SKEPTOSOPHY
A brief introduction to the philosophies which underpin science and skepticism
written for laymen, by a layman
Contents
Introduction ....................................................................................................................................................................2
Science: The Often Received Wisdom ....................................................................................................................2
Science: The Reality ...............................................................................................................................................2
Scientific Skepticism ..............................................................................................................................................4
Pseudoscience and Woo ..............................................................................................................................................4
Occam's Razor ........................................................................................................................................................5
Evidence Trumps Mechanism .................................................................................................................................5
Pseudoscience .........................................................................................................................................................5
The Scientific Method ....................................................................................................................................................5
Experiments ...............................................................................................................................................................5
Fair Tests ................................................................................................................................................................5
Anecdotal Evidence and Confirmation Bias ............................................................................................................5
The Null Hypothesis ...............................................................................................................................................6
The Burden of Proof ...............................................................................................................................................6
Multiple Variables ...................................................................................................................................................6
Placebos .................................................................................................................................................................6
Regression to the Mean ...........................................................................................................................................7
More on Placebos ...................................................................................................................................................7
Control Groups (and Placebo Groups).....................................................................................................................8
Pseudomedicine, and a Final Word on Placebos… ..................................................................................................8
Bias and Blinding ...................................................................................................................................................9
Peer Reviewing ........................................................................................................................................................ 10
Publication............................................................................................................................................................ 10
Publication Bias .................................................................................................................................................... 11
Falsification .......................................................................................................................................................... 11
From Hypothesis to Theory...................................................................................................................................12
Repeated Testing ................................................................................................................................................... 12
P Values ................................................................................................................................................................ 12
Meta-analysis and Systematic Reviews ................................................................................................................. 12
Skeptics ........................................................................................................................................................................ 13
How to Find Out More ................................................................................................................................................. 16
Author's Note ............................................................................................................................................................... 17
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Skeptsophy by Antony Wootten
Introduction
This essay is intended to introduce you to the fascinating world of scientific-skepticism (usually
spelt with a 'k' in this context). Since science and skepticism are so closely linked, the vast majority
of this essay will be exploring the ideas behind the scientific method, in which a scientific-skeptic
should be well-versed. So, if you are already a battle-hardened scientist or passionate scientificskeptic, don't waste your time reading any further, this essay is not for you. However, if you are
pretty new to the world of science and scientific-skepticism, it might be. This is written for laymen
by a layman. My aim is to share with newcomers everything I have learned over the last couple of years
of listening to podcasts and reading books on the subject, for fun, in my spare time, about how science
and scientific-skepticism (hereafter just called 'skepticism') work. It is also my intention to make it
clear exactly why science is an institution you can trust, despite what the vast body of anti-science
conspiracy theorists would have you believe. Don't get me wrong, there are problems with science;
there is room for the dishonest to manipulate findings and pull the wool over the eyes of the world;
not all the anti-science rhetoric you might hear is groundless. But science (if you'll allow me to pretend it is a single, sentient entity) is aware of that, and has inbuilt systems to deal with those problems. I intend to explain the rudiments of those systems, and I believe you will see that, in the end,
bad science is eventually routed out and exposed, simply because in order for scientific claims to
survive they have to actually work.
First though, we need to talk about some of the myths surrounding science itself.
Science: The Often Received Wisdom
Science is often billed by its dissenters as a shadowy, elitist organisation, like a religion or a cult,
with closed doors behind which lurk dark secrets: scientists manipulating data with the sole intention of fooling the world into believing their lies. From this anti-science point of view it is easy to
believe that the scientists in their shadowy labs and lairs are intent on discrediting the noble
achievements of the heroic, lone mavericks operating outside of – and ostracised by – the scientific
community; mavericks who promote new miracle cures which would, if released into the public
domain, bring down the big pharmaceutical companies whose money and power hold the scientific
community in their thrall. This perspective is especially prevalent in the fields of alternative medicine, health and nutrition.
Of course, this paranoid view doesn’t stand up to a moment’s scrutiny. Just think of the millions of
scientists around the world who would have to be willing accomplices in this conspiracy. What is
true however is that science is not perfect. It is open to corruption. But, despite certain significant
and pervasive flaws (which I will come to) science is our best method for finding things out. And
here's why...
Science: The Reality
Science is purely and simply a good way of finding things out. And we all want to find things out.
Whenever we are unsure whether or not something is true, in any context or walk of life, we do
what we can to find out the truth. Science is the process which enables us to do that.
I can't emphasise that point enough. Science is a truth-seeking process, not a belief system. And,
crucially, it is totally overt. You – yes you! You personally – can scrutinise its methods, can see
right into its internal workings, can read all its so called 'secrets', can spot its errors, can tell it it's
wrong, and it will thank you for doing so, and if you are right and it is wrong then it will change its
mind. All that science wants is to know the truth; the real, unbiased, often inconvenient truth; even
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when the truth hurts; even when the truth flies in the face of its previous findings and means tearing
up long-held theories and consensuses; even when the truth costs money, science wants to find it.
The trouble is, if you really want to find the truth you have to find ways of making sure that what
you are finding is the actual truth, and not just the truth that you were hoping to find, or that you
already believed. We humans are very biased beings, and creative too. We are more than capable of
seeing evidence for our beliefs where really there isn't any. Science is the process of seeking the
truth, through experimentation, in such a way that our biases and beliefs are removed from the
process, so that we are forced to form our opinions based on an open-minded assessment of the data
generated, and not on our passions. That can hurt. If the data generated – the evidence – goes
against your preconceived ideas, what do you do? Reject it? Repeat your experiment, tweaking it
until it gives you the results you wanted? No. You change your mind. Of course you do! You'd have
to, wouldn't you? What's the alternative? To cling to an idea for which there is no evidence, or
which is disproven by the evidence? That would be closed-minded prejudice, wouldn't it? It is this
mind-changing which makes science so powerful. By changing its mind in the face of real, hard
evidence, science gets better. It learns, develops and grows. This is why I am careful not to use the
term 'scientific knowledge', but instead use the term 'the scientific consensus'. If you are always
prepared to change your beliefs when faced with strong evidence, then you can't really call your beliefs 'knowledge'. Or 'beliefs', for that matter. What science 'knows' or 'believes' can be best described as 'the theory which is compatible with our current best evidence', or the 'scientific consensus'. If new and contradictory evidence comes to light, gradually more and more scientists become
convinced, and so the consensus changes. Not straight away because scientists need time to assess
the evidence themselves and make sure it is solid and reliable, but if it is, then they will, one by one,
lab by lab, team by team, find it to be so, and change their minds accordingly.
Some people who reject the scientific consensus often reject the scientific process too. They will
say science is not the only way to find things out. They might even be able to tell you about the
processes they follow in order to find things out. But there are no two ways about it, a better way of
finding things out than science... is just better science. You can think of science as a continuum,
with good ways of finding things out at one end, and bad ways of finding things out at the other.
Guess-work would be at one of the extreme ends of the continuum. Good science is at the other,
with all its tight restrictions and controls. Other processes are just other positions along the continuum. It is impossible for a 'finding things out' process to be outside science because science is the
process of finding things out.
I should point out that a process is not automatically going to be good science simply because it is
billed as 'science'. No-one has the monopoly on science; anyone can do it. But the 'can' in that sentence means 'is free to' rather than 'is competent enough to'. I can do an experiment and call it science. So can you. So can any organisation, from GlaxoSmithKline to Monsanto (who make GM
crops) to Nelsons (who make homeopathic pills) and anyone and everyone in between. But just because we are all free to do it, doesn't necessarily mean we are all competent enough to do it well.
But when science is done well, it generates accurate, reliable results which drive progress. Progress
can only be driven by the truth, and that is what good science reveals. But not all so-called science
is as tightly controlled as it should be, and so can fall somewhere along the aforementioned continuum. Some so-called science – even in the mainstream – is distinctly bad. An important example of
this comes from within the world of science and medicine itself: it is well known that trials of new
medicines run by the big pharmaceutical companies (big pharma) will very often produce positive
results when a company is trialling one of its own products, and less positive results when trialling
someone else's. Big pharma companies routinely bury – simply by failing to publish – research
which shows poor results for their own product. This is disgraceful, unscientific behaviour, and it is
endemic and well documented. This sort of underhand distortion of the truth is exactly what makes
many people deeply suspicious of science in general. I'm not glossing over this inconvenient truth,
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but it is a massive topic, so if you want to know more, read Ben Goldacre's book Bad Science. For
now, suffice to say that while bad science does take place within the scientific community, good
science and solid skepticism are on hand to rout it out.
To be good science, it has to be unbiased and accurate, tightly controlled and dispassionately conducted. A scientist might think their experiment is all those things, but if it isn't, then their evidence
is no good. But as I have already mentioned, science is totally overt. A good scientist will publish
not only their results, but also their methodology for others to scrutinise and repeat. If a scientist
does not publish their methodology, you may be right to assume they have something to hide. Certainly, if you cannot scrutinise their methodology there is no way of knowing whether their results
are reliable, and so their findings cannot be accepted into the scientific consensus.
So, you can already see that the experiment itself is only the beginning of the process. All results –
whether produced by a big pharmaceutical company, an independent lab or a lone maverick – have
to stand up to intense scrutiny and repetition. This is something that alternative practitioners often
find hard to accept.
So that's science. But where does skepticism come in?
Scientific Skepticism
If you are skeptical, you will require solid, reliable evidence before you believe something extraordinary. Not only that, but you will also require that the methodology for generating that evidence
was accurate and unbiased – in other words, good science. Because science is so overt, skeptics can
scrutinise it thoroughly, just as can any scientist (or any living human for that matter!). And that's
what skeptics do. Skeptics don't just credulously believe exciting or extraordinary new discoveries;
they scrutinise them. But if both the method and the evidence stand up to scrutiny, the skeptic will
believe the extraordinary thing. Science changes its mind in the face of solid evidence, and so does
a skeptic. A credulous person will believe what they want to believe regardless of veracity of evidence.
Skepticism can be applied to such diverse topics as medicine, history, politics, economics, religion,
sociology, the supernatural, nutrition, popular conspiracy theories, UFOlogy, road safety, cooking,
coppicing, and everything in between. But throughout the rest of this essay, where examples are
needed, I will mainly be focussing on medicine because that's where the dangers lie. There are dangers in other areas too, but they are not usually immediately life-threatening. For instance, if a historian makes a claim about something she believes happened in the past, and lots of people believe
that claim but it turns out not to stand up to scrutiny, it's unlikely that anyone will die. (That, of
course, is not to belittle or ignore the damaging and painful effects of such examples as holocaustdenial.) But if a doctor tells you that a medicine not accepted by the scientific community will cure
your life-threatening illness, and you believe him and consequently reject mainstream medicine, if
the doctor's advice is wrong then you actually might die as a direct consequence of that misinformation. So that's the area on which I will be focusing my attentions. But rest assured, both science and
skepticism are vital components of all areas of research.
Pseudoscience and Woo
I'm pretty sure you already know enough about science to have no trouble listing a number of things
which fall outside of the scientific consensus. On your list there are likely to be such things as psychic powers, astrology, ghosts, god, cryptozoology, alien visitors, alternative medicines, and many
other things; in short, what skeptics refer to as 'woo'. I prefer the term 'pseudoscience', although
pseudoscience and woo are not quite the same; woo is the items on your list whereas pseudoscience
is the unscientific method that has been used to supposedly 'prove' the woo. (The word 'woo' is also
sometimes used to describe the believer – 'he's a bit woo' you might say, or 'she's a woo'.)
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Occam's Razor
Scientists and skeptics generally go by the principle of 'Occam's Razor', which says that if there are
two competing hypotheses, both of which fit the evidence equally well, the one which requires the
fewest new assumptions is more likely to be accurate. Thus, pseudoscientific ideas are often rejected by scientists and skeptics because they require you to make lots of new assumptions which
are not compatible with existing data and evidence.
Evidence Trumps Mechanism
Very often, proponents of, for instance, a medicine which the scientific consensus rejects, claim that
science rejects it because science cannot explain the mechanism by which it works. This is not the
case. Science my very well not be able to explain that mechanism, but if the data is there to show
that it does indeed work, the scientific consensus will accept that it does, and will set about trying to
understand the mechanism. Evidence trumps mechanism. Medicines and treatments which are rejected by the scientific consensus are rejected not because their healing mechanisms are beyond the
understanding of science, they are rejected because the data from experiments show that they do not
heal.
Pseudoscience
Where science equals unbiased and accurate experimental processes, pseudoscience equals poor,
unreliable experimental processes. Pseudoscience is called pseudoscience because, despite being
billed by its proponents as real science, it does not follow unbiased and accurate experimental procedures and so the evidence cannot be trusted. When there is no reliable evidence for something, the
only thing leading you to believe in it is your faith that it is real. Whereas science is not a belief system but a truth-seeking process, pseudoscience is the lack of adherence to any such process, and is
therefore better described as a belief system.
So, that's the ground-work done. Let's now have a look at what makes for good, scientific experimental methods and processes.
The Scientific Method
So far, I've made a lot of claims about how good science is as a method for finding the truth. In this
section, I'm going to explain the method in some detail. If you are one of those who believe the
myths about science which I denounced in the first few paragraphs of this essay, this section is very
much for you. Here, you will discover the nuts-and-bolts of science, why the scientific community
can be relied upon to provide solid evidence, and why the scientific consensus can be trusted.
Experiments
Fair Tests
An experiment always needs to be a fair test, meaning the results are unpolluted by misleading factors. These misleading factors can be incredibly subtle, sneaking into the process like gremlins intent on making your evidence unreliable. I'm going to go through a few of these factors, starting
with some core principles of science.
Anecdotal Evidence and Confirmation Bias
We have all heard extremely compelling anecdotes to support an idea which we instinctively know
would fall into the 'not proven by science despite much experimentation' category, or in other
words, pseudoscience. My friend knows ghosts exist and can give me several fascinating anecdotes
about her own experiences to 'prove' it. Anecdotal evidence like that may seem compelling, but is
deeply, deeply unreliable because our memories, perceptions and interpretations of what we think
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we see are fallible. Our perceptions are also subject to our own biases. If we want to believe in
something, we will have all sorts of anecdotal evidence to support that belief because we selectively
'cherry-pick' the anecdotes that support our belief and ignore – or forget – the ones that don't. The
term 'cherry-picking', by the way, is actual scientific jargon, not just a colloquial term. And 'confirmation bias' is the phrase which sums up this process. Confirmation bias is what happens when we
choose to remember the evidence which seems to confirm our belief, and forget or fail to notice the
evidence that doesn't. Science is the process of eliminating human fallibility, confirmation bias and
cherry-picking. Ten, a hundred or a thousand anecdotes do not equal a single piece of evidence.
The Null Hypothesis
Science begins at what is called the 'null hypothesis', i.e. the assumption that there is no evidence to
support a newly proposed hypothesis. Anecdotal evidence is not reliable enough to move scientific
understanding beyond the null hypothesis. This can frustrate pseudoscientists who feel they are being marginalised by the scientific community who won't accept their many strong anecdotes as hard
evidence.
The Burden of Proof
If you have a new hypothesis, whether you are a pseudoscientist or a Nobel Prize-winning nuclear
physicist, the 'burden of proof' is on you, not on the scientific community, meaning it is your job to
provide good, hard, reliable evidence. If you can do that, the scientific community will take notice,
but there just isn't the time, money or inclination to investigate every new or contradictory idea.
Pseudoscientists often challenge scientists and skeptics to disprove something, as if that gives them
the upper hand, but they've got this the wrong way round. They are the ones who need to come up
with the evidence, and anecdotal evidence will not do.
Anecdotal evidence has its place though. If there are enough convincing anecdotes to make scientists think a phenomenon might be worth looking into, look into it they will, but using the scientific
method to eliminate human fallibility and generate reliable evidence.
Multiple Variables
A variable is anything you can change when doing an experiment. An experiment might be influenced by any number of variables. The trick is to make sure you have thought of them all, and constructed your experiment in such a way that the results will be affected only by the variable you are
testing, and not by any of the others. To use a real world example, imagine you are testing the hypothesis that omega 3 fish oils boost children's achievement in GCSE exams (as has been claimed).
You could fairly easily create an experiment in which a number of students are given regular doses
of omega 3 tablets during the build up to taking their exams. You would then look at their exam results and compare them with, say, what they were expected to get, or what has been achieved by
other students in previous years, or preferably, a group of similar students who were not given
omega 3 tablets. But in order to make it a fair test you need to eliminate all the other variables, or
things that vary from student to student, which could affect their performance, such as other special
help they might have been getting from the school or from their parents, other food ingredients they
might have consumed that could have boosted their ability (omega 3 fish oil is not the only supplement some people claim boosts your brain power), and even just the effect on students of knowing
they are involved in a trial, which in itself can, through one mechanism or another, lead to students
showing improvements even if omega 3 fish oils themselves are ineffective. If the students do get
better than expected exam results after taking regular doses of omega 3 but you have not eliminated
(or 'controlled for') all those other variables, it is impossible to know whether their improvement is
attributable to the omega 3 or to something else. That is where control groups come in, but you'll
have to wait for that bit because we need to talk about placebos first.
Placebos
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The placebo effect can totally invalidate the results of an experiment. Here's how. If someone is suffering an illness which causes them pain, and you give them a tablet which you explain will alleviate the pain somewhat, they will often experience less pain after taking the tablet even if the tablet
contained no medicine what so ever. A tablet that contains no medicine what so ever is called a placebo. Placebos do work on certain symptoms, pain being a particularly good example because pain
is hard (or impossible) to quantify, so you need the patient to judge for themselves how bad their
pain is, and a placebo pill really can make them feel as if their pain has improved. It's much like
when a child hurts its knee and its mum or dad rubs or kisses it better. The parental rub and/or kiss
has no genuine healing properties, but the child does feel better afterwards. So scientists need to be
aware of the placebo effect, and control for it in their experiments. If you are a scientist testing a
new cure for knee pain, and you give this new medication to a number of knee pain sufferers, and
some of them say it made their knees feel much better, you need to be aware that this does not necessarily mean your new medication has worked. It could just be that their belief in the medicine
working has made them believe their knees feel better.
Regression to the Mean
By way of a brief aside: another reason for the improvement might be what is called 'regression to
the mean'. Usually, pain which is not caused by something too serious does actually go away by itself. If you take no medicine for your headache, for instance, your headache will probably go away
all by itself. If you take your pain medicine at the point when you can bear the pain no longer, the
pain might begin to fade because of the medicine, but it might have been going to do that anyway.
Your pain regresses to the mean. Regression to the mean can be applied to all sorts of different circumstances. At an accident black-spot, there might be a spike in the frequency of accidents one
year, and steps might be taken to improve safety there. When there are fewer accidents the following year, that might mean the safety features are working, but it might just be the result of regression to the mean; maybe the following year there will be fewer than average accidents, but that
doesn't mean things will be that good forever because regression to the mean means the frequency
is likely to pick up again in the future.
More on Placebos
Back to knee pain and the placebo effect. It might not be the pill itself which acts as a placebo. It
could just be that your kind doctorly words when administering the medicine inspired faith in your
abilities which in turn made patients feel better, but they attributed the perceived improvement to
the medicine. But crucially, the improvements in their knee pain, as reported by the patients, might
be solely attributable to the placebo effect, and your medicine might actually be utterly ineffective
and completely useless as a treatment for knee pain.
One fascinating feature of the placebo effect is that it works even when the subject knows they have
been given a placebo instead of a real medicine. It seems that if you give a patient anything at all,
and tell them it won't cure their ailment, the process of discussing it with a doctor and taking a tablet
they know is useless can still be enough to trigger the placebo effect.
Having said that though, I must though make it completely clear that placebos are not – as far as we
know – magic. Placebos cannot cure measurable, chronic, physical ailments. They cannot make
cancer go away. They cannot cure Parkinson's. They cannot protect you from malaria or AIDS.
These are not random examples. There are many examples of alternative medicines which work
only as well as placebo, but which are sometimes touted as cures for, or protection from, the above
conditions.
That is a brief introduction to what placebos can and can't do. So, now back to control groups (but
you haven't yet heard the last of the placebo effect just yet!).
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Control Groups (and Placebo Groups)
In order to test your new medication for knee pain – which, for the sake of needing to call it something, I'll call smarticus orangium – you obviously need to give it to some people who have knee
pain. But that alone is not going to give you all the information you need. You also need a 'control
group', which means a group of people who are not given the medication, so you can compare results. If both groups report the same improvements in their knee pain, you know that was probably
not down to the smarticus orangium actually working, because your control group weren't given any
and their knees got better without it. It was either regression to the mean or the placebo effect, or
both. But let's assume the control group reports no improvement and the group given smarticus
orangium (the treatment group) reports improvement in their knee pain, that could still just be the
placebo effect at work, so to control for that you also have a third group. This is your placebo
group, and they are given a placebo, and told it is smarticus orangium, but really it is just an orange
smartie. (Of course, Placebos can be anything, they don't have to be orange smarties!) What you
would hope to see is that the treatment group reports the biggest improvement. The placebo group
will probably also report some improvement, but hopefully not as much as the treatment group, and
the control group will probably report less improvement. If that happens, it is looking good for
smarticus orangium – it is probably an effective treatment for knee pain. If however the treatment
group and the placebo group report the same degree of improvement, and the control group reports
less improvement, that means smarticus orangium has performed no better than an orange smartie.
We can be quite sure that orange smarties don't cure knee pain – that is the placebo effect at work.
Therefore, we have to admit that smarticus orangium also does not cure knee pain because its results are no better. A wrong conclusion to come to would be that because orange smarties work just
as well as smarticus orangium, orange smarties therefore cure knee pain.
So, in order for a new medication to be considered to work, it has to prove itself to be more effective not just than no treatment, but than placebo.
Pseudomedicine, and a Final Word on Placebos…
Here are a couple of other interesting points about the placebo effect. You may often hear proponents of certain alternative medicines proclaim that the placebo effect doesn't work on babies. A
baby doesn't know anything about medicine, so they can't possibly begin to feel better as a result of
the placebo effect. But they do. The placebo effect works on babies for a couple of reasons. First,
babies respond to a bit of TLC (as in the 'let daddy rub it better' example given earlier) so the very
process of carefully examining a baby before administering a medication, cuddling it and soothing
it as you do so, makes the baby feel better. Secondly, the baby can’t tell you about its symptoms itself, so, if it is something that can't be seen, such as teething pain or tummy ache, it is down to the
parent to make a judgement about how much pain the baby seems to be in. The parent is well aware
that the baby is being treated, and will therefore sometimes see an improvement even if there is no
actual improvement. In short, that is a kind of placebo-by-proxy effect. Additionally, a baby being
treated with a placebo might just spontaneously happen to get better, an example of regression to
the mean. For these reasons, the placebo effect does work on babies and, incidentally, animals too,
despite what some people might believe. That is worth bearing in mind next time you are shown an
unlikely sounding alternative health product for your baby or your pet.
Finally, one more myth about placebos, or rather, a myth about medicines that work no better than
placebo. If, in conducting your smarticus orangium experiment, you discover that the treatment
works no better than the ordinary orange smartie placebo, you might say, "Ah, well, if it works as
well as a placebo that means it is effective to some degree because we know that placebos do work.
Therefore, smarticus orangium is an effective and valid treatment for knee pain". That is wrong. If it
only works as well as placebo, it does not work. Placebos, as I have already stated, are not magic.
They don't cure you. They just make you feel as if your symptoms have been alleviated. Practitioners of alternative medicine often make the above statement about their treatments, but if repeated
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testing in properly controlled scientific fair test experiments continually show the treatment to be no
more effective than placebo, then the treatment does not work. It is, therefore, not a medicine. It
should, therefore, not even be called an alternative medicine, or even a complimentary medicine,
because something calling itself a medicine needs to be a medicine, and if it doesn't work, it isn't.
The term 'pseudomedicine', meaning anything which is billed as a medicine but works no better
than a placebo, is much more accurate.
Bias and Blinding
It is astonishing how easy it is for the bias of the person conducting the experiment to creep into
proceedings and undermine the entire fair test, in much the same way as can the placebo effect. This
can happen totally subconsciously, and often only becomes apparent when other scientists carefully
scrutinise the experiment, and expose the bias-related flaws. For instance, imagine you are testing a
psychic's claimed remote viewing powers. ('Remote viewing' is the ability to see faraway places
psychically, without visiting them or seeing pictures of them.) You show them four different points
on a map, and ask them to draw the scene they see in their mind at each point. You yourself are able
to look at photographs taken at the four locations and can therefore say whether or not the drawings
look like those places. The drawings the test subject comes up with require some interpretation, as
they look pretty abstract at first glance. However, on closer inspection you are astonished to see certain similarities between the photos and the drawings. From this you could conclude that the subject's remote viewing powers are real. Case closed, phenomenon proven.
Except… There is more than a little room here for you to have polluted the results with your own
bias, perhaps a subconscious desire for remote viewing to be real, or even for it to not be real. Let's
assume a pro-remote viewing bias. In your desire to find similarities, you excitedly matched largely
abstract drawings with the photos you felt they resembled. But what would have been the results if
someone else was doing the matching? Might they have matched them differently? Well, being a
conscientious scientist, you decide to employ a few helpers, and re-run the experiment. You might
get the helpers to do exactly what you did, i.e. match the drawings with the photos. But there is still
a problem. Each helper could have their own bias. A whole load of biased results does not equal
good evidence, any more than does a whole load of anecdotes. So, you need to find ways of making
it impossible for any biases to influence the results – you can't stop people being biased, but you can
take their biases out of the equation.
This time, one helper is asked to write a list of things they can see in each of the drawings, without
ever having seen the photos. These lists are then passed to a second helper who can see the photos
but not the drawings, their job being to match those lists with the photos. Could bias still be creeping in now? Well, yes, if these two new members of your team (the list-writer and the photomatcher) happen to know that the experiment is about remote viewing, their own biases could have
an impact. So, you tell them nothing about remote viewing (and for the sake of argument we will
assume they don't suspect that's what you are testing). But the list-writer could say something to influence the photo-matcher's decisions, so you don't allow them to meet; the list-writer leaves the
lists in an unmarked envelope on a table in an empty room for the photo-matcher to collect. You
may very well still be able to argue that the list-writer and the photo-matcher could in some subtle
way be biased, but you could control for that by having a hundred different list-writers and a hundred different photo-matchers, and you add all the results together. This way, the overall effect of
any one person's bias is massively reduced, lost among the sea of results, or countered by the opposite bias of others.
Applying those seemingly paranoid precautionary measures is called 'blinding'. It means that the
people doing the donkey work do not know what the experiment is about, and cannot see anything
that could influence what they do and therefore pollute the results. Wherever possible, experiments
should always be blinded. In the smarticus orangium experiment, blinding would mean that the per9
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son giving out the smarticus orangium pills and the orange smartie placebos would have to not
know which was which (although there would need to be a system to make sure someone did, otherwise you wouldn't know which patient had the treatment and which had the placebo). If they did
know which was which, they might influence the patient by inadvertently giving them their 'Ooooh,
that's only a placebo I'm afraid' face, or their 'Yep, that'll sort you out, madam' face.
But you can go further than that.
Back to the remote viewing experiment. You still have to compile all the results and do the numbercrunching. Did the drawings made by the psychic always match up with the correct picture via the
list-making and photo-matching process? That sounds like a simple case of just marking them right
or wrong, like marking exam papers. But there is still room for your own subconscious pro-remote
viewing bias to affect the results. Imagine one of the photo-matchers' 1s and 2s look similar, which
is sometimes the case. It might come down to your own judgement as to whether they had written a
1 or a 2 on one of the lists, which could make the difference between the list being matched to the
right or wrong photo. One or two of these judgements by you can be enough to swing the results
one way or another, and thereby invalidate the experiment. (You may think that the odd error here
or there wouldn't have much impact on the results, but in this sort of experiment the margins can be
tiny. A couple of percentage points might make all the difference – something I'll return to in the
sections on Repeated Testing and P values.) So, you decide to employ yet another person to do the
marking and analyse the results, someone who knows nothing about the purpose of the experiment
(ie is blinded to it). They don't need to know the purpose of the experiment to be able to come up
with a statement like 'The lists were matched with the correct photo 64% of the time'. If you do all
this, your experiment is double-blinded, because the people doing the donkey work and the person
doing the data analysis have no idea what the experiment is about and what their input means. (You
also hear of triple blinding, and, who knows? maybe even quadruple blinding, and so on.) You, the
scientist, designed the experiment, but got other people to do it all, each person not knowing their
part in the overall process. If you did that, then you may have successfully removed bias from the
experiment. I say 'may have', with some caution, because an experienced scientist might still find
my method flawed. That's what the process called 'peer reviewing' is all about.
Peer Reviewing
Next, you need to write up your experiment into what's called a 'paper', which is basically like when
your school science teacher used to get you to write-up the experiment you'd done that lesson, complete with your method, results and conclusion. You can then publish your paper.
Publication
There are various routes to publication. If your experiment is solidly scientific, meaning you have
followed all the procedures so far discussed, you can submit your paper to a peer reviewed science
journal. Your peers – scientists from your field – will thoroughly scrutinise your method, and if they
are happy that your findings are sound, the journal might publish your paper.
Alternatively, if your methodology was poor and your findings dubious, you might prefer not to
have your failings exposed by the peer review process, electing instead to publish your findings
yourself, perhaps on a website, in a tabloid newspaper, in a YouTube video, or even in a journal
which you have created yourself and is disguised as a peer reviewed science journal even though
the peers doing the reviewing are your own doting mates and your mum. This may well get your
paper out there into the public eye, and, despite logic and reason, will probably get you some dedicated followers. This is the tragedy of science: although good science does, ultimately, win through,
pseudoscience flourishes and blooms in the public eye, serving no purpose other than to lead the
unwary down blind alleys and get them intoxicated on enticing misinformation.
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Publication Bias
All this bad news and I’ve not even mentioned ‘publication bias’ yet. I’d better rectify that right
away. Publication bias refers to the selective publication of only the studies which suit your cause.
In medical science that means the drug trials which show your drug to be more effective than placebo and/or other rival drugs. Trials can vary in their results for all sorts of reasons. There’s no need
to invoke human bias or error; chance alone can lead to different results even when trials are repeated exactly. If you have the results of several trials, some showing positive results and some
negative, it is your moral duty to publish them all, so that others can see the entire picture and come
to accurate conclusions. But that, inevitably, does not happen. It is all too easy to ‘forget’ to publish
the negative trials. And so, through publication bias, the world learns how great your drug is, instead of the truth.
This travesty could be done away with simply by introducing a system of mandatory registration of
every trial. If such a system existed, it would be impossible to hide – or 'forget' to write-up – trials
with negative results, and the scientific community would be able to appraise all the data, not just
the data the big pharma drug companies (or whoever) want you to see. It would not then matter if a
trial is funded by a drug company with a vested interest in getting a positive result for their own
product; they would not be able to hide the negative results away from public view, and the veracity
of all results would still be subject to the scrutiny of the scientific and skeptical communities. But
without such a system, the scientific process is wide open to the evils of publication bias.
Falsification
So, let's say your trial has survived the peer review process and made it into a reputable science
journal. The process does not end there. The scientific consensus will not automatically change to
accommodate your results. Scientists are suspicious and sceptical creatures.
Even though you went through the peer review process in order to get your paper published, more
of your peers will now read your method and look for ways of proving you wrong. That sounds a bit
harsh; surely it would be more polite and supportive of them to congratulate you and tell you how
much they admire the way you conducted your experiment, wouldn't it? Polite and supportive, yes,
but that would also be counterproductive. Looking for ways of proving you wrong really is a vital
part of the process. Remember, science begins with the null hypothesis. You are sure your findings
are accurate, but the only way to be certain is to let everyone else scrutinise your experiment in
minute detail, looking for bias, unfairness, failures to control for variables you hadn't considered,
and so on. This is called 'falsification'; your peers will deliberately try to falsify your findings. And
the process continues even after that. Other scientists will actually recreate your experiment in their
own labs, tightening the controls if they think yours weren't tight enough. They will then publish
their results in papers for other scientists to scrutinise and falsify. This needs to happen repeatedly
before the scientific community can begin to accept that your findings are probably correct, and the
scientific consensus can move away from the null hypothesis. I say 'probably' because you can
never be 100% certain. You cannot prove that a theory is definitely correct, you can only say that
our best evidence so far supports it, but you have to leave the door open for future evidence that
might tell you something different. Take Newton's theory of gravity. For a couple of centuries it was
largely accepted as the correct way to predict the movement of the planets. But some astronomers
noticed slight differences between what the theory predicted and what was actually observed, as if
under certain extreme circumstances Newton's theory was slightly wrong. And in the early 1900s,
along came Einstein with his theory of general relativity, which was radically different from Newton's theory, but made predictions which accurately matched observations.
This is one of science's great strengths. I said at the beginning that science is not a belief system, it
is a truth-seeking process. The keystone of that process is total open-mindedness. Science is always
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willing to change its mind in the light of new evidence, but that evidence needs to stand up to thorough scrutiny.
From Hypothesis to Theory
It may surprise you to know that even if your experiment survives the peer review process, and everyone is in total agreement with your findings, your idea is still only a theory. The original idea you
had, for instance, that smarticus orangium might be good for knee pain, was your hypothesis. Your
belief that it is good for knee pain, based on rigorous scientific testing followed by peer reviewing,
is still just a theory. Even the most long-standing, widely supported, thoroughly tested concepts in
modern science are still called theories: the theory of evolution; the theory of relativity; quantum
theory, etc. In practise, they are treated pretty much as facts because so far all the reliable evidence
ever gathered fully supports them, and you would never make any progress if you didn't treat them
as facts. But there might come a day when new evidence changes them, either subtly or completely,
so they are not facts, they are just extremely strong theories.
Repeated Testing
There are a huge number of ways in which results can be misleading, even when all the conventions
so far described have been followed. With the best will in the world, random chance does sometimes generate extreme results. Imagine you toss a coin ten times. Even though the theoretical odds
of getting a head are 50/50, you are unlikely to get exactly 5 heads. You may well get 6 heads, or 3
or 7 or occasionally even 10 or 0. That's how randomness works. If you saw ten coin tosses and
every single one was a head, you might think something strange was going on. But if you toss the
coin 100 times, you are less likely to see such extreme results because opposite extremes (i.e. a run
of heads and a run of tails) will begin to cancel each other out. (This is another example of regression to the mean.)
Apply that to trialling a new cancer drug: if you have a small data set, let's say a trial which only
includes 10 people, random chance can have a huge effect on the results. Cancers go into remission
spontaneously and apparently randomly; an unlikely occurrence but it would account for 10% of the
data if it happened to one of the 10 people in your trial. But if your trial includes 100 or 1000 people, those random spikes in the data are more likely to be smoothed out, although they can still occur.
P Values
Chance can be controlled for mathematically. You can calculate a 'significance level' for your experiment ', and a 'P value' from your results. If your P value is less than the significance level, you
can consider the results to be within the range of random chance, meaning nothing significant happened. If you are trialling a cancer drug, this result means the drug has not shown any statistically
significant effect.
P values and significance levels are massively complex. The above example is only there to give
you an idea of what they are for. I'm not even going to attempt to explain how they work. That's because I haven't a clue! But at least we now know what the experts are talking about when they mention them: it is the mathematics they use to control for fluctuations in their results caused by nothing
more than random variation, rather than being caused by efficacy of the medicine (or whatever)
which they are testing.
Meta-analysis and Systematic Reviews
Random variation caused by chance is one of many reasons why repeated experimentation by peers
is so vital. Even when a huge test group has been used, results which fall beyond the significance
level could still be attributable to a rare freak of random chance. The more an experiment is repeated, the more those freaks of chance are mitigated. And, similarly, the bigger the data set (or
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number of people involved in a drug trial, for instance) the 'cleaner' the data will be. A great way to
simulate a huge data set is to add together all the data from lots of different experiments where good
scientific methodology was used, and treat it as a whole. This is called a 'meta-analysis'. In a metaanalysis, the effects of random chance are, to a great extent, mitigated, thus smoothing out those
freak spikes in the data and giving a much clearer view of the evidence.
But you can't just lump together all the data from every trial ever performed on a particular drug (or
whatever is under review). There is no point including data from trials which used flawed methodology because those data are not to be trusted. So you must select only the trials where the methodology was sound. This selection process is vastly different from the biased process of cherrypicking. It is complex and thorough, and is called a 'systematic review'. Systematic reviews often
reveal all sorts of unexpected surprises, and are vastly more trustworthy and definitive than any one
trial or experiment. But they can cause great offence. Imagine you are pioneering a particular drug,
say for instance, a homeopathic remedy of some kind. Even though the scientific consensus is that
homeopathy doesn't work, you are convinced that you have some evidence to the contrary, generated by one or more trials. But in a systematic review of all homeopathic trials ever conducted, the
trials you have been championing are rejected, and the final conclusion of the meta-analysis is that
there is no evidence for the efficacy of homeopathy. You would be jumping up and down, claiming
injustice and prejudice and victimisation. Well, you would if you were the kind of scientist who becomes so emotionally attached to an idea that you are not prepared to accept unbiased scrutiny. And
systematic reviews are unbiased: the judgements as to whether or not to include a trial are made
without knowing the actual results, only the methodology, so systematic reviewers are not able to
cherry-pick.
If the preceding few pages can be seen as a layman's tour through the key features of the scientific
process, the systematic review can be seen as the tour's dramatic final destination. We have arrived
at the Grand Canyon of science, the Niagara Falls of finding things out, the Great Pyramid of truthseeking. It is a magnificent thing. Feast your eyes on its beauty.
So now let's see what joys skepticism has in store.
Skeptics
Despite my mighty grade C in 'O' level biology and my monumental grade B in 'O' level physics, I
consider myself a science layman, and I am also fairly new to the world of skepticism. New, that is,
in terms of having only just realised there are other people out there formalising the skeptical process in the same way as science formalises the process of experimentation. I have always been prone
to a bit of casual scepticism (with a c), but was excited beyond words to discover the skeptical (with
a k) community. So I want to finish by looking at how the skeptic community fits in with the scientific community, and what they actually do.
Science is like a lasagne. Yes, it is. Don't argue. At the bottom you have the scientist who formulates
a hypothesis. In the layer above that, you have the scientist who carries out an experiment to test the
hypothesis. Above that you have various layers representing the peer review and repeated experimentation processes, meta-analyses and systematic reviews. By the time we reach the top layer of
pasta we have a fully formed theory. On top of that is a layer of bechamel sauce, representing the
media, with all its good and bad reporting of science, because, despite all the exquisitely careful
scientific truth-seeking going on in laboratories the world over, scientists don't have time to tell the
public what they are doing. That is inevitably left to the newspapers who have enormous fun creating punchy headlines from snippets of scientific data they either don't understand or have no interest
in accurately describing. I shouldn't tar all media outlets with the same brush of course, but even the
reputable broadsheets, and even the BBC are sometimes guilty of creating a sensational story by
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distorting or misinterpreting something they read in a scientific paper, transforming it into a work of
science-fiction, and calling it news. But then comes the cheese layer. That top layer of crunchy bubbling cheese is the skeptical community who make it their business to pick apart the nonsense in the
media, and bring the truth to the public outside of the scientific community. They do this through
various media outlets of their own (see the 'How to Find Out More' section below) and by launching
campaigns to stop the wrong-doing of dangerous pseudoscience. They report fraudulent advertising
of pseudomedicine to the Advertising Standards Authority (www.asa.org.uk). They lobby parliament and certain regulatory bodies, such as, in the UK, the Medicines and Healthcare Products
Regulatory Agency (www.gov.uk/mhra) and, in the United States, the Food and Drugs Administration (www.fda.gov), to name just a couple, on important skeptical issues. They investigate extraordinary claims and take to task companies and individuals who sell products and services which
don't work. You too can get involved in these actions, combating pseudoscience, pseudomedicine
and the corruption within big pharma.
The scientific, evidence-based approach of skeptics enables them to scrutinise all sorts of topics and
subject areas. I've just focussed on science because of the very real harm that can be caused by
pseudoscience and pseudomedicine, but skeptics are often equally interested in history, mythology,
politics, religion, economics, theology, the supernatural, conspiracy theories, UFOlogy, and so on.
Instead of just accepting what they are told, skeptics examine the quality of the information. Where
the information relates to evidence gathered through experimentation, skeptics ask: was the scientific method rigorously adhered to? Does the information rely on anecdotal 'evidence'? Does the information come from someone with a vested interest in promoting a product or service? If the information comes from a lone maverick, is there any reason to believe their claims? That lone maverick could even be a well respected scientist. Just because their past achievements have been sound
and important does not mean their future ones will also be. Take for instance the double Nobel
Prize-winning Linus Pauling who then went on to promote vitamin C mega-dosing as a miracle cure
for all sorts of ailments and diseases, including cancer. He was a well-respected, leading scientist in
more than one field, and a quack in another.
Skeptical analysis of medical claims can help save lives. But in less immediately life-threatening
fields it is also important. Anywhere you find someone promoting an idea, theory, claim or piece of
advice which does not stand up to scientific scrutiny, there is also, by definition, an anti-science
message, and that is a dangerous one. Even the very friendly, well-meaning naturopath with an apparently harmless alternative health spar in a beautiful rural setting – a relaxing retreat upon which
you'd only want to turn the skeptical spotlight if you were a complete arse – is inadvertently promoting the anti-science message by, for instance, telling you what wonderful things wheatgrass
juice will do for your body despite what the scientists say. "Don't listen to scientists, they don't want
you to know the truth!" is what you probably won't hear them say, and what they are probably not
even thinking, but most definitely is the message that underlies any unscientific or pseudoscientific
claim. And this is the same for all other fields too, not just ones with a medical theme. UFOlogists
telling you the government doesn't want you to know the truth about UFO sightings; conspiracy
theorists telling you the government – or big pharma, or the Illuminati, or whoever – are filling the
atmosphere with poisons sprayed from the backs of planes; holocaust deniers twisting the historical
data to match their own claims; they are all spreading their own versions of the anti-science message, deliberately or inadvertently telling you not to trust what you are told unless you are told it by
them. The skeptical message is not the opposite of that. The skeptical message is, simply: scrutinise
everything, no matter who says it. Conspiracies do exist. History records countless examples. So
there might really be a global conspiracy to control our minds with gasses sprayed from the backs
of planes, and if the evidence supports that then we must not ignore it. But all too often the evidence, when properly scrutinised, does not support wild claims, and without evidence the claims are
no better than guesses. So the message from these lone mavericks becomes 'believe my unsubstantiated guesses, and don't believe the mainstream consensus.' Ultimately, this is as damaging as the
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anti-science message from the world of pseudomedicine because if we all just believe what we want
to believe, we will often end up believing things which are completely wrong, and no progress can
ever be made that way. Science and skepticism are the tools which stop us falling into that bottomless pit.
Scientific skepticism works a little like the way our legal system works. In law, you cannot convict
the accused unless your evidence is utterly watertight. If it's not, the case will be thrown out. That
evidence is painstakingly scrutinised by all involved until the guilt of the accused is utterly irrefutable, or the evidence is deemed to be no good. Skeptics use the same rigour to examine wild claims
in just about any field of research. Like scientists, skeptics will change their minds when faced with
reliable, irrefutable evidence, even if it means abandoning former beliefs. Belief is not a choice. No
matter how hard I try, I cannot make myself believe that 5+5 is 11. Belief comes directly from what
the evidence indicates, and scientists and skeptics work hard to ensure the evidence we are given is
solid.
Here's another analogy for you: the world is like Wikipedia. I'll explain. Wikipedia is totally opensource, meaning anyone can put what they like up there and anyone else can change it. Theoretically, it could be full of utter rubbish. It could be a repository for vast jungles of misinformation and
pseudoscience, and the equivalent in other subject areas. But it isn't. Wikipedia is not 100% reliable,
but it is at least a great place to begin your research into just about any topic. There are just enough
people interested in seeking the truth to 'police' Wikipedia, purging the nonsense and populating its
pages with accurate information. It's an uphill struggle, but they are, by and large, winning. In this
way, Wikipedia is like the world. Most people aren't consciously interested in actively truth-seeking.
There are more people out there who will feed you misinformation than will tell you scientific
truths. But the truth is always more powerful than misinformation, and, as science paves the way
forward, misinformation is gradually exposed and shown to be worthless, and so the truth comes to
the fore.
That might all sound a bit overly optimistic, and probably is. I haven't forgotten all the bad science
and publication bias I touched on earlier. But I am optimistic about this. Science progresses in a
'three steps forward, two steps back' fashion, but it does progress. Science works, and whether we
are scientists ourselves, whether we have no interest in science or are militant enemies of science, it
is science which leads us forward, furnishing us with information to fuel progress. Science makes
the world better. The computer on which I'm typing now is a product of science. The car you drive,
the TV you watch, the sunscreen you smother yourself in, your glasses, your fridge, your smartphone, any medicine you take are all products of science. Without good science and solid truthseeking, none of those would exist at all. You can't build a working microchip from bad science and
misinformation.
Similarly, you can't cure (or treat effectively) cancer using pseudoscience and pseudomedicine. so
it's strange that so many people are so credulous about pseudomedicine. You wouldn't find pseudocar-manufacturers successfully selling things they insist are cars but which don't actually work, or
pseudobakers selling bread made of rubber, or pseudo-tailors selling invisible pseudoclothes (except
in the case of that particular emperor of legend). But you do find pseudoscientists trying to sell you
pseudomedicines all the time, and in some cases this is potentially extremely dangerous, so the
skeptical community has their work cut out for them.
It fascinates me how easy it is to get the world to believe in a crazy idea for which there is no evidence. It seems that anyone can proclaim anything, and if they do it loud enough and the media
picks it up, that proclamation is out there, and people will believe it. It doesn't matter how roundly
and conclusively it is disproven by science, the belief endures because science cannot make definitive statements like 'this hypothesis is wrong'; it can only say things like, 'there is no evidence to
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support this hypothesis'. Remember, science is totally open-minded. To the public, that sounds
weak, so they prefer to believe the much stronger statements coming from the proponent of the hypothesis, like 'homeopathy can cure you', and 'the MMR vaccine causes autism' (to use real-world
examples), even though those statements are baseless. Absence of evidence is not evidence of absence, as you will hear them say in order to defend their evidenceless position, but sometimes you
do have to concede that if there was anything to these claims, there would be some evidence to support them. Science does the donkey work, i.e. providing the evidence or showing that there is none.
Skeptics take it from there.
But how do you know you can trust what skeptics tell you? Well, when a mainstream newspaper
prints a story about how scientists have found a new magical cure for something, skeptics don't take
their word for it, they look-up the actual scientific paper at the heart of the story, pick it apart, and
report to the public what the scientists actually found. You can do that yourself. Services such as
PubMed (www.ncbi.nlm.nih.gov/pubmed) will point you in the direction of literally millions of papers and essays which you can actually read, and make up your own mind about. I told you, science
is totally overt!
If you don't have time to trawl the PubMed archives, have a look at Behind the Headlines
(http://www.nhs.uk/news/Pages/NewsIndex.aspx), an NHS news service which applies scientific
skepticism to the big news stories on health issues.
Like science, skepticism strictly adheres to a peer-review process. You can leave comments on
skeptical websites, pointing out where the skeptic has gone wrong, and they will listen to your criticism, take it on board, and if you are right they will change their mind. They are not interested in
pre-conceived ideas. They are only interested in the truth. In the world of skepticism, lies simply
don't survive.
How to Find Out More
So, if you do now want to venture into the world of skepticism, it is very easy for you to do so.
There are various skeptic societies around the UK and the rest of the world. A good place to start is
the Mersyside Skeptic Society (www.merseysideskeptics.org.uk). You don't have to live anywhere
near Merseyside! They, and others such as the Greater Manchester Skeptics Society
(www.gmskeptics.org), produce a number of excellent podcasts such as Skeptics with a K and Be
Reasonable. They are also extremely active in organising and promoting events such as QED
(www.qedcon.org). If you are US based, or happy to travel there, you may well want to check out
The Amazing Meeting, (or TAM,) (www.amazingmeeting.com) which is organised by the James
Randi Educational Foundation (http://web.randi.org/), or JREF. (JREF is well worth finding out
about. If you have an interest in the supernatural, search the internet for the JREF Million Dollar
Challenge.) On a more local level, you might find a Skeptics in the Pub group
(https://en.wikipedia.org/wiki/Skeptics_in_the_Pub) which runs events in a pub where speakers
come along to talk about a particular topic from a skeptical or scientific angle. I also recommend the
podcast Skeptics Guide to the Universe (http://www.theskepticsguide.org/). And if you like your
skepticism raucous and sweary, you can do worse than Cognitive Dissonance
(http://dissonancepod.com/).
One podcast which deserves special mention, the podcast which opened this world up to me,
is Skeptoid (www.skeptoid.com), and there are currently five books containing transcripts of the
podcast episodes. The Skeptoid podcast is all about the skeptical process of open-mindedly assessing the evidence, and as such, each 12 minute (or so) episode manages to be fascinating even when
examining a phenomenon which wouldn't normally interest you.
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I'm doing a huge disservice to all the other hundreds of excellent podcasts out there which I have
not mentioned, but you will be able to find them very easily through iTunes, Google, or your podcast app.
There is also a host of great books by various authors such as Ben Goldacre. His book Bad Science
is wonderfully humorous and deeply informative. You can also read his Bad Science blog here:
www.badscience.net. Michael Shermer's The Believing Brain is a little heavy going but ultimately
worth the effort, and his book Why People Believe Weird Things is enormously entertaining; Christopher Hitchens' The Portable Atheist is a fantastic compendium of wisdom by various authors on
religion; and, of course, just about anything by Richard Dawkins for an often evloution-focused,
sometimes confrontational anti-religion approach. I also recommend Skeptic magazine:
www.skeptic.com, and a Google or Amazon search will turn up many, many more excellent publications.
And one final recommendation: for a crash course in skepticism, listen to (or read, or better still,
watch on YouTube) Tim Minchin performing his poem Storm.
Once you dip your toe into the world of skepticism, you will discover an enticing wealth of fascinating material to read, listen to, watch and even attend in person. I hope I have given enough guidance here to accelerate the novice skeptic along that fascinating path of discovery. And if you were
coming at this from the point of view of one who has long been sceptical about science, if you have
always seen science as a secretive, dogmatic, threatening opponent, I hope I have shown you a different perspective and perhaps, if you were truly interested in knowing the truth rather than feeding
a prejudice, I may have changed your mind.
By Antony Wootten
------
Author's Note
I am not a journalist, podcaster, blogger or tweeter. I have written this purely because these words
were pounding away in my mind and I had to let them out. I have no idea whether they will be of
any use to anyone else, but I feel better for having released them onto these pages. If you would like
to pass this document on to anyone you feel would benefit from reading it, please do so freely.
Please don't change any of the content though, I do assert my copyright claim over it. If you would
like to alert me to inaccuracies and omissions, please email me.
[email protected]
This is in no way intended to generate publicity or attention for me personally, but in case anyone is
interested in what I do when I'm not writing overly long and amateurish essays on subjects I know
little about, my website is below. It has nothing to do with skepticism.
www.antonywootten.co.uk
copyright Antony Wootten, 2015
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