Algorithms of the Modern World


Algorithms have essentially taken over the world as we know it today. Algorithms keep track of any data and information on many individuals to provide a more accessible picture of their life. These algorithms cover various topics, including sports, business, education, and what people watch on the internet. The algorithms do this while retaining the world's current social and ethical concerns and avoiding any skewed viewpoints or flaws in themselves to appeal to a broad audience.


Explain how algorithms are being used in different types of workplace environments.

In sports, algorithms are utilized to manage players using statistical data. These algorithms play a dominating role in determining which players to employ, train, or decline to meet the team's game requirements. Complex camera systems catch the player's key highlights, while algorithms retain this data through wearable devices put on the athlete even during training. A coach for a football team, for example, might utilize these recordings and the data analysis to determine the more beneficial striker, defender, or player for a specific soccer game, to maximize the winning chances for his team. 

The majority of the success in the corporate sector is based on algorithms. In the corporate world, algorithms are used to improve customer service and streamline internal operations. Streaming services such as Netflix, for example, use algorithms to propose movies and shows to customers based on their preferences. This information includes things like a person's favorite genre or which movie or series they prefer. E-commerce is another example of a business algorithm in action. In these businesses, algorithms change the price of a product based on the popularity of goods in a customer's shopping basket. The algorithm still has problems in terms of social and ethical concerns in the commercial sector. Other algorithms are utilized by large businesses like Google, Amazon, and Facebook to employ individuals. 

These algorithms can aid in the selection of the top candidates for available positions. They accomplish this by reducing the amount of traffic generated by unsatisfactory applications. They may do this by administering assessments such as cognitive tests, or they may ask the candidate to input specific details to determine which candidate performed the best and fits the company's goals. For example, one of Google's application exams requires candidates to take a personality test to find the best-fit candidates. The personality test gathers information about a person's characteristics to decide who is the best candidate for the job. Algorithms also look into the field of education. 

The Australian Curriculum, Assessment, and Reporting Authority (ACARA) is a marking and grading system for various tests conducted all over Australia. As schools get more complex and diverse within their educational system, they are overcrowded with students. Such overcrowdedness is creating a hassle for teachers to mark every test a student does, specifically, writing, which has no laid out or directed marking criteria. That is why many algorithms over the years have been implemented in various schools around Australia schools. These algorithms are used in a machine learning process, as it is trained by more than 1000 maybe even more marked NAPLAN papers or papers from such tests. Such human-marked essays help the algorithm understand what to look for in an over or underachieving essay.


Explain the social and ethical issues associated with using algorithms in different workplace environments.

The algorithm's primary social and ethical concern in the sporting industry is accepting players for a team. While an algorithm selects players for a team, the algorithm tends to look out for what a player can do to win the game. An algorithm does not look at what the player brings to the team or their attitude towards certain team members. In many professional-level leagues, a game is won by serious chemistry between teammates. If the algorithm chooses a player, but the player does not get along with their teammates, the chances of winning the game become very narrow, no matter how good that player will be. On the other hand, if a player who gets along with their teammates instantly is chosen, the winning chances are maximized no matter how sound the player is. 

Nevertheless, sports algorithms are essential for managing and evaluating individual player performance to maximize winning for that particular team. The major social and economic flaw in the corporate sector starts with marketers requiring to know information about whom they want to sell their products to, and this can be a complicated issue because users may not want to share their data with third-party marketers or sources. These privacy concerns are due to predictive algorithms already storing data about us from our daily searches to our daily viewing history, and this is why many ads that show up before us are about a product we want soon or have been trying to gain in the recent past. 

Netflix is a provided example of such algorithms in action. If a person is interested in a specific genre, Netflix will use their previous viewing history to recommend additional shows which revolve around that genre. Though such algorithms are not all negative, the consumer can also profit from such algorithms. For example, if a consumer was seeking a specific product on the internet, an perfectly calculated and placed advertisement could assist them in locating it. In addition to this example, have you ever noticed that you search for a particular product and start getting advertisements all about that specific product you were trying to locate? 

Excellent internet services (Google, Facebook, Twitter, and Instagram) have been chastised for using algorithms to promote products online by exploiting the privacy of the billions of web users today. This example exhibits the negative effect of algorithms, but this also reveals that it is not the algorithm exploiting the user's data, but it is the maker of the algorithm manipulating it to make a profit for themselves. Recruiting algorithms have been demonstrated to be influential in hiring the correct number of individuals and selecting suitable personalities. 

However, there have been concerns about the recruiting algorithms, which are racially discriminatory. This is quite important, as race should have no bearing on our ability to obtain employment. Many tolerant applicants have also been refused employment because of the recruiting algorithm. For example, a real estate company's algorithm rejected four ideal applicants because they did not match the personality and appearance criteria included in the algorithm's database. 

The major social and ethical issue is that algorithms in the education system can analyze and grade an essay based on its structure; however, the algorithm cannot access the essay based on the concept or the topic that the essay revolves around. The ACARA algorithm, for example, can not comprehend the consistency and leniency of human markers. 

Such algorithms will award the text a good grade if it is structurally sound and matches the structure that has been recorded in the algorithm's database. For example, if a student has written a C-grade essay, but it matches and comprehends with essays in the algorithm's database, they usually tend to be marked up. However, taking an A-grade student who has written an essay regarding the topic with creativity and not in a structure that comprehends the structure that is in the algorithm; tend to be marked down. Such marking down shows that algorithms avoid the subject entirely, relying on structural patterns to label the results, not the creativity and the originality that many students across Australia bring to their writing.


Finally, as computer technology gracefully advances, algorithms help to drive these changes by making routine activities more efficient and accessible. The sporting world, the business world, marketing, and the education industry are just a few industries that use algorithms for their benefit across the world. Algorithms also serve a variety of objectives and improve workplaces. However, this should not be accomplished by replacing human jobs but rather by assisting such employment and the people who work in them. These algorithms are not perfect, and they do make mistakes now and again, but they help increase efficiency in various industries and occupations.


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