The Algorithm Problem Solving Approach in Psychology

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When solving a problem, choosing the right approach is often the key to arriving at the best solution. In psychology, one of these problem-solving approaches is known as an algorithm. While often thought of purely as a mathematical term, the same type of process can be followed in psychology to find the correct answer when solving a problem or making a decision.

What Is an Algorithm in Psychology?

An algorithm is a defined set of step-by-step procedures that provides the correct answer to a particular problem. By following the instructions correctly, you are guaranteed to arrive at the right answer.

An algorithm is often expressed in the form of a graph, where a square represents each step. Arrows then branch off from each step to point to possible directions that you may take to solve the problem. In some cases, you must follow a particular set of steps to solve the problem. In other instances, you might be able to follow different paths that will all lead to the same solution.

This article discusses how algorithms are used as an approach to problem-solving. It also covers how psychologists compare this approach to other ways to solve problems.

Examples of Algorithms

There are many different examples of how algorithms can be used in daily life. Some common ones include:

  • A recipe for cooking a particular dish
  • The method a search engine uses to find information on the internet
  • Instructions for how to assemble a bicycle
  • Instructions for how to solve a Rubik's cube
  • A process to determine what type of treatment is most appropriate for certain types of mental health conditions

Reasons to Use Algorithms in Psychology

The upside of using an algorithm to solve a problem or make a decision is that yields the best possible answer every time. There are situations where using an algorithm can be the best approach:

  • When accuracy is crucial: This is useful in situations when accuracy is critical or where similar problems need to be frequently solved. In many cases, computer programs can be designed to speed up this process. Data then needs to be placed in the system so that the algorithm can be executed to come up with the correct solution.
  • When each decision needs to follow the same process: Such step-by-step approaches can be useful in situations where each decision must be made following the same process. Because the process follows a prescribed procedure, you can be sure that you will reach the correct answer each time.

Potential Pitfalls When Using Algorithms

The downside of using an algorithm to solve the problem is that this process tends to be very time-consuming. So if you face a situation where a decision needs to be made very quickly, you might be better off using a different problem-solving strategy.

For example, an emergency room doctor making a decision about how to treat a patient could use an algorithm approach. However, this would be very time-consuming and treatment needs to be implemented quickly. In this instance, the doctor would instead rely on their expertise and past experiences to very quickly choose what they feel is the right treatment approach.


Algorithms can be a great problem-solving choice when the answer needs to be 100% accurate or when each decision needs to follow the same process. A different approach might be needed if speed is the primary concern.

Algorithms vs. Heuristics

In psychology, algorithms are frequently contrasted with heuristics. Both can be useful when problem-solving, but it is important to understand the differences between them.

What Is a Heuristic?

A heuristic is a mental shortcut that allows people to quickly make judgments and solve problems.

These mental shortcuts are typically informed by our past experiences and allow us to act quickly. However, heuristics are really more of a rule-of-thumb; they don't always guarantee a correct solution.

So how do you determine when to use a heuristic and when to use an algorithm? When problem-solving, deciding which method to use depends on the need for either accuracy or speed.

When to Use an Algorithm

If complete accuracy is required, it is best to use an algorithm. By using an algorithm, accuracy is increased and potential mistakes are minimized.

If you are working in a situation where you absolutely need the correct or best possible answer, your best bet is to use an algorithm. When you are solving problems for your math homework, you don't want to risk your grade on a guess.

By following an algorithm, you can ensure that you will arrive at the correct answer to each problem.

When to Use a Heuristic

On the other hand, if time is an issue, then it may be best to use a heuristic. Mistakes may occur, but this approach allows for speedy decisions when time is of the essence.

Heuristics are more commonly used in everyday situations, such as figuring out the best route to get from point A to point B. While you could use an algorithm to map out every possible route and determine which one would be the fastest, that would be a very time-consuming process. Instead, your best option would be to use a route that you know has worked well in the past.

A Word From Verywell

Psychologists who study problem-solving have described two main processes that people utilize to reach conclusions: algorithms and heuristics. Knowing which approach to use is important because these two methods can vary in terms of speed and accuracy.

While each situation is unique, you may want to use an algorithm when being accurate is the primary concern. But if time is of the essence, then an algorithm is likely not the best choice.

2 Sources
Verywell Mind uses only high-quality sources, including peer-reviewed studies, to support the facts within our articles. Read our editorial process to learn more about how we fact-check and keep our content accurate, reliable, and trustworthy.
  1. Lang JM, Ford JD, Fitzgerald MM. An algorithm for determining use of trauma-focused cognitive-behavioral therapy. Psychotherapy (Chic). 2010;47(4):554-69. doi:10.1037/a0021184

  2. Bobadilla-Suarez S, Love BC. Fast or frugal, but not both: decision heuristics under time pressure. J Exp Psychol Learn Mem Cogn. 2018;44(1):24-33. doi:10.1037/xlm0000419

By Kendra Cherry
Kendra Cherry, MS, is the author of the "Everything Psychology Book (2nd Edition)" and has written thousands of articles on diverse psychology topics. Kendra holds a Master of Science degree in education from Boise State University with a primary research interest in educational psychology and a Bachelor of Science in psychology from Idaho State University with additional coursework in substance use and case management.