Causality, explanation, and deductions of predictions

Please follow and like us:

0.9k

1.1k

788

404

1k

This may be why we found Karl Poppers book “The Logic of Scientific Discovery” so interesting because in it he describes how the advance and growth of science rests on a doctrine of falsifiability and only those theories that are testable and falsifiable by observations add value to a scientific community.
On page 39, he writes:

“To give a casual explanation of an event means to deduce a statement which describes it, using as a premise of the deduction of one or more universal laws together with certain singular statements, the initial conditions.”

He later goes on to define these statements and how they are related.

The first or as he calls it the “universal statement of laws” apply to the entire universe.  These are more commonly called laws of nature.  Newton’s law of gravity would be an example of a universal statement because it can be applied throughout the universe.

The second or singular statement is defined as those that apply to specific events.  The temperature in Boston on the 15 of June was 75 degrees is an example of a singular statement because it applies only to that date.

Karl believes for a theory to be valid these singular statements must be deductible from the both the universal statements and a set of initial conditions defined by singular statements that establish the cause of an effect.

This may seem simple however, as Karl points out defining how these parameters are related is not.

Most modern scientists believe in the principal of cause and effect or “the assertion that any event can be causally explained.”

However, the fact that an event can be causally explained can have two different meanings depending on your interpretation of the word can.

One can, by using deductive logic define the “reality” or causality of an individual event by analytically observing that event.  However, because the prediction is based on observations of that individual event it is always possible to find a set of statements and initial conditions that will satisfy that prediction.

Therefore, this definition of cause and effect is unfalsifiable because the causality of each is based on individual parameters of an event and therefore will always be true for that event.

However, one can also define the causality of an event in terms of what Karl calls a “synthetic” reality or theory based on inductive logic by saying the “world is governed” by strict laws that are constructed so that every single event has a “universal regulation” or causality.

This definition of cause and effect is also unfalsifiable because if an event was discovered that did not fall into its definition of “universal regulation” it is possible to redefine it because it is based on a “synthetic” reality, which does not have a rigid structure of its own.

Karl dismisses the validity of most theories that are based on what he calls the “synthetic” reality of inductive mathematical logic.  For example, the predictive powers of the Quantum mechanics are based on defining their properties in terms of what he would call the “synthetic” reality of inductive mathematical logic.

He would consider this a “synthetic” reality because it is based on the abstract or inductive logic of equations and not on the deductive logic derived from observing how particles interact in a “real” or non-abstract environment.  This would make them unfalsifiable because it is always possible to insert new equations in a theory to validate any observation because they are not physically connected to the environment they define.

However, our ability to make detailed analytical observations of our environment has increased significantly in recent years.  This means we do not have to rely as much on the “synthetic” reality of abstract equations to define the structure of our theoretical models as we have done in the past. 

Summing up, Karl Feels theories developed on deductive logic derived from observing how particles interact in a “real” or non-abstract environment as we are doing in this blog would more likely to add value to scientific community because they would be testable and falsifiable by them whereas ones based on abstract mathematical logic are not.

Later Jeff

Copyright Jeffrey O’Callaghan 2008

Please follow and like us:

0.9k

1.1k

788

404

1k