June 2, 2020
Deduction, induction, abduction
In deductive inferences, what is inferred is necessarily true if the premises from which it is inferred are true; that is, the truth of the premises guarantees the truth of the conclusion. A familiar type of example is inferences instantiating the schema All As are Bs. a is an A. Hence, a is a B.
Inductive inferences form a somewhat heterogeneous class, but for present purposes they may be characterized as those inferences that are based purely on statistical data, such as observed frequencies of occurrences of a particular feature in a given population. An example of such an inference would be this: 96 per cent of the Flemish college students speak both Dutch and French. Louise is a Flemish college student. Hence, Louise speaks both Dutch and French.
The mere fact that an inference is based on statistical data is not enough to classify it as an inductive one. You may have observed many gray elephants and no non-gray ones, and infer from this that all elephants are gray, because that would provide the best explanation for why you have observed so many gray elephants and no non-gray ones. This would be an instance of an abductive inference. It suggests that the best way to distinguish between induction and abduction is this: both are ampliative, meaning that the conclusion goes beyond what is (logically) contained in the premises (which is why they are non-necessary inferences), but in abduction there is an implicit or explicit appeal to explanatory considerations, whereas in induction there is not; in induction, there is only an appeal to observed frequencies or statistics. (I emphasize “only,” because in abduction there may also be an appeal to frequencies or statistics, as the example about the elephants exhibits.)
Updated Jul, 03 2020