On any platform, creators and marketers find themselves spending effort to conquer “the algorithm”: A mythical creature lauded for complexities that only the platform’s developers understand. People are advised to study this monster and adhere to its arbitrary rules at all times. However, this monster is a farce. Somewhat… In the context of content creation, algorithms can determine whether your content provides value to other people. While there are many ways to interpret this statement, the most important takeaway is that algorithms are influential in your success. Since resources (such as money and time) are limited, we must be efficient with them. This leaves one question for us to answer: Which factors of the algorithm are the most important?

What is an Algorithm?

The definition of an algorithm is a set of rules or calculations to follow. Let’s use an example for a more practical explanation: Imagine that you want to give “scores” to pet owners (in order to find the best pet owners). Instead of visiting each owner and assigning a score randomly, you can create an algorithm that uses dogs and cats to determine the OWNER’s score.

score = dogs + cats

If you were biased towards dogs, you could weight this algorithm to make dogs worth more than cats.

score = dogs * 1.25 + cats * .5

where each dog would count 25% more and each cat 50% less.

You can even use an if-statement where you do or don’t give points IF certain criteria is met.

if (cats > 10) { score = 0 } else { score = dogs + cats }

In this case, if you own more than 10 cats your score is 0. As a result, the “best pet owner” — who maintains the highest score (value) — would be someone with 10 cats and an unlimited number of dogs.

Every platform that suggests content or provides sorted functionality uses algorithms based on these simple concepts. However, many more variables and metrics may be used — such as saves or streams — instead of cats and dogs. In any case, the goal of an algorithm usually matches the goal of its creators. In a capitalistic environment, companies create algorithms in order to indirectly increase company profits. This can be done by directly creating algorithms that perform specific tasks efficiently (i.e increase the amount of ads viewers watch). Beyond these basics, “anything is possible”.

Artificial Intelligence in Algorithms

Machine Learning is a subfield of Artificial Intelligence that involves statistical models to analyze patterns. Algorithms based on Artificial Intelligence — or more specifically Machine Learning — use models (from existing and real-time data) to create the ‘score’ (value) described above. This is done by identifying key metrics (statistics) from an input (such as a piece of content) and feeding the metrics into a system (the algorithm) which finds a pattern (model) in relation to the content’s output (results). An application (that runs the algorithm) can learn in a similar manner to a human through the implementation of a neural network; by comparing previous results to new results and improving the algorithm to become better at its main goal.

Artificial Intelligence objectively analyzes information in a more efficient manner than humans. This is because AI is able to recognize patterns in datasets and find correlations that humans wouldn’t be able to find easily. When you visit a doctor, the diagnosis you receive is based on the sum of the experiences and information the doctor has acquired. In contrast, an AI’s diagnosis is based on the sum of every input and output it has been fed in addition to training time; which is likely much more extensive compared to a human. As an example, medical algorithms that use Artificial Intelligence can accurately predict whether someone has a disease based on a number of metrics (such as BMI, Blood Pressure, etc). This allows doctors to gain better insight into a patient’s problem and avoid costly procedures that may not be necessary.

Artificial Intelligence can be wrong and biased; just as their creators are. It’s important to understand that being better at analyzing information is not an equivalent to being correct. In a similar manner to a human, an AI is only as good as the inputs and outputs it’s based on. Decisions based on incorrect or insufficient data are guaranteed to be faulty. In other words, flawed and biased data will result in flawed and biased decision-making. This is why we can’t rely on Artificial Intelligence to solve all of our problems. Do you remember when Amazon scrapped its AI recruiting tool due to its bias against women?

Since an algorithm based on Artificial Intelligence finds its own patterns, it’s possible for the indirect creators of the algorithm — who directly work on the AI learning mechanism itself — to have no understanding of how the algorithm actually works. In other words, while people are able to speculate how the “brain” of an AI is working, there is no hard-set formula of the algorithm it creates. Instead, an algorithm is “constantly changing” over time to become better at a given objective (i.e suggesting content to viewers).

Personalization in Algorithms

Personalization is the action of designing or producing something to meet someone’s individual requirements. In the case of an algorithm, these “individual requirements” usually refer to a person’s preferences (on social media or advertising or otherwise). Understanding the concept of personalization is important because algorithms that are personalized can’t be studied using a single individual. Stop wasting your time doing so. An easy way to determine whether an algorithm uses personalization is by checking whether your feed is different from others.

Is artificial intelligence required to implement personalization? No. However, the basis of personalization lies on the factors that you value the most; which is different for everyone. In other words, artificial intelligence can be used to make personalization more efficient. As a reminder, an AI is only as good as the data it’s based upon. This is another reason your personal data is valuable.

Which Factors Are Important?

Not every platform uses artificial intelligence in their algorithms, but many popular ones do. The advent of advertising and social media has led to an increased demand for personalization; in addition to humans being naturally drawn to factors that resemble themselves. Understanding these concepts will help you identify the type of algorithm you are dealing with to determine the factors you should focus on. However, you must remember that algorithms are simply a means to achieving a goal of a person or company. As a result, it may be more beneficial to stop spending time “figuring out what the algorithm does” and more time on its intentions.