  It is widely believed that theory is useful in physics because it describes
simple systems and that strictly empirical phenomenological approaches are
necessary for complex biological and social systems. Here we prove based upon
an analysis of the information that can be obtained from experimental
observations that theory is even more essential in the understanding of complex
systems. Implications of this proof revise the general understanding of how we
can understand complex systems including the behaviorist approach to human
behavior, problems with testing engineered systems, and medical experimentation
for evaluating treatments and the FDA approval of medications. Each of these
approaches are inherently limited in their ability to characterize real world
systems due to the large number of conditions that can affect their behavior.
Models are necessary as they can help to characterize behavior without
requiring observations for all possible conditions. The testing of models by
empirical observations enhances the utility of those observations. For systems
for which adequate models have not been developed, or are not practical, the
limitations of empirical testing lead to uncertainty in our knowledge and risks
in individual, organizational and social policy decisions. These risks should
be recognized and inform our decisions.
