Information Technology Reference
In-Depth Information
It is true that, considered as a science, computing is difficult to categorize. The
underlying theories—in particular, information theory and computability—appear
to describe properties as eternal as those of physics. Yet much research in computer
science is many steps removed from foundational theory and more closely resembles
engineering or psychology.
A widely agreed description of science is that it is a method for accumulating
reliable knowledge. In this viewpoint, scientists adopt the belief that rationality and
skepticism are how we learn about the universe and shape new principles, while
recognizing that this belief limits the application of science to those ideas that can be
examined in a logical way. If the arguments and experiments are sound, if the theory
can withstand skeptical scrutiny, if the work was undertaken within a framework
of past research and provides a basis for further discovery, then it is science. Much
computer science has this form.
Many writers and philosophers have debated the nature of science, and aspects of
science such as the validity of different approaches to reasoning. The direct impact
of this debate on the day-to-day activity of scientists is small, but it has helped to
shape how scientists approach their work. It also provides elements of the ethical
framework within which scientists work.
One of the core concepts is
falsification
: experimental evidence, no matter how
substantial or voluminous, cannot prove a theory true, while a single counter-example
can prove a theory false. A practical consequence of the principle of falsification is
that a reasonable scientificmethod is to search for counter-examples to hypotheses. In
this line of reasoning, to search for supporting evidence is pointless, as such evidence
cannot tell us that the theory is true. A drawback of this line of reasoning is that,
using falsification alone, we cannot learn any new theories; we can only learn that
some theories are wrong. Another issue is that, in practice, experiments are often
unsuccessful, but the explanation is not that the hypothesis is wrong, but rather that
some other assumption was wrong—the response of a scientist to a failed experiment
may well be to redesign it. For example, in the decades-long search for gravity waves,
there have been many unsuccessful experiments, but a general interpretation of these
experiments has been that they show that the equipment is insufficiently sensitive.
Thus falsification can be a valuable guide to the conduct of research, but other
guides are also required if the research is to be productive. One such guide is the
concept of
confirmation
. In science, confirmation has a weaker meaning than in
general usage; when a theory is confirmed, the intended meaning is not that the
theory is proved, but that the weight of belief in the theory has been strengthened.
Seeking of experiments that confirm theories is an alternative reasonable view of
scientific method.
A consequence is that a hypothesis should allow some possibility of being
disproved—there should be some experiment whose outcomes could show that they
hypothesis is wrong. If not, the hypothesis is simply uninteresting. Consider, for
example, the hypothesis “a search engine can find interesting Web pages in response
to queries”. It is difficult to see how this supposition might be contradicted.
In the light of these descriptions, science can be characterized as an iterative
process in which theory and hypothesis dictate a search for evidence—or “facts”—
