and see if they get the same result.

The hypothesis that only vaccination of virtually everyone on the planet would bring an end to the SARS-CoV-2 pandemic was always inherently unfalsifiable. If this goal were achieved, and the virus and/or the disease associated with it did indeed subside to the point that even the most hysterical virus-panickers were no longer particularly concerned about them, there would be no control groups upon which to test alternative hypotheses.

Chief among these alternative hypotheses is that if the young and healthy had simply been allowed to experience and recover from natural infection whilst the elderly and vulnerable were protected from exposure, the virus would have burned itself out after herd immunity had been reached. This is, indeed, what appears to have occurred in areas of the world with low COVID injection uptake, such as barely-vaccinated Africa:

Source: Our World in Data

Anyone purveying unfalsifiable claims should fall under immediate suspicion of being a bullsh*t artist.

Conclusion

A 2021 research paper enticingly titled ‘You can’t bullshit a bullshitter’ (or can you?): Bullshitting frequency predicts receptivity to various types of misleading information‘ found that people who frequently engage in “persuasive bullsh*tting” – the use of misleading exaggerations and embellishments to impress, persuade, or fit in with others – are more susceptible to believing bullsh*t.

(Side note: Isn’t it delicious that ‘bullsh*t studies’ constitutes an entire branch of social psychology research? I reckon those who enter this field do so mostly so that they can write the word “bullsh*t” in an academic paper, over and over again, and get away with it. Or maybe that’s just me.)

Perhaps this explains why the vast majority of politicians – not to mention the corporate media presstitutes and many of your attention-seeking social media friends – have swallowed COVID-19-related bullsh*t with such alacrity.

According to the lead author of the study, Shane Littrell,

“We found that the more frequently someone engages in persuasive bullshitting, the more likely they are to be duped by various types of misleading information regardless of their cognitive ability, engagement in reflective thinking, or metacognitive skills.”

People Who Frequently Mislead Others Are Less Able to Distinguish Fact From Fiction

Practising the arts of intellectual self-defence is necessary for anyone who wishes to defend themselves against the bullsh*t that pervades our culture, as Harry Frankfurt so acerbically observed.

Carl Sagan’s baloney detection kit deserves pride of place in one’s armoury of intellectual self-defence, but like any skills, these ones require frequent practice to acquire mastery. Don’t worry – you’ll get plenty of opportunities for practice. Just turn on the nightly news.

And if you want to learn how to distinguish truth from bullsh*t in the health and nutrition arena, sign up for my full-day Be Your Own Doctor seminar. In-person and virtual attendance options are available.

Is your bullsh*t detector telling you that something is not quite right, but you’re not sure how to identify reliable sources, conduct research, and express your findings to others? I teach these skills of intellectual self-defence – among many other things! – in my EmpowerEd health and nutrition education program. Want to learn more? Activate your free 1-month trial of EmpowerEd here.

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