"Algorithm" is a word that is often thrown around. What are we talking about when we build conversations around YouTube or Facebook algorithms? What are algorithms and why do people complain so much about them?
Algorithms are Problem Solving Instructions
We live in a world where computers are only vaguely understood, even though they permeate every moment of our lives. However, there is an area of computer science in which everyone can understand the basics of the action. This area of computer science is called programming.
Programming is not a glamorous job, but it is the foundation of all computer software, from Microsoft Office to robocallers. And even if your programming knowledge comes solely from the bad 90s movies and unconventional news stories, you probably do not need anyone to explain what a programmer does. A programmer writes code for a computer, and the computer follows the instructions of that code to perform tasks or solve problems.
In the world of computer science, an algorithm is just a fancy word for code. Any instruction that tells a computer how to solve problems is an algorithm, even though the task is very simple. When you turn on your computer, follow the instructions to turn it on. That's an algorithm at work. If a NASA computer uses raw radio wave data to render a photo from outer space, this is also an algorithm.
The word "algorithm" can be used to describe any instruction set, even outside the data center. For example, your method of sorting cutlery in a drawer is an algorithm, as is your method of washing your hands after using the bathroom.
But here's the thing: Nowadays, the word "algorithm" is rather reserved for some very special technical conversations. You do not hear people talking about algorithms of "basic math" or "MS Paint Graffiti Tool". Instead, you can hear Instagram users complaining about friendly suggestion algorithms or privacy groups bombarding Facebook's data collection algorithms.
If "algorithm" is a term for computational instructions, why use it almost exclusively to describe confusing, magical, and evil aspects of the digital world?
Most people use "algorithms" and "machine learning" interchangeably.
In the past, programmers and pop culture have called most computer instructions "code" for the most part. Machine learning is the large, cloudy area of computing that uses the word "algorithm" instead of "code." This has understandably contributed to confusion and discomfort associated with the word "algorithm".
Machine learning results in this It's been a long time, but only in the last 15 years has it become a big part of the digital world. While machine learning sounds like a complicated idea, it's pretty easy to understand. Programmers can not write and test code specific to each situation, so they write code that can write itself.
Think of it as a more practical form of artificial intelligence. If you've rated enough emails from your boss as spam, your email client will automatically move all of your boss's emails into the spam folder. Similarly, Google uses machine learning to ensure that YouTube's search results remain relevant, and Amazon uses machine learning to suggest which products you should buy.
Of course, machine learning is not all right. The name "machine learning" sounds so scary that some people feel uncomfortable, and some of the common applications of machine learning are ethically questionable. The algorithms that Facebook uses for data mining or users on the Internet are a less than flattering example of machine learning.
In the press, you hear the Google algorithm for ranking search results, the "YouTube algorithm" for the recommendation of videos and "Facebook algorithm" to decide which posts are displayed in your timeline. These are all issues and debates.
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Why Algorithms Are Controversial  Long Division is (among many others) a well-known algorithm for dividing numbers. It is done only by students instead of computers. Your Intel CPU uses a very different algorithm when dividing numbers, but the results are the same.
Voice output generally uses machine learning, but no one talks about the speech-to-text algorithm, because there is one objectively correct answer that anyone can instantly recognize. Nobody cares how "the computer finds out what you said or whether it's machine learning or not. It only matters to us if the machine has received the correct answer.
However, other machine learning applications do not have the advantage of having a "correct" answer. For this reason, algorithms in the media are a regular subject of entertainment.
An algorithm for alphabetically sorting a list is just one way to accomplish a defined task. But an algorithm such as Google for "the best sites for a search" or YouTube for "the best video recommend" is much less clear and does not fulfill a defined task. People can debate whether this algorithm will deliver the desired results, and people will have different opinions on it. However, in our alphabetical sorting example, everyone can agree that the list will end up sorting alphabetically as desired. There is no controversy.
How should we use the word "algorithm?" use
? Algorithms are the basis of all software. Without algorithms, you would not have a phone or a computer, and you would probably read this article on a piece of paper (in fact, you would not even read it).
But the general public does not do it The word "algorithm" should not be used as a term for computer code. In fact, most people assume that there is a difference between a computer code and an algorithm – but this is not the case. Because of the compound of the word "algorithm" with machine learning, the meaning of the term has become "foggy", but its use has become more specific.
Should you start with the word "algorithm" to describe even the most insignificant parts of computer code? Probably not, because not everyone understands what you mean. The language always changes and it always changes for a good reason. People need a word to describe the confusing, opaque and sometimes dubious world of machine learning, and "algorithm" becomes that word – for now.
In saying this, it is good to keep in mind an algorithm (and a machine) learning) is essentially a bunch of code 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