There is lots of photographic evidence
on the Internet purporting to show various types of evidence. Some
claim to show evidence of paranormal things such as ghosts, orbs, or
UFOs. Others may claim to show evidence of health-related claims, or
evidence of various unexplained anomalies such as Bigfoot. Others may present photos attempting to
back up more modest claims, such as the claim that “my cat is
really smart” or “my dog has special abilities.” But many a
modern scientist may think that all such evidence can be ignored, on
the grounds that it does not meet the “gold standard” of
publication in a peer-reviewed journal.
But is some experimental evidence
described in a peer-reviewed journal generally better evidence than
photographic evidence in a scrupulous photo blog (such as one that is
careful about requiring that photos be from a dated identified source, rather
than passing along anonymously posted photos)? I think it is not. I
will now give some reasons to support this claim.
Reason #1: Photographic evidence is
in general better evidence than merely experimental evidence.
In general, photographic evidence is
more convincing evidence than experimental evidence. For example,
imagine if I do some experiments suggesting that John Blackheart
killed his wife. Whatever such experiments suggest, they do not have
the evidence value of a photograph showing John Blackheart killing
his wife. Similarly, I may do some fancy computer experiments
suggesting that a particular star is going to soon explode. But such
experiments do not have the evidence value of a photograph showing
the star actually blowing up.
Reason #2: The number of
hard-to-detect “ways to go wrong” in a complex experiment is much greater than the number of hard-to-detect “ways to go wrong” when
taking a photograph.
Once we dismiss some invalid claims of
skeptics (some of whom incorrectly imagine that the air in front of
our cameras is typically filled with dust sufficient to mislead us,
and that your ordinary breath is sufficient to produce what looks
like a ghost in a night photo), we find that the number of ways in
which you can go wrong when taking a photo is pretty small. It is
also true that in almost every case in which a photographic mistake
might mislead you, the mistake is easily detectable. For example, if
you point your camera at a bright light, it may produce lens flare
that misleads you; but that has a very characteristic look, so it's
easy to detect (and easy to avoid). Similarly, if you move your
camera violently while taking a picture, that may produce a ghostly
look that misleads you. But that also will produce a very
characteristic look that is very easy to detect, and avoid. The same
thing holds true for the mistake of photographing your camera strap –
it may create a weird-looking white streak that may mislead you, but
it has a very characteristic look that is very easy to recognize. So
in general, detecting errors in photos is pretty easy, and avoiding
such errors is also pretty easy.
But when it comes to experiments, we
have a totally different situation. There are countless subtle ways
in which a complicated experiment might go wrong. A scientist might
make a mistake in setting up the “controls” that are used with
the experiment. Or he might make a mistake in any of a number of
measurements used in performing the experiment. Such a mistake could
involve using some piece of fancy equipment incorrectly, which is
very easy to do (since such instruments are often harder to use than
one of the old VCR machines). Or a mistake (such as ordinary human
clerical error) might be made in writing down a result after reading
a scientific instrument. Or a mistake might be made when tabulating
or summarizing data collected from different sources. Such a mistake
might be as easy to make as a typographical error entered into a spreadsheet.
Similarly, scientific work based on computer experiments offer 1001
opportunities for error. Such experiments often involve many
thousands of lines of code, and a programming bug might exist in any
one of those lines. Also, experimental bias might lead to errors in
the design or interpretation of the data.
With this thing, you're 1 button click away from a false result
In short, photographs are much simpler
than complicated experiments, and offer much less opportunity for
error.
Reason #3: Many scientists have
financial incentives to cheat on experiments, but most bloggers do
not have any financial incentive to cheat when producing photographs.
The overwhelming majority of blogs make
no significant money for those who write them. So almost all bloggers
have no financial incentive to cheat by posting fake photos.
But when it comes to scientific papers,
one often finds a different situation. Many scientists have financial
incentives to cheat on experiments. The most obvious case is
scientists who are taking money (directly or indirectly) from
corporations that desire a particular experimental result
(corporations such as oil companies, tobacco companies, and
pharmaceutical companies). More generally, it would seem that many
scientists have a financial incentive to cheat in order to produce
some dramatic experimental result (although this does not tell us
anything about what percentage of them cheat, and we may presume that
most do not cheat). A scientist who can claim to have produced some
breakthrough result is more likely to keep his job, or to get a
better job.
Reason #4: Peer-review is greatly
overrated, because it is an anonymous process that does not involve
auditing the data behind a scientific paper, and therefore does
little or nothing to show that the paper was produced without
cheating.
We have heard so much hype about
peer-review being some “gold standard,” that one might imagine
that when a paper is peer-reviewed by other scientists who didn't
write the paper, those scientists drop in on the paper's authors to
check their source data and log books, to make sure that things were
done without any cheating. But nothing of the sort happens. Instead,
peer-review is an anonymous process. A paper's authors never meet
those who are doing the peer review.
Accordingly, peer-review offers little
opportunity to detect that an experiment was done without cheating. A
peer-review may be able to detect if a paper commits math errors or
errors of fact (such as listing the wrong chemical formula for a
particular molecule). But a peer-review cannot find something such as
an experimenter who simply faked things in order to be able to claim
an experimental breakthrough, and enhance his job prospects.
Detecting such a thing would require face-to-face visits, which don't
occur under the peer-review process.
Reason #5: You have no way of
detecting whether an experimenter cheated while doing the research
for a peer-reviewed paper, but you can investigate the authenticity
of Internet photos.
There exists software that you can use
to detect fake photos. One example is the free site
www.fotoforensics.com.
The site is easy to use. You can go to a blog, cick on a photo to get
a URL that lists only that photo, and then paste in that URL into the
“URL” slot on the www.fotoforensics.com
site.
Could you use any similar technique to
check out the validity of the original source data from which
peer-reviewed scientific papers were written? No, because scientists
rarely publish such data.
Reason #6: Scientific experiments
are often robbed of their evidence value by a subsequent experiment
on the same topic, but a similar type of thing is rarely possible
with a photograph.
A
scientific paper on the PLOS One site had the startling title “Why
Most Published Research Findings are False.” One
of the points made in this paper is that scientific studies are very
often contradicted by later scientific studies on the same topic. For
example, one study may show that Substance X causes cancer, while a
later study may show that Substance X does not cause cancer.
As reported here, a head of global
cancer research at Amgen identified 53 “landmark” scientific
papers, and had his workers try to reproduce as many as they could.
It was found that 47 of the 53 results could not be replicated.
So it is very
common – perhaps even probable – that a randomly selected
peer-reviewed paper of experimental results may be “undone” by
subsequent research. But there is no such problem with a
photograph. Suppose one investigator gets a photograph seeming to
show a ghost (or an orb with a face) at a particular location. If you
take a later photograph of the same spot that does not show such an
anomaly, that does not at all undo or cancel out the previous
photograph. The evidence of that photograph still stands. It is
immune to disprove by taking additional photographs at the same site.
While such photographs (if made in sufficient number) may show that
some paranormal thing does not usually occur at some location, they
can never show that the first photograph did not capture a paranormal
sight that may occur only rarely.
Reason # 7: The total amount of peer
review on a popular “photo blog post” exceeds the peer review for
the average scientific paper
A typical
scientific paper is reviewed by two people, and then receives no
further peer review after its publication. Part of the reason is that
online scientific journals offer no convenient mechanism for posting
comments to a published paper. It is true that the http://arxiv.org
server (which hosts lots of physics papers) has a “trackback”
mechanism by which you can write a blog post and then have your blog
post be listed in the same place that the original paper is available
online (kind of buried at the bottom). But you can do that only by
using some nerdy hard-to-use “embedding” technical trick.
Partially because it is so hard to post an online comment to a
scientific paper, most peer-reviewed scientific papers end up being
reviewed by only 2 peers of the paper's authors.
But a popular post
on a photo blog may end up getting dozens of user comments, many of
which qualify as being a form of peer-review. So a popular post may
end up getting ten times more peer-review than the average scientific
paper.
Conclusion
In short, there is no sound basis for
thinking that experimental evidence published in peer-reviewed
journals is a form of evidence superior to photographic evidence
published on scrupulous web sites. The myth that
publication in a peer-reviewed journal is some greatly superior “gold
standard” is a convenient excuse used by many materialists, an
excuse for ignoring evidence that may upset their worldview, and
contradict their dogmatic assumptions. But there is no sound basis
for assuming that some experimental result published in a peer-reviewed journal is
more likely to be true than something that is shown abundantly in
photographs outside of a peer-reviewed journal.
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