What's Inductive Reasoning, and Why Is It Important?
We all use inductive reasoning to draw conclusions on a daily basis. This means that we rely on past observations and experiences to support our current or future beliefs.
For example, if we notice the sky is cloudy, we will conclude that we should go out with an umbrella because it’s almost certain to rain. Or we have the conviction that the bus will arrive at the station at a certain time in the morning because it has always done so.
Likewise, inductive reasoning has been very useful for the empirical sciences. Thanks to the repeated observation of particular phenomena, laws or general principles have been formulated. Having said this, we will delve into what this form of reasoning consists of and why it’s so important in our lives.
What’s inductive reasoning?
Induction is a type of reasoning whose premises support the conclusion, but do not guarantee it. In inductive argumentation, the premises arise from experience or observation of particular cases, and, from them, a general conclusion is drawn.
A typical example of inductive reasoning is the following:
- Premise: All crows observed so far have been black.
- Conclusion: All crows are black.
In this case, the conclusion will never have absolute support from the premises (as in the case of deductive arguments), since there will always be a small probability that it is falsifiable. Following the previous example, it will always still be probable that a crow of another color may appear.
In this sense, we cannot speak of valid or invalid reasoning when it comes induction, but of strong or weak reasoning depending on the degree of probability of the conclusions.
An inductive argument will be strong when it’s highly improbable that its conclusion is false and its premises are true. Conversely, it will be weak if it is highly probable that the conclusion is falsifiable by the appearance of another case that does not meet the set standards.
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The characteristics of inductive reasoning
Inductive arguments or reasoning are characterized by the following:
- Being comprehensive: This implies that the conclusion provides more information than that contained in the premises, by making general inferences about the unobserved.
- Being fallible: This is because the conclusions are never definitive.
- You can’t validate it: Conclusions are based on probabilities and cannot be qualified as valid or invalid.
The problem with induction
In the 18th century, the empiricist philosopher David Hume proposed a famous argument against the inductive method, known as the problem of induction. This reflects the lack of justification or logical foundation existing in inductive inferences.
For Hume, inductive reasoning implies a logical leap or an inferential gap. This is because the premises support the conclusion only in a more or less probable way. It’s never definitive.
Thus, Hume concluded that there’s no way to justify the causal relation in inductive inferences. After all, the fact of observing that an event is repeated in time, in the same way, does not necessarily imply that it will always happen that way.
For example, when one event follows another repeatedly, most people think that there’s a connection between the two, such that the first causes the second to happen. If we kick a ball and it always shoots off in a certain direction, we will conclude that the ball will move to another point every time we hit it with our foot.
However, Hume argued that even if we perceive the succession between two events (in this case, the act of kicking the ball and its displacement), it’s impossible to establish some necessary and sufficient condition between the two. Therefore, he declared that the relation of causality is a product of human imagination and consists of little more than the hope that certain events will occur after others that precede them.
Therefore, we can be sure that the sun will rise every morning because it has always done so. However, this inductive inference will not be based on an objective principle of causality, but on our imaginative ability to establish relationships between events.
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The importance of inductive reasoning
Despite Hume’s observation about the inductive method, we must recognize the usefulness of this reasoning in everyday life. In the sciences, as well.
Thanks to inferences of this type, we can make decisions. Furthermore, we can also draw immediate conclusions. They might have a certain margin of error, but are indispensable for our functionality. It also is for our daily development and survival.
It would be counterproductive for human beings to know all the particular cases or possible scenarios in order to be able to act or make decisions. In fact, our common sense draws conclusions from the always limited information of experience.
And when it comes to new evidence, previous knowledge modifies as it presents itself. This is what mental flexibility consists of.
The same applies in the scientific field. Not all knowledge obtained by empirical sciences is 100% infallible, especially facts concerning new or recently discovered phenomena.
It’s quite common to see how the scientific community updates its postulates, given new evidence. When it comes to unknown phenomena, there’s no more effective way to determine their truth.
Let’s take a recent example. The knowledge we have so far about COVID-19 has arisen from the study of particular cases: those infected. At the beginning of the pandemic, the scientific community concluded a series of postulates. Then, these were modified with the arrival of new evidence.
Inductive reasoning is extremely useful for daily life and the development of science. Although it has its flaws, it’s essential for understanding the world around us and acting accordingly.It might interest you...