Andrew Badham 2023-07-11 15:07:14

Making sense is a crucial part of any argument. If you’re listening to someone’s advice and the pieces of their logical puzzle don’t match up, that’s probably a good sign that their ideas are misguided. However, just because something makes sense doesn’t mean it is true. When we believe things are true just because it makes sense, we are effectively using deductive reasoning.

Deductive vs Inductive Reasoning

There are two ways we can make sense of information, through deduction or induction.

Deductive reasoning draws conclusions based on general principles, rules, or premises. If the premises are true and the reasoning is valid, then the conclusion must also be true.

For example, let's say we know that all mammals are warm-blooded, and a dog is a mammal. Using deductive reasoning, we can conclude that the dog is warm-blooded. The conclusion is based on the general principle that all mammals are warm-blooded, and we're applying it specifically to the dog.

Inductive reasoning makes generalizations or conclusions based on specific observations or evidence. It takes data and uses it to come up with a bigger picture.

For example, let's say you've seen several cats, and all of them have tails. Using inductive reasoning, you might conclude that all cats have tails. It's not a 100% certain conclusion, but based on the cats you've observed, it's likely to be true.

Both of these approaches seem to make sense, so what’s the problem with deductive reasoning?

Unexpected Complexity

Earlier we said that if your premises are true, your conclusion would be true. You might already be able to see the problem here. What if the premise wasn’t true? Or what if it was only partly true?

If we look at our earlier example of “all mammals are warm-blooded”, we might think that this is a very safe premise, but what if they’re not all warm blooded? As it turns out there are some mammals that are not purely warm blooded, such as the arctic ground squirrel. They are what’s known as heterothermic, which—to be honest—I didn’t know was a thing until, I researched this article. And that is the point I am trying to make, there is often complexity we are unaware of.

Does the Data Back it Up?

Let’s look at another example. We know that playing video games increases dopamine levels. We also know that dopamine reinforces behaviour. Therefore, if you play violent video games, it will reinforce violent behaviour. That makes sense, right? Except, we just don’t see that in the data. If that idea were true, we would expect to see more violence in populations that play lots of violent video games… but we don’t. So, while the idea seems plausible, it doesn’t appear to be true.

What’s the Red Flag?

So, what’s the red flag that we are looking for? If you are listening to a thought leader, influencer, or colleague, listen to what information they provide. Is it the rules, principles, or mechanisms only, or do they also provide the results?

For example, if a colleague said, “Plants don’t want to be eaten, so they create chemicals to poison the animals that eat them.” You might think to yourself, that’s an interesting idea but what is the outcome data? Do people who eat more plants die sooner than those who don’t? The answer is no, populations that eat more plants live longer.

So, is deductive reasoning bad? No, this type of logic points us in the right direction to start investigating, but we can’t assume something is true just because it makes sense. We need to check the data and see whether it backs up our ideas. We also need to challenge our premises to see if we are making any assumptions.