The False Dilemma

The Fallacy of Presumption can take many forms. One common example is the false dilemma. This fallacy is also known as the false binary or false dichotomy. As its name indicates, the false dilemma divides a scenario into only two alternatives. When the situation calls for a yes/no answer, that works fine. But in many situations, things are more complex. Thus the false dilemma tricks you into choosing between two imprecise, inaccurate or otherwise flawed options.

You’re Either with Us or You’re a Terrorist

The false dilemma is fairly common. For example, “you’re either with us, or you’re against us,” presents a rigid, binary look at life. This attitude can then be used in all kinds of political debates to tar one’s opponents. “If you don’t want to donate to this charity, then you don’t care about the poor.” Or how about this one: “If you don’t vote for this proposition, then you must not care about the environment.” Isn’t it possible that there are other alternatives out there?

Things Aren’t Always Black or White

Of course in reality, most things are more complex. You care about the poor, but you don’t have any spare change. Or you prefer a different charity. You care about the environment, but you also care about your gas bill. The false dilemma oversimplifies, leading to improper conclusions. To avoid this fallacy, start by asking the question: are there really only two options here? If you can think of other likely options, then you’re probably facing a false dilemma.

Challenge the Assumptions

Rootclaim’s analyses start with a set of hypotheses meant to represent the most likely possibilities. But we realize that you may disagree. That’s what makes this a crowd-based effort. You can strengthen the analysis by suggesting an alternative hypothesis. When implemented on a large scale, the end product is a more reliable analysis.

Weighing the Choices

The false dilemma sees things in absolutes. But real life is less clear-cut. A Rootclaim analysis assigns probabilities for each piece of evidence given each hypothesis. For example, consider the case where Doug is found lying in a pool of blood in his kitchen. It is tempting to assume that the blood proves conclusively that Doug was stabbed to death by his neighbor Mark. But there are alternative explanations that, while less likely, are still possible. It may be 99% likely that there would be blood on the floor if Mark stabbed Doug. But it could also be 20% likely that Doug stabbed himself, or that his wife Jane did it. By embracing the nuances of multiple competing possibilities, Rootclaim avoids falling into the trap of false dilemmas.

The Rootclaim Way

It is easy to fall for false dilemmas. But life rarely consists of simple yes or no choices, and reality is rarely black and white. Rootclaim helps to cut through the gray. Our robust algorithm considers multiple hypotheses simultaneously. And the fact that the inputs are crowdsourced means that every idea, detail, figure and source faces scrutiny—including making sure that each story considers the full range of possible explanations. For a more reliable analysis, follow the Rootclaim method.