Reasoning, in its most fundamental sense, is the process by which we take bits of information and knowledge that we already have, and compare or combine them to generate new knowledge. It describes our ability to move from what we know to what we don’t know.

We do this by drawing conclusions from a set of premises – things we already know (or believe) to be true. The way we combine the premises to produce a conclusion is called an argument. The goal is to construct a sound argument so that we draw conclusions in such a way that they are guaranteed – or at least very likely – to be true. We want to come to the right conclusions, but this can be tricky.

In the first place, you have to make sure that all of the premises you use as your starting point are solid. This means getting your facts straight, examining your assumptions, and making sure you have all the information you need. It’s a bit like putting together furniture – if you want to build something decent, you have to make sure that you have all the right parts, that none are missing or broken.

If you don’t have all the components in order, the finished product won’t be sound. It may end up just collapsing on itself.

But even starting with all the right pieces isn’t, in itself, a guarantee. You have to put them together in exactly the right way, so that all the pieces fit. Only then can you be sure that the finished product is strong.

Luckily, just like furniture, reasoning comes with instructions. There are rules for how to put your premises together to build a strong conclusion. Discovering these rules and demonstrating how and why they work is the task of logic.

The first and most important thing to understand is how we go about drawing conclusions from premises. Professional logicians (a.k.a. your philosophy professors) generally break down this process into two different types of reasoning: inductive and deductive.

Inductive reasoning looks at a set of premises and draws conclusions based on what they suggest is probably true. Often, this takes the form of using lots of examples to derive an overall principle for how something works. For instance, if Bradley Cooper, Ryan Gosling, David Beckham, and Michael Fassbender all look good with beards, looking at those examples might lead one to conclude: Men look good with beards. That conclusion fits all of the evidence we have so far; nothing we’ve seen would lead us to disbelieve it. It’s not guaranteed to be true, but based on the evidence, it seems like it’s probably true. And if it’s the case that men look good with beards (as the evidence suggests), then any individual man could surely conclude, “I would look good with a beard.”

Oh, the tragic consequences that often attend errors in reasoning.

The challenge with inductive reasoning is the same challenge faced by all empirical science – all our attempts as human beings to gain objective knowledge by observing the world. Human observations necessarily have a subjective element to them, which makes objective knowledge really tough to come by. There is a limit to how many examples we can examine, how rigorously we can test our conclusions. The examples we have access to may be incomplete or biased, or we may have biases in deciding how to interpret them. If I only look at examples of sexy sexy men, it’s no surprise they all end up looking pretty good with beards. Give Michael Fassbender an eye patch and a hook hand, he’s probably still going to look pretty good.

Of course, if you’re conscientious about trying to eliminate bias, choose your examples very carefully, and look at as many examples as you can, you can achieve a high probability that the conclusions you draw from them will be true. In scientific experiments, everything possible is done to try to eliminate bias. But even the average human (and probably dogs and cats and gerbils as well), in everyday life, uses inductive reasoning all the time to draw practical conclusions about the way the world works. If I’ve seen the sun rise every morning 10,000 days in a row, I don’t need any fancy book-learning to convince me that the sun will come up tomorrow, and the next day, and all the days after that. I can predict that the sun will come up every day, and it’s extremely likely that it will.

If I doesn’t, I’ve got big problems, because I also didn’t need a supply-filled doomsday bunker 10,000 days in a row….

Sigmund Freud (famous for his psychoanalytic theories and infamous for his misogyny) observed that this ability to reason is present from our earliest days of consciousness. Even a baby in his crib learns, after dropping a toy a few times, that when he cries his parents will come over to retrieve the toy and stop his squalling. It doesn’t take long before babies start tossing out their toys on purpose, because they know almost every time their parents will come running.

So while inductive reasoning isn’t foolproof, it’s a useful tool for generating expectations about the world that we need in order to function. We just have to be aware of its limitations.

But isn’t there a more clear-cut, reliable way to reason? Can’t I get an upgrade?

Enter Reasoning 2.0: deduction. Deductive reasoning is designed to draw conclusions in a much stricter way than inductive reasoning. A conclusion arrived at through deduction is the necessary result of combining the available premises. The premises can’t produce any other conclusion.

Let’s return to our beard example. When our hapless hair-grower looked at the evidence and drew his conclusion, “Men look good with beards,” he used inductive reasoning. But then he took another step. He reasoned, “All men look good with beards. I am a man. Therefore, I must look good with a beard.” This is classic example of deductive reasoning, called a syllogism. It uses two premises that connect through the term they share in common, and then connects them to the inescapable conclusion. It’s kind of like saying A=B, and B=C, so A=C.

If, in fact, “All men look good with beards,” then any individual man must look good with a beard. That conclusion isn’t dependent on observations, or evidence. It’s necessarily true based on the way my premises fit together. Unlike inductive reasoning, deductive reasoning always produces conclusions that are true by necessity.

Of course, this doesn’t mean it’s foolproof. In the first place, you have to make sure your argument is well-constructed. Let’s go back to that drawer you were building (you have to finish it sometime). You look at your materials and realize *gasp* you’re missing one of those essential 16 cylindrical pegs that were packaged loose in a giant bag of random stuff you had to sort through, and went rolling off to the corners of the room at the first opportunity. You need something to fit into that proverbial round hole, but you don’t have the right piece to hand, so maybe you try to find something else that kinda fits – there always seems to be a square peg lying around. You might be able to jam it in there, but is it really going to hold the pieces together if it doesn’t fit properly?

Deductive reasoning can only produce conclusions that are necessarily true if the premises are combined in the right way, if they really do fit together seamlessly. In logic, this is referred to as validity. Luckily, logicians have come up with a whole set of rules to help us put together valid arguments. Unluckily, those of us who aren’t logicians still need to apply those rules properly, and sometimes that’s not easy.

And there’s another thing that can get messed up when using deductive reasoning: the relationship between logical form (how the argument is put together) and content (what the argument says).

The rules that logic provides for how to put together a valid argument deal with just that – how to put premises together to produce conclusions. Just like a drawer can be put together the same way, whether it’s made of pine, oak, mahogany, or styrofoam, logic tells us how to put premises together to build conclusions, no matter what topic the premises and conclusions actually deal with. This attribute is called topic neutrality. Validity is a about form, not content, so the rules that govern validity apply regardless of content.

Our familiar example of deductive reasoning demonstrates a particular form. “All men look good with beards. I am a man. Therefore, I will look good with a beard.” This takes a general rule about all individuals of a certain type, and then applies it to a particular individual of a certain type. But I can apply that same form to information about any type of thing. The topic of the statements doesn’t matter (men, honey badgers, whatever); what matters is the relationship between the premises, based on the type of information they give.

Since logical form is independent of the content of your argument, the same rules always apply, so you can use the rules of logic to help you make a strong argument, no matter what your topic.

But topic neutrality can be a curse as well as a gift – it means that playing by the rules will give me conclusions that are valid, but not necessarily conclusions that are true. Truth depends on content. If I start with premises that are or might be false, then any conclusion I draw on the basis of those premises can be false, even if I’ve reasoned logically.

Ultimately, it’s essential to understand the principles of logic, but it’s equally important to use critical thinking skills to test and evaluate the information you use to help you draw conclusions. These two things in combination will not only allow you to write a kick-ass research-based argument, hold your own in a debate, and ace the LSAT, they will also allow you to make better judgments and decisions every day of your life.

For more info on how to use logic, check out my series on logical fallacies.

Works Consulted
Béziau, Jean-Yves, ed. “Deductive and Inductive Arguments.” Internet Encyclopedia of Philosophy. Web. Accessed 12 Oct., 2016.
Lau, Joe, and Jonathan Chan. “What is Logic?”. Critical Thinking Web. University of Hong Kong, 2016. Web. Accessed 13 Oct., 2016.