The interaction between people and social media through machine learning and AI algorithms poses a challenge. Despite the widespread coverage of news articles and events influenced by social media, a continuous echo chamber grows due to machine learning algorithms developed by some of the most prominent corporations globally. These algorithms are utilized to exhibit user-generated content through advertisements. Facebook, for instance, had 1.35 billion monthly active users in September 2014 and is predicted to earn 9 billion in global Facebook advertising revenue in 2015 (Duffett, 2015). This predicament has adversely impacted the general public and the billions of individuals who use apps like Facebook, Instagram, and Twitter, creating walls around the content only an individual can see. One probable cause of this issue is the malicious intent of marketing and monetization targeting specific groups of people. A possible solution to this problem could involve conducting a study to investigate how these algorithms operate and why they are precise across several groups of people.