DeepAI

Heuristics

What Are Heuristics?

A heuristic is, simply put, a shortcut. Heuristics are strategies often used to find a solution that is not perfect, but is within an acceptable degree of accuracy for the needs of the process. In computing, heuristics are especially useful when finding an optimal solution to a problem is impractical because of slow speed or processing power limitations.

Example of a Heuristic

Let’s a take a look at a familiar example of a heuristic that people use to reduce cognitive load -- calculating the tip for a meal at a restaurant. Imagine a dinner for two that comes to a total of \$17.38. On the receipt the tax is itemized as \$1.75. A common sales tax rate is between 8% and 10%, depending on where you live. To quickly calculate a 20% tip, you could simply double the tax and leave a \$3.50 tip.

You’ll technically be leaving a 20.14% tip, which is a bit of an overshot, but if you’re a generous soul, this gets you close enough, and you don’t have to do long division in your head.

Heuristic Limitations and Cautions

In the example above, the heuristic we used was based on some consistent context (the fact that sales tax happens to be between around 10%). You should be wary when taking this heuristic into new territory where your assumptions may not be accurate. For example, if you went out to dinner in Saskatechewan, Canada where the provincial sales tax rate it 6%, and applied this heuristic, you may find yourself with a very dissatisfied waiter. The point is, heuristics are great when the assumptions you’ve based your heuristic are sufficiently consistent.