August 2020, ScientificAmerican.com 75Naomi Oreskes is a professor of the history of science
at Harvard University. She is author of Why Trust Science?
(Princeton University Press, 2019) and co-author
of Discerning Experts (University of Chicago, 2019).OBSERVATORY
KEEPING AN EYE ON SCIENCEIllustration by Jay Bendt
In college, I learned about the myriad logical fallacies that per-
vade our world. Good logic, it turned out, was pretty restrictive.
It consisted primarily of modus ponens —“If A is true, then B is
true. A is true. Therefore, B is true”—and modus tollens —“If A is
true, then B is true. B is not true. Therefore, A is not true.”
In contrast, there is a universe of logical fallacies. In science,
the most vexing typically takes the following form: My theory says:
if P, then Q. I design an experiment to see if Q obtains. It does.
Therefore, P is true. Sadly, this conclusion is logically incorrect. Q
might hold for a variety of reasons having little or nothing to do
with my theory. Yet scientists make this mistake all the time, which
led philosopher Karl Popper to argue that the method of science
is—or at least should be—falsification. Popper insisted that one
can never prove that a theory is true, because that would require
you to test it in every conceivable circumstance, which is impos-
sible. But just a single counterexample can prove a theory false.
While Popper’s theory was profoundly counterintuitive, many
scientists were attracted to it for its clarity and (apparent) logical
rigor. Yet there is a logical flaw here, too. My experiment could
have failed for reasons having nothing to do with the theory itself.
My experimental setup, for example, might have been insufficient-
ly sensitive to detect the predicted effect. This problem has no log-
ical resolution, but scientists grapple with it mostly through con-
silience (asking which explanation is most consistent with
evidence from a variety of sources) or inference to the best expla-
nation (looking at a problem from a variety of angles and seeing
which explanations hold up best).
All this is to say that logical fallacies are everywhere and not
always easily refuted. Truth, at least in science, is not self-evident.
And this helps to explain why science denial is easy to generate
and hard to slay. Today we live in a world where science denial,
about everything from climate change to COVID-19, is rampant,
informed by fallacies of all kinds. John Cook of George Mason Uni-
versity has, for example, undertaken an analysis of the logical fal-
lacies and distortions tied to climate change denial, which include
jumping to conclusions, cherry-picking data, raising impossible
expectations, relying on fake experts, encouraging conspiracy the-
ories and questioning the motivation of scientists. But there is a
meta-fallacy—an über-fallacy if you will—that motivates these oth-
er, specific fallacies. It also explains why so many of the same peo-
ple who reject the scientific evidence of anthropogenic climate
change also question the evidence related to COVID-19.
Given how common it is, it is remarkable that philosophers
have failed to give it a formal name. But I think we can view it as
a variety of what sociologists call implicatory denial. I interpret
implicatory denial as taking this form: If P, then Q. But I don’t like
Q! Therefore, P must be wrong. This is the logic (or illogic) that
underlies most science rejection.
Climate change: I reject the suggestion that the “magic of the
market” has failed and that we need government intervention to
remedy the market failure. Evolutionary theory: I am offended
by the suggestion that life is random and meaningless and that
there is no God. COVID-19: I resent staying home, losing income
or being told by the government what do to.
In many cases, these objections are based on misunderstand-
ings; evolutionary theory does not prove the nonexistence of God.
In others, the implications are real enough. Climate change is a mar-
ket failure, which will take government action to address. And absent
a system for widespread testing and contact tracing, there was no
known way to slow the spread of SARS-CoV-2 in the U.S. without
the majority of us staying home. COVID-19 has shown how danger-
ous the fallacy of implicatory denial is. When we reject evidence
because we do not like what it implies, we put ourselves at risk.
The U.S. could have acted more quickly to contain COVID-19.
If we had, we would have saved both lives and jobs. But facts have
an inconvenient habit of getting in the way of our desires. Soon-
er or later, denial crashes on the rocks of reality. The only ques-
tion is whether it crashes before or after we get out of the way.The False Logic
of Science Denial
Arguments against the reality
of COVID-19 mirror those against
climate change and evolution
By Naomi Oreskes
JOIN THE CONVERSATION ONLINE
Visit Scientific American on Facebook and Twitter
or send a letter to the editor: [email protected]© 2020 Scientific American