Inferences are essentially conclusion, drawn from evidence or information. The process of making inferences is an important one in the philosophy of reasoning, and of course in intelligence analysis where your goal is to take disparate information and, after analysis, render conclusions.
There are three types of inferences: inductive, deductive, and abductive.
Inductive reasoning is the opposite of deductive reasoning. In inductive reasoning, we have a set of true premises, that allows us to make a prediction about a general situation.
For example, if a friend’s dog has never bit us when we have visited before, we can assume they will not bite us this visit
Deductive reasoning is a form of reasoning that moves from the general to the specific, as in the scientific method. This is a very mechanical form of reasoning that is common in TECHINT (technical intelligence.) A simple example of deductive reasoning is as follows:
- All mammals have hair
- A human is a mammal
- Therefore all humans have hair
In philosophy, inductive reasoning is expressed by turning these items into letters like you might see in algebra.
- All M have H
- U is M
- Therefore all U have H
It’s important to recognize the validity of a statement (such as All M have H) is different from the truthfulness of the statement. A statement can be logical and valid but not correct, if your premises are wrong (such as you think all mammals have hair and you find out you are not correct.)
Abductive reasoning is perhaps the most relevant to intelligence analysts. In this form of reasoning, you take an incomplete data set, or another situation where you do not have all the facts to be perfectly certain and you form an “educated guess” about that situation.
Tools like the Analysis of Competing Hypothesis can help you perform this kind of reasoning correctly.