They are the secret, invisible helpers in the background without whom nothing would work in the digital world: algorithms. Almost everything we see on the internet has been created by algorithms. And we are often aware of this, for example when searching the web or on social media platforms. But we rarely know how they work.

The many algorithms that accompany us on our forays through the internet always remain in the background. We don't have to activate them and we don't receive a notification that they have just completed a task for us. As soon as we switch on the computer, an algorithm runs that meticulously controls the start-up process.

Streaming services such as Spotify or Netflix use algorithms to suggest new songs and series that we have never heard of or seen before. And yet they often fit amazingly well with what we have previously consumed on these platforms. This demonstrates one of the great strengths of algorithms: recognising patterns in large data sets.

The algorithms create personalised taste patterns from the music we have listened to and the series we have watched, which they then compare with the entire database. What matches the recognised pattern is then recommended to the user. We often only realise how well this works when it no longer works as usual. If you try out a new service, for example, you first have to train the algorithm so that it suggests convincing titles.

Even in our physical world, algorithms are constant problem solvers and diligent task processors. Modern assistance systems in cars ensure that we automatically stay on track, enjoy a pleasant climate and the navigation system guides us safely to our destination even in the event of an unforeseen road closure.

There are algorithms for all this and much more.

How do algorithms work?

We now know that without algorithms, we would not be able to do many things the way we are used to. These hard-working helpers carry out simple to highly complex tasks without complaint. Regardless of their complexity, algorithms have a number of fundamental characteristics that make them work:

Unambiguity: Every step of the algorithm must be clear and unambiguous. Ambiguity would lead to confusion about what to do next.

Executability: Each step must be practically feasible and must not encounter insurmountable obstacles.

Finiteness: An algorithm consists of a finite number of steps. This means that it leads to a clear result or fulfils a defined task.

Input: An algorithm requires an input to solve the task. This can be data, information or variables that are relevant for the algorithm.

Output: The algorithm generates output as a result. This can be, for example, the solution to a problem or a specific result.

Efficiency: A good algorithm should work efficiently, i.e. solve the task with a minimum of time and resources.

Repeatability: If the same algorithm is executed several times with the same inputs, it should deliver the same result each time.