# Abductive Reasoning

## The Basic Idea

The scientific method begins with a hypothesis—an educated guess. After making some sort of observation about the world, scientists come up with a potential explanation, which they put to the test using cleverly-designed experiments. But until there’s data to back them up, hypotheses are just stabs in the dark: they might be accurate, but they also might not be.

The generation of hypotheses relies on a particular kind of logical inference, known as abductive reasoning, abduction, “inference to the best explanation,” or, simply, “hypothesis.” Alongside its sisters, deductive (“top-down”) reasoning and inductive (“bottom-up”) reasoning, abductive reasoning is a core component of the methodology of science, and although it cannot itself be the basis for any sort of conclusions about the world, it represents the crucial first step towards that end.

## History

Abductive reasoning was coined by the American philosopher Charles Sanders Peirce around 1865.1,2 Up until this point, philosophers had divided logical arguments into two subclasses. First, you have deduction, or “necessary inference,” where a specific conclusion follows from a general rule. For example, given the premises “All men are mortal” and  “Socrates is a man,” deductive reasoning leads us to the conclusion that Socrates must be mortal. Deduction results in “necessary” inferences because it is always correct: it’s about taking rules that apply to a wider population and inferring that they also apply to a random sample.2

In contrast, induction is a type of “probable” inference, extrapolating a general rule based on specific examples. For instance, given the premises “Socrates is a man” and “Socrates is mortal,” induction leads us to the generalized conclusion that “All men are mortal.” This process is the inverse of deduction, making an argument about a population based on a smaller sample, which can often lead to incorrect conclusions.

Deduction and induction capture many of the logical arguments that a person can make, but Charles Sanders Peirce noticed that there was a type of argument that didn’t fit into either of these categories. Imagine, for example, that you go out for a walk, and you notice that the grass is wet. As a first premise, you know that when it rains, the grass gets wet; and as a second premise, you know that the grass is currently wet. You might be tempted to argue that, therefore, it must have rained. There’s a strong possibility that this is the case—but it’s also not the only possible explanation for the grass being wet. This could also be because, say, somebody had their sprinkler on earlier. You’ve made an educated guess, but it is not the sole conclusion to be drawn. This “best guess” reasoning is what Peirce called abduction.2

## Consequences

As mentioned above, the most important function of abduction is  as a component of the scientific method. Peirce, as a scientist himself, integrated the three forms of logical argument—deduction, induction, and now abduction—into one comprehensive methodology for seeking the truth: the scientific method.2 After abducting a hypothesis, probably after making some sort of surprising observation, scientists use deduction to help them figure out how to test their theory, coming up with one or more necessary inferences that would have to prove true if the hypothesis were correct. Finally, researchers engage in induction, running an experiment and making a probable inference in order to explain its results.2

## Controversies

When Peirce introduced the concept of abduction, he envisioned it, alongside deduction and induction, as forming a logical trichotomy—a distinct, three-phase approach to a better understanding of reality. He thought of these processes as the basic building blocks of reason, each being irreducible to another. In other words, he thought of them as totally distinct logical operations. However, not all philosophers agree that abduction is its own, unique type of logical reasoning. Instead, some have argued that abductive arguments can actually be broken down into deductive and inductive reasoning.3

## Related TDL content

TDL Perspectives: Becoming an Applied Behavioral Scientist

Applied behavioral science is all about using the scientific method—abduction, deduction, induction—to find evidence-based solutions to the problems plaguing some kind of system. This article goes over the basics of what a career in applied behavioral science looks like.

## Sources

1. Douven, I. (2017). Peirce on abduction. Stanford Encyclopedia of Philosophy. https://plato.stanford.edu/entries/abduction/peirce.html
2. Burch, R. (2001, June 22). Charles Sanders Peirce (Stanford encyclopedia of philosophy). Stanford Encyclopedia of Philosophy. https://plato.stanford.edu/entries/peirce/#dia
3. Kapitan, T. (1992). Peirce and the autonomy of abductive reasoning. Erkenntnis, 37(1), 1-26.

### Dan Pilat

Dan is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. Dan has a background in organizational decision making, with a BComm in Decision & Information Systems from McGill University. He has worked on enterprise-level behavioral architecture at TD Securities and BMO Capital Markets, where he advised management on the implementation of systems processing billions of dollars per week. Driven by an appetite for the latest in technology, Dan created a course on business intelligence and lectured at McGill University, and has applied behavioral science to topics such as augmented and virtual reality.

### Dr. Sekoul Krastev

Sekoul is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. A decision scientist with a PhD in Decision Neuroscience from McGill University, Sekoul's work has been featured in peer-reviewed journals and has been presented at conferences around the world. Sekoul previously advised management on innovation and engagement strategy at The Boston Consulting Group as well as on online media strategy at Google. He has a deep interest in the applications of behavioral science to new technology and has published on these topics in places such as the Huffington Post and Strategy & Business.

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