What’s inductive logic?

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Inductive logic draws probable conclusions from premises or observations, but is open to biases and incorrect conclusions. A strong argument has a high probability, but even strong arguments can be flawed due to biases, illogical conclusions, and uncertainty. It is important to examine each premise for potential bias and illogicality, and to determine the probability of the conclusion based on the strength and quantity of the premises. Inductive logic can only lead to a fully educated guess, not undeniable truth.

Inductive logic is a form of reasoning that uses premises or observations to draw a probable conclusion. Unlike deductive logic, which guarantees the truth of a conclusion based on incontrovertible evidence, inductive logic can at most suggest that a conclusion is highly probable based on the premises. Since inductive reasoning is open to somewhat general and non-specific premises, the possibility of biases and incorrect conclusions is often quite high. However, inductive logic is often used to argue for everything from purchasing decisions to legislation, as it is much easier to construct than deductive arguments.

For a statement to be considered inductive, it must have one or more premises that lead to a conclusion. For example, the premises used to arrive at the conclusion “more people drink cow’s milk than goat’s milk” might include “grocery stores carry a greater volume of cow’s milk than goat’s milk” or “there are more dairies that have cows than goats”. While these claims may not be able to conclusively prove that more people are drinking cow’s milk, they make the claim more likely to be true. If an inductive conclusion has a high degree of probability, it is called a strong argument; a conclusion with a low degree of probability is considered a weak argument.

Even a strong inductive argument can be flawed; biases, illogical conclusions, and the simple fact of uncertainty can lead to an incorrect conclusion despite strong premises. Bias occurs when a person making or assessing the likelihood of an argument gives extra weight or discounts certain premises based on external circumstances, such as personal experience. If, for example, a person has been bitten by a poodle, they may believe that all poodles are evil and are less likely to adopt one. Illogical conclusions can occur when all the premises are objectively true, but the conclusion drawn from them does not follow logically; for example, while “all poodles are dogs” may be true, it does not logically follow that “all dogs are poodles.”

Inductive logic’s greatest vulnerability is its inherent uncertainty. Even with strong premises and a logical conclusion, an inductive argument always has the possibility of being false. Horse racing handicapped regularly experience this problem, as even a heavily favored horse with a perfect record and a poor field of opponents can have a bad race and finish last, regardless of the perceived probability of winning. The vulnerability of inductive arguments is also of paramount importance in courtrooms, as few cases provide only deductive and unambiguous evidence.

Because the world is full of uncertainties and differing interpretations, many people come across inductive reasoning when making decisions. When attempting to determine the validity of inductive logic, it is important to examine each premise for potential bias, illogicality, and specificity. If the premises can reasonably be judged to be unbiased and logical, then it is necessary to see whether the conclusion is a logical assumption from the evidence. Finding the conclusion to be logical, it is therefore important to determine how probable the conclusion is, based on the strength and quantity of the premises. Even after all of this scrutiny, it’s important to remember that inductive logic can only lead to a fully educated guess, and never to the ultimate, undeniable truth.




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