I typically peer review about two papers a year and I
remember a few years ago, I conducted a review of a potentially helpful study
on fishing boat air quality and the health of fishermen. It was a good study,
with helpful findings. Unfortunately, the sample size was unclear and when I
made inquiries, I found it was based on a sample size of one boat and crew. I
recommended that this sample size be stated explicitly or the paper be rejected.
I believe the paper was withdrawn because it never came back on my docket.
I have long been amazed at the tiny sample sizes used in
many studies. This isn’t evil but the potential weaknesses of studies need to
be more clearly stated. With the Reproducibility Project finding only 40% of
psychology experiments as being verifiable we should all have a cynical eye on
how science advances.
It is easy to overwhelm people with copious data and
statistical analysis. The process of verifying someone else’s data has zero sex
appeal. A.E. Housman
opined: "Some individuals use statistics as a drunk man uses lamp posts -
for support rather than illumination." I think he was right.
There exists a battle within science. Does is operate in
an environment where scientists quickly abandon previous theory in the face of
evidence, as Karl Popper would describe?
Alternatively, is it founded on paradigms and group behavior, as Thomas Kuhn
would assert?
Some philosophers (e.g., Kuhn and Feyerabend)
have extended this inquiry into the limits of the scientific method. They argue
that the outcomes of revolutionary times in science occur when traditional
mental models or paradigms are being challenged. Scientists will not abandon a
theory based on a single, falsification event. They seek (or await) a new
paradigm that accommodates new data; however, they do not do so with alacrity.
Data usually drives paradigms, from ‘grounded
theory’ approaches in the social sciences to inferential statistics. However,
data, or in a general sense evidence, is a product of data acquisition methods.
Evidence is also routed through biases connected with epistemology and context
(such as time, environment or other
circumstances). Moreover, evidence is routed through paradigms. All of these
issues, whether data error or biases rooted in epistemic or context, are a
threat to objectivity. The interface of evidence and bias can be
summarized by Heisenberg’s assertion that “the world cannot be separated from
our perception of it.”
Should designers care about scientific philosophy?
Design is an applied science and reflections
on the capability and limitations of science are helpful for understanding
potential benefits. We can recognize that not all technical advances are
orderly and founded on historical developments. Some philosophers (e.g. Paul Feyerabend
and Stanislav Grof) would consider the whimsy and chaos of individuals as
productive and powerful agents of change. Others (e.g., Richard Rorty)
considered some final truth to never be attainable or even desirable, which
points back to the 18th century Scottish philosopher, David Hume’s
realization of there being no end point in proving scientific theories. He
argued that the contentious and muddy world of scientific (and what Kuhn would
call pseudo-science) pursuit is good.
However, the necessity of creative forces in
formulating new paradigms does not negate the power of the scientific method,
from the practical inventions of Thomas Edison to Richard Feynman’s march
through theoretical physics. Designers use abductive reasoning with its
reliance upon a conclusion of an operating product rather than formal rules and
preconditions – the ends justify the means. And they can throw away bad
results/conclusions.
Design can seem to be arbitrary – a small whimsical
thought can lead a team to pursue an approach that cannot easily be reversed. Is
this idea superior or is there something much better that has not been
conjured? Synthesis of ideation and
‘bounded rationality’ will lead to a final concept upon which copious time and
talent will be spent.
Designers need science and
engineering. Advances in material science, information technology and
manufacturing techniques provide our fuel for dramatic change. In the end, we
seek to design things that work. The word ‘things’ is used purposely. The 21st
century designer is not just designing products — we are designing experiences,
interactions and solving systemic problems. We run our hand along the guiderail
of science but are not afraid to use our creativity and undefinable abilities
in developing design solutions.
