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What are algorithms, and why do they make people unpleasant?



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"Algorithm" is a word thrown around a lot. But when we build conversations about YouTube or Facebook algorithms, what are we actually talking about? What are algorithms, and why do people complain so much about them?

Algorithms are instructions for problem solving

We live in a world where computers are only easy to understand, even though they penetrate every moment of our lives. But there is an area for computer science where someone can understand the basics of what happens. The area of ​​computer science is called programming.

Programming is not glamorous work, but it is the basis of all computer software, from Microsoft Office to robokallare. And even if your programming knowledge originates only from bad 90's movies and off-beat news reports, you probably don't need anyone to explain to you what a programmer is doing. A programmer writes code for a computer, and the computer follows the instructions in that code to perform tasks or solve problems.

Well, in the computer science world, an algorithm is just a neat word for code. Every instruction that tells a computer how to solve problems is an algorithm, although the task is super easy. When you turn on the computer, it follows a set of instructions on how to enable. It is an algorithm at work. When a NASA computer uses raw radio data to photograph outer space, it is also an algorithm at work.

The word "algorithm" can be used to describe some sets of instructions, even outside the calculation range. For example, your method of sorting cutlery in a box is an algorithm, as well as your method of washing your hands after using the bathroom.

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But here's the thing: These days, the word "algorithm" tends to be reserved for some very specific technical conversations. You do not hear people talking about "basic math" algorithms or "MS Paint graffiti tool" algorithms. Instead, you hear Instagram users complain of suggestions for algorithms for friend or private groups that base Facebook data collection algorithms.

If "algorithm" is a catchall term for calculation instructions, why do we use it almost exclusively to describe confusing, magical, and the evil aspects of the digital world?

Most people use "Algorithms" and "Machine Learning" interchangeable

Previously, programmers and pop culture referred to most computational instructions as "code". This is still true today for mostly. Machine learning is the large, cloudy area for computers where we usually use the word "algorithm" instead of "code". It has understandably contributed to the confusion and concern surrounding the word "algorithm".

Machine learning has been around for a long time, but it has only become a major part of the digital world for the past 15 years. While machine learning sounds like a complicated idea, it is quite easy to understand. Programmers cannot write and test specific codes for each situation, so they write code that can write themselves.

Think of it as a more practical form of artificial intelligence. If you categorize enough with your manager's emails as spam, your email client will automatically shoving all your manager's emails to the spam folder. Similarly, Google uses machine learning to ensure that the YouTube search results are relevant, and Amazon uses machine learning to suggest which products to buy.

Of course, machine learning is not all good and foolish. The name "machine learning" sounds pretty good enough to make some people unpleasant, and some of the popular uses for machine learning are ethically questionable. The algorithms that Facebook uses for data mines or users on the web are an incredible example of machine learning.

In the press you hear about "Google's algorithm" to rank search results, "YouTube's algorithm" to recommend video clips, and "Facebook's algorithm" to determine which posts you see on your timeline.

The problem with AI: Machines learn things but cannot understand them

Why algorithms are controversial

19659005] Long division is a familiar algorithm (among many others) to divide number. It's just that it's done by school kids instead of computers. Your Intel CPU uses a different algorithm completely when dividing numbers, but the results are the same.

Speech-to-text usually uses machine learning, but no one talks about the speech-to-text algorithm because there is an objectively correct answer every person can immediately recognize. No one cares about "how" the computer shows what you said or whether it is machine learning or not. We only care if the machine has the right answer.

But other applications of machine learning do not have the advantage of having a "right" answer. Therefore, algorithms have become a common conversation in the media.

An algorithm for sorting a list alphabetically is just one way of accomplishing a defined task. However, an algorithm that Google's in some way "ranks the best sites for a search" or YouTube to "recommend the best video" is very vague and does not achieve a defined task. People can discuss whether that algorithm produces the results it should, and people will have different opinions about it. But with our alphabetical sorting example, everyone can agree that the list stops sorting alphabetically as it should. There is no controversy.

How should we use the word "Algorithm?"

Algorithms are the basis of all software. Without algorithms you would not have a phone or computer, and you would carefully read this article on a piece of paper (actually you wouldn't read it at all).

But the public does not use the word "algorithm" as a catchall term for computer code. In fact, most people assume there is a difference between a computer code and an algorithm, but it does not exist. Because of the word "algorithm" association with machine learning, its meaning has become foggy, but its use has become more specific.

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Would you start using the word "algorithm" to describe even the most trivial bits of computer code? Probably not, as not everyone will understand what you mean. The language always changes, and it always changes with good reason. People need a word to describe the confusing, opaque and sometimes dubious world of machine learning, and the "algorithm" becomes that word for now.

As mentioned, it is good to remember that an algorithm (and machine learning) is basically a bunch of code that is written to solve tasks. There is no magic trick; It's just a more complicated iteration of the software we're already familiar with.

Sources: Slate, Wikipedia, GeeksforGeeks


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