Although predictions based on past events can be an oversimplification. Scientists who study human behavior, for example, agree that past behavior is useful for predicting future behavior, but only under specific conditions. For example, the person must remain essentially unchanged and the anticipated situation must be closely similar to the past situation that activated the behavior. Without such assumptions, formulating predictions for human behavior will be highly unsuccessful. For instance, researcher Ajzen found that a student’s attendance rate for the first eight sessions of a semester-long course correlated with 0.46 for the second eight sessions. Despite class attendance being a habitual and routinized behavior and that there is little likelihood of profound changes in either the person or situation, the correlation is far from perfect.
Furthermore, predictions mostly work best for short time intervals, such as when predicting weather patterns. Dr. Edward Lorenz notes that chaos theory proves weather and climate cannot be predicted beyond a very short term (approximately 3 weeks). According to chaos theory, all the “initial” conditions in the atmosphere must be known to precisely predict what the atmosphere will do in the future. In addition, one must take into account other large-scale phenomena such as the effects of the planet’s rotation in space. Small changes in any one variable can profoundly affect the future weather. Lorenz described this problem as the “butterfly effect”, where small causes can have large consequences. The accuracy of predictions is constrained by the constancy of variables. Furthermore, the theory of chaos renders non-linear concepts such as turbulence, weather, the stock market or brain states virtually unpredictable Uniformities provide a basis to interpret the unknown and generate knowledge. However, people are consciously or unconsciously biased when they select uniformities or patterns that uphold their core beliefs. Religious systems, for instance, are shared systems of beliefs to explain the unknown. These belief systems are strongly dependent on uniformities as evidence that the beliefs are valid. An example is how religious leaders are claiming that “immoral acts” are responsible for the outbreak of the Ebola virus in Liberia.
The Christian leaders agreed that “God is angry with Liberia” and declared “Liberians have to pray and seek God’s forgiveness over the corruption and immoral acts (e.g. homosexualism) that continue to penetrate our society”. Both the Natural and Human Sciences tend to seek uniformities to derive theories to explain cause-effect relationships and make future predictions under the assumption that nature does not change. Our dependence on uniformity to generate knowledge will remain as long as we try to explain phenomena that are unverifiable. The assumption of uniformity is thus essential in the process of obtaining knowledge but does not provide incontrovertible proof that the knowledge is true.