The Two Types of Knowledge (or How to
Be Smart)
Although
the paper that introduced the theory of evolution to the world was published in
1858, Charles Darwin first conceived of the idea in 1838.
He had
spent five years on the HMS Beagle as a geologist when he noticed something
peculiar in his records: the geological distribution of fossils and wildlife
showed a pattern of change between different species.
At the
time, the controversial predecessor to Darwin’s theory was transmutation, which
rightly suggested that one species changes into another, but which wrongly
assumed that this occurs due to some spontaneous life-force, or laws that kick
into play at different predetermined times by God, or some other mysterious but
unidentified process.
Critics
saw it as a feeble attempt at the materialization of life, an idea that had
taken hold of the world ever since the Enlightenment, without any compelling
evidence to support its radical claim.
That
initial paper published by Darwin (along with Alfred Russel Wallace, who had
come to similar conclusions), however, was strong where transmutation was weak:
it gave a specific process for this change.
In any
population of a species, we have variation in phenotype (observable
characteristics), arising from mutations that occurs in the genome and from the
epigenetic changes that occur during life, and the result is that different
individuals in a group of organisms show differences in their ability to adapt
to their environment — some do well and
survive; others don’t.
This
simple process of variation and selection explains how a common ancestor
produces the diversity of life we observe in the biosphere.
In
this way, life is — as Jonas Salk, the famed
medical researcher put it — “an error-making and
error-correcting process.” It gives us many attempts at overcoming the
challenges of any environment by introducing variation, and it then selects the
correct answer by eliminating what doesn’t work.
Useful
knowledge survives and gets passed down to newer generations, who can then use
this knowledge to enhance their effectiveness. But this, however, isn’t the
only kind of knowledge available to us.
Experimentation and Refinement
The
actual process of learning (or getting smarter) extends beyond our
predetermined genome, but evolution has set a precedent in form.
Even
the learning we do in the world follows a variation and selection (via
elimination) pattern. We try lots of different things, we see what works, and
then based on the results, we eliminate the competing options, selecting for
the skills that will be most useful in the future, too.
Cognitive
neuroscience has a theory of mind (called predictive processing) that suggests
that the human brain is a prediction engine, which consistently creates our
perception of the world based on our past interactions within similar
environments.
In the
beginning, when you are young, there isn’t much information to go off of, so
you get mostly unconstrained inputs from the external world into your brain,
but as you get older, you start to filter through this variety for usefulness,
making better distinctions.
You
create mental concepts in your mind about what is important and what is not,
and then these concepts shape your future perceptions by using the
already-selected knowledge to further select knowledge.
This
entire process is mostly intuitive, and what keeps it updating is
pain/pleasure, which tells your body that a certain perception and your
corresponding reaction should either be reinforced or not. But some forms of
experience on the pain/pleasure axis like surprise and awe can be used to
intentionally tell your mind that something unexpected was experienced, too,
encouraging you to consciously readjust the conceptual model.
Whether
you are learning to play a sport or simply trying to create a more accurate
mental model of reality in your mind, you are working with a variety of
experiences, and within those experiences, you have to choose and reinforce the
ones that are the most useful to you.
In
this way, everything that you do is essentially an experiment that gets refined
and corrected with experience and practice.
The
difference between you and, say, a professional tennis player is almost
certainly that they have a genome that makes them more suitable to play their
sport, but more importantly, they have intuitive knowledge embedded in their
brain from all of the predictive processing they have done, in a very specific
environment, to refine their sense for what works and what doesn’t.
The
same can be said for great artists and scientists, entrepreneurs and investors,
and other everyday folks who do what they do well.
Our
brain is a prediction engine that builds knowledge and gets smarter as it
better aligns what it needs to do with the demands of the environment.
Conjectures and Their Refutation
Predictive
processing alone likely isn’t what makes humans unique. If it really is the
process by which we make sense of the world, the chances are that some form of
it appears in other animals in nature, too.
What
takes humans one step beyond this simple empirical knowledge-building is that
we can think in abstract concepts, with a complex language, and then share this
knowledge between us within culture.
The
best formal system that we have ever devised for this is the scientific method,
which operates based on a combination of asking questions, formulating
hypotheses, and then testing those hypotheses based on the data collected from
our experiments and observations.
In the
same way that we have variation and selection in evolution (and in our
empirical mental modeling), the philosopher of science Karl Popper suggested
that we have it in scientific inquiry, too, where we start by formulating a
conjecture based on incomplete information (a theory), and we improve on our
conjectures by refuting them.
Science,
in this way, can never be completely certain of anything but it can only get
more and more correct as we refute bad conjectures and replace them with better
ones and so on. And in order for something to be considered a scientific
theory, it has to be capable of being proven wrong.
We
don’t need to just rely on our mind updating itself by putting it in different
environments to gain knowledge; we can also make use of the abstract knowledge
we collectively build in culture.
Whereas
personal experimentation and refinement can improve a brain by directly
building its intuitive understanding, abstract theories (based on evidence) can
do the same thing without us needing to go through the same process that
someone else did to collect that knowledge.
There
is, of course, some important practical knowledge that is lost in the
translation from the abstract to the concrete, just like empirical knowledge
(from predictive processing) lacks the rigor that comes with having a
scientific community constantly challenging you, but both are capable of
adapting our minds in a way that is more useful to us.
By
updating our mental model, good conjectures, based on strong collective
evidence, can make our predictions of reality more accurate.
The Takeaway
Knowledge,
whether implicit or explicit, underlies everything that we do.
By
virtue of evolution, much of this knowledge is encoded in our genome, which
programs us before we are born. It has been selected based on generations and
generations of efforts to survive, implanting us with a general template of a
phenotype that is best suited for our environment.
In the
21st century, however, as our environment continues to change at an exponential
rate, the knowledge encoded in our genome is becoming less and less sufficient
for our attempts at making sense of the world.
Fortunately,
evolution has also programmed us with the ability to learn. With a mind that
experiments, predicts, and corrects, we can build empirical knowledge to adapt
us to other relevant environments.
We can
use our pain/pleasure axis and the affect that we experience as surprise/awe to
self-correct into building an intuitive understanding of the world that allows
us to master our surroundings and their demands.
To
further augment this intuitive understanding, we can also stand on the
shoulders of the giants that have come before us in culture by using their
theories and evidence to further sharpen our mental model of reality.
There
are many ways to define intelligence, and different definitions cater to
different expectations, but ultimately, it’s about how effectively an agent can
make sense of and navigate its environment.
Knowledge
and its application is the process that we build everything else on, and it
starts with what we do to feed it.
Zat Rana
https://medium.com/personal-growth/the-two-types-of-knowledge-or-how-to-be-smart-b06403c6858b
No comments:
Post a Comment