What's important about science? We think the
most important aspects of science are
skepticism, empiricism, and rationalism.
The first refers to an attitude toward beliefs and assumed
facts, the second refers to a way of knowing true reality, and
the last involves the use of reason in the search for reality.
We'll say more about all of them below.
These key factors are what makes science important in human
existence (including human survival), what people, especially
those who doubt, or criticize science, need to take into
account.
Human fallibility:
But before we start, we are NOT, we repear NOT saying that
science is infallible. As it happens, a substantial amount
of criticism directed at science concerns its fallibility.
So let's address this right off the bat: Science is a human
activity. Humans can be fallible. So science can be fallible.
For those who are
interested, this is a sort of a logical syllogism: if (a) Humans do
science, and (b) Humans can be fallible, then (c) the science
can be
fallible.
BUT as you will see in the discussion below,
scientists know this (that humans can be fallible), which is why they created science, a way
of knowing about the world that takes into account human
fallibility, particularly in knowing reality, and tries to remedy it over time.
So, as we often do, let's start with a
definition:
science (noun):
1. A branch of knowledge or study dealing with
a body of facts or truths systematically arranged and showing
the operation of general laws: the mathematical sciences.
2. Systematic knowledge of the physical or
material world gained through observation and experimentation
(i.e., the scientific method).
3.Any of the branches of natural or physical
science.
4. Systematized knowledge in general.
5. Knowledge, as of facts or principles;
knowledge gained by systematic study.
Epistemology: How we know things.
As you read through these five definitions of
science, you'll see the word "knowledge" more than once.
We just thought you'd like to know that this falls under the
philosophical topic of epistemology, which is all about how we
know things.
Scientific Method: What it boils down to is this: Science is a
way for humans to know things about the world around them, what
the physical world is comprised of and how it works.
As we'll see below, science employs a method that helps minimize
human fallibility and maximum the validity of what we learn from
it. The development of what came to be called "scientific
method" has been seen as the basic foundation for what came to
be called "science."
Skepticism:
Scientists are all skeptics. They take nothing for
granted and do not rely on beliefs or opinions for finding truth
and reality. To an extent, this means that they approach
things with doubt. This does not mean that they assume all
opinions and beliefs are false. They simply believer they
must be verified by observable data.
Reasoning: Skepticism uses
our ability to reason, apply critical thinking, collect and
analyze observable data to find true reality. It is a
process whereby scientists seek to determine validity of a
supported conclusion that arise from well designed research, NOT
the process of finding a preconceived conclusion. This
last point is crucial. Science does everything possible to
avoid the fallacy of confirmation bias (seeking to prove
what one already believes to be true).
Plato vs. Aristotle
We can trace our approaches to knowing things
all the way back to these two ancient Greek philosophers, Plato
and Aristotle.
Plato held that pure reason was the path to
knowing and truth.
Aristotle, a student of Plato, held that
observation was they way.
These two approaches result in empiricism and
rationalism.
Empiricism:
This is what we call knowing based on
observation. Science is based on empiricism (the
Aristotelian approach), knowing by means of seeing. Over
the years, observation has become more difficult (e.g., in
subatomic physics), but science continues to strive toward
accurate and valid observation.
Rationalism:
This is the application of reason to what we
observe (using the Platonic approach). Science is also
based on rationalism, especially in how we view causality and
form theories for explaining how things happen. Scientists
use reason and logic to form their understandings.
Spiritualism:
Science does NOT employ spiritualism.
Science looks to find the laws of nature but not who, or what
created those laws. Science is NOT incompatible with
spiritualism, or any set of religious beliefs (except religious
beliefs that invalidate science). There are plenty of
scientists who believe in God.
To
see the website for an
international organization that deals with the relationships
between science and religion.
Paradigms:
As defined by the Oxford English Dictionary a paradigm
is "a typical example or pattern of something; a pattern or
model". In an important book about the history of science,
The Structure of Scientific Revolutions (published in 1962),
Thomas Kuhn defined the term as: "universally recognized
scientific achievements that, for a time, provide model problems
and solutions for a community of practitioners."
The once
held notion that the Earth is the center of the universe is a
paradigm that was eventually abandoned--the paradigm shifted.
Science looks to explore within the context of a paradigm,
and further when a paradigm proves less useful, identify new
paradigms.
Imagination:
Science DOES use imagination. In fact, Einstein himself
was noted for using his imagination to come up with a
"thought experiment" in his theorizing about relativity.
In order to expand knowledge, it is valuable to imagine
different was to look at things (new paradigms-see below).
An hypothesis is an exercise in imagination.
At times, it is imagination that leads to scientific
revolutions and paradigm shifts (e.g., the shift from seeing
earth as the center of the universe to seeing it as simply a
part of the universe).
Facts and Theories:
Elsewhere on this website we discuss the
difference between these two (click
HERE to see that discussion). For now, we just want to
say that what science observes are facts, which are neither true,
nor false, but just facts (.e.g., if you drop a rock, it will
fall to the ground--that is a fact.). Facts are the
data scientists seek to discover and explain.
Errors in
observation: While the fact, in itself, is neither true, nor
false, our perceptions can be true, or false. That doesn't
change the fact as an external, objective reality. It just
means, we haven't truly seen the fact. These errors can
occur as a result of our method for viewing the fact (for
example, we use an incorrectly calibrated instrument). And
they can result from internal, mental biases, which we discuss
elsewhere on this website.
To
see our introduction to this matter of bias.
Theories offer explanations for those facts
that are based on our reasoning, often using cause and effect to
arrive at laws of nature. Theories can be valid, or
invalid. Science continuously seeks to validate various
theories, often replacing those that are found invalid (often do
to limitations in the theory, that is, things it can't account
for) with new theories. An example would be how the theory
of relativity expanded Newtonian mechanics, and then quantum
mechanics came to expand or replace both.
Model:
Often, scientists use models, both as a preliminary to
developing a theory, and as an ongoing method for testing a
theory. So a model is a verbal, mathematical, or visual
representation of a scientific structure or process, which
allows scientists to construct and test inferences and theories.
Like theories, models can be valid, or invalid.
Crucial
Point: Theories and models are all part of how scientists go
about developing and sharing our understanding of realities of
how the world works. Of the two, facts and theories, the
facts are most important. If a theory about how the facts
function is invalid, that does NOT invalidate the facts.
Scientific Goals:
There are several things science seeks. Here are
some of the most important:
Prediction
Some might consider this the
ultimate goal of science, predicting what can and will happen.
Science seeks to know what causes will lead to what effects in
what circumstances. As mathematic models (often employing
probability and a new notion called "fuzzy logic") have become
more complex and sophisticated, science looks toward the
interaction of multiple causes leading to multiple effects.
A prime example of this would be weather prediction (we're
talking about local daily weather, not climate, but it can
extend into that area as well).
Accuracy
Remember we mentioned observation
above? Well, the issue here is how accurate are the
observations. Science works constantly to improve
accuracy, often by developing new observational techniques (the
cloud chamber used to observe subatomic particles is such a
technique)
Reliability
In science, reliability has to do
with replication. For something to be reliable, we have to
know it will repeat. For example, for a bridge to be
reliable, we have to know we can cross it more than once
(usually, many times more).
The more something is replicated in
research, the more reliable it is. Another way of putting
it is, reliability results when the same (or highly compatible)
results are achieved by same study repeated either over time, or
by different researchers, or both.
Validity
Loosely speaking, this refers to
truth, how true are the findings of the research. There
are several different types of validity.
Content/Construct Validity:
What this looks at is does the research actually study what it
says it studied (e.g., Does an IQ test really measure
intelligence)? Were the constructs (these are
theoretical concepts) and the contents (design of the study)
appropriate to the study? In other words, doing an
experiment about subatomic particles by weighing baseballs is
NOT valid.
Internal Validity: Internal
validity occurs when it can be concluded that there is a causal
relationship between the variables being studied. A danger is
that changes might be caused by other factors. In other
words, internal validity means that we have looked at and
controlled enough of the variable, both causes and effects, to
say that A caused B. When internal validity is strong,
successful replication of the study is very likely.
It is important to note that
experimental studies examine causal relationships, but
correlational studies do not--they just look at how two, or more
things may change together.
External Validity: This
occurs when the finding in the study can be generalized to the
world at large. In other words, the findings aren't
limited to the laboratory.
Predictive Validity: As
noted above, many
see this as an ultimate goal. Scientist consider their
research and the theories they use valid when it leads to
prediction (e.g., predicting what will happen if dynamite is
ignited. More importantly, prediction can lead to
control. If we can predict an outcome from certain causes,
we can possibly create the outcome when we want and need it to
happen, OR we may be able to prevent that outcomes by
eliminating the causes.
Scientific Consensus:
This occurs when scientists
come to a shared finding, either through replicated research (see
reliability above), or through replicated analysis of data reported.
To be clear, this consensus is NOT a shared opinion. It is a
shared empirical perception based on repeated research and analysis.
Do scientists always agree?
No, but when they disagree, they have to present factual information and
clear description of analytical rationale. Without these, such a
disagreement falls into the realm of opinion.
It is important to understand
that science is ultimately a group endeavor, and any factual competition
between scientists is of benefit to us all.
To
go to the introduction to science
To
go to read about the Scientific Method
To
read about the reliability and validity of scientific findings.