Although it has not been the word of the year, because the pandemic cancels everything, we use the word “algorithm” more and more in our jobs, in our leisure, in our lives. The algorithms they seem to control what we see, what we read, what we buy, even the friends we have. Algorithms are omnipresent and omnipotent. The word algorithm is a strong candidate to be the word of the 21st century, but do we know what an algorithm is?

## Definition and origin of the word

The Royal Academy of the Spanish Language (RAE) define algorithm in its first meaning as “ordered and finite set of operations that allows to find the solution of a problem”. Its origin, according to the RAE itself, perhaps comes from late Latin *algobarismus*, and this in turn from classical Arabic *ḥisabu lḡubār*, which means “calculation using Arabic numerals”.

Other sources, however, suggest that its origin comes from the Latinization of the name of Al-Juarismi, Persian mathematician, astronomer and geographer, considered one of the great mathematicians in history, who presented the first systematic solution of linear and quadratic equations.

If we reflect on this definition, we can conclude that we continually apply algorithms in our day to day.

And so it is. To give a few examples, we have surely assembled, or helped to assemble, a piece of furniture from that well-known Swedish company based on a more or less long, but finite, set of instructions. From a lot of pieces placed in rectangular boxes we can have a chest of drawers, a wardrobe or a sofa. Surely we have also surprised someone with a delicious dessert created from a list of ingredients and following the orderly sequence of steps that are included in the recipe.

While these examples fit the definition, the word algorithm is more often associated with mathematics and computer science. Let’s take a brief look at what algorithms are like in these two disciplines.

## Algorithms in mathematics

Although we probably don’t remember it, the first time we are faced with algorithms in mathematics is in elementary school. In these courses, teachers teach something as basic and common in life as adding, subtracting, multiplying and dividing. Actually, doing these operations is applying the algorithms that allow us, from some input numbers, to obtain an output result. In subtraction, for example, from the minuend and the subtrahend, applying a series of steps, we obtain the difference between both values, which is what we call subtraction.

In general, given a mathematical problem with a solution, we know that there does not have to be a single set of steps to solve it, but that there may be several different ways of doing it, that is, several algorithms.

Continuing with the example of subtraction, when they have carried, we can apply several algorithms to arrive at the solution. For those of us who went to EGB, it used to be the algorithm by compensation (better known as “I take one”) and for the younger ones, the algorithm by grouping. Sometimes this diversity of algorithms leads parents to despair when trying to help their children with their homework, but the reality is that the important thing is that each one applies the algorithm that best suits their way of reasoning.

Of course, as our knowledge of mathematics increases, we learn more elaborate algorithms that provide solutions to more complex problems.

## Algorithms in computing

Algorithms in programming are basic. A computer program is nothing more than a sequence of instructions for a computer to perform a certain task, based on input values. Typically, this task is used to solve a problem. Therefore, what we are doing is that the computer implements an algorithm so that, from a finite number of instructions, it obtains a solution. We can, therefore, get a computer to subtract two numbers by programming one of the algorithms that allow us to do a subtraction.

## machine learning

In general, algorithms can be classified according to the type of problems they solve. There are search, ordering, data compression, graphics, cryptographic and machine learning, among others.

machine learning or *machine learning* They are the ones that have attracted the most attention in recent years. These algorithms have the particular characteristic of being able to learn from data. Thus, they make predictions that allow us to make decisions automatically, without being established or decided. *a priori*.

The term *machine learning* it was already coined in 1959. However, what has caused these algorithms to be on the rise in recent years is that now is when we have enough data that allows us to train them to be used with significant results.

There are already algorithms that give us recommendations on what to see, what to read, what to buy, which friends to follow on social networks based on the content we usually consume and the tastes of people who consume content similar to ours. Although they tend to be right, thus reinforcing the proper functioning of the algorithm, let us not forget that they can cause the well-known effect of information bubbles or echo chambers.

Although it seems that these algorithms control our lives and that they can be dangerous due to the biases that have been shown to have, let us not forget that they are programmed, trained and validated by people and, therefore, we are the people who consciously have to know what to expect from them, what decisions we let them make for us, regulating their development so that respect equity criteria, without being discriminatory.

Perhaps the future will bring us things unimaginable today, but for now we should not fear algorithms, but rather give them the value they have to help us solve complex problems. Much more so when they can be trained and run on machines with high computing power.

sky blue field, Professor of the Department of Telematics Engineering, *Charles III University*

This article was originally published on The Conversation. read the original.

Reference-www.eleconomista.com.mx

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