Type I and Type II Errors: Without a crystal ball, without perfect information, you often face decisions where no matter what you choose there is a risk of being wrong. And, because of this risk, a valuable tool that you can use for making better decisions is the concept known as Type I and Type II errors.

To explain, a Type I error is a false positive — believing something is true when it’s not. A Type II error is a false negative — believing something is false when it’s actually true. In both cases, you end up wrong. Therefore, the challenge is learning how to choose the least worst option.

For example, let’s start with something simple. You’re halfway to the corner store when dark clouds appear. Do you go back home for an umbrella, or keep walking? If you go back and it doesn’t rain, you’ve made a Type I error — wasting time and energy. But if it does rain, you’ve made a Type II error — failing to prepare, you get soaked.

Now let’s raise the stakes. You’re not feeling well. Do you go to the hospital? If you go and it’s nothing serious, that’s a Type I error — a false positive. You go to the ER and wait. A few exams are ordered, you feel lousy, and it might be expensive. However, if you stay home and it’s serious, that’s a Type II error — a false negative. You thought you just needed some rest, but you actually needed medical help.

Or, imagine you’re tested for cancer. A false positive means you are told that you have cancer when you don’t. It creates anxiety, and possibly unnecessary treatments. On the other hand, a false negative means the test misses cancer that you actually have. This delays treatment, allowing the cancer to spread.

This is similar to a fire alarm. The alarm goes off, but there is no fire. You evacuate and the fire department responds to discover the alarm was triggered by burnt popcorn or cigarette smoke. On the other hand, an alarm that fails to go off is similar to a test that misses cancer. The fire grows and spreads. By the time you discover the fire you are trapped.

Last, consider a difficult dilemma in the justice system, especially when it comes to capital punishment. If you convict an innocent person, that’s a Type I error — a false positive, deciding they are guilty when they’re not. On the other hand, if you acquit a guilty person, that’s a Type II error — a false negative, deciding they are innocent when they’re actually guilty. Both are mistakes, but one is far harder to undo. A guilty person gets away with a crime, is released, and might reoffend. Not good. But an innocent person executed can never be brought back. That’s why many argue that the justice system should lean towards avoiding Type I errors — even if it means some guilty people go free.

Now, while a useful tool for framing decisions, Type I and Type II errors have some limitations. First, they treat choices as simple yes-or-no, when real life often provides additional options. For instance, if it starts raining you might be able to wait under a bus stop or duck into a nearby coffee shop. You don’t necessarily need to either return home for an umbrella or continue to the store. It’s not just yes or no. Second, consequences are often unknown and dynamic. They can change over time. Will it be no rain, light rain for 5-minutes, or a heavy downpour that lasts for hours? You don’t know. Last, they assume each decision happens in a single moment, when in reality, it’s an ongoing process involving multiple decisions, often with chances to wait, test your assumptions, and gather better information.

The bottom line, when framing decisions in terms of Type I or Type II, the real question is not, ‘Are you right or wrong?’ Instead, it’s asking: ‘If you are wrong, which mistake can you live with, which error has the least worst outcomes?