Student sample for assessment
Written by a Year 9 student in Bayswater, Victoria, Australia.
When you open social media, the content you see is not randomly selected. An algorithm—a set of rules a computer follows to perform a task—decides what appears. These rules are designed to predict what will interest you based on your previous activity. Your likes, comments, shares and time spent on posts all feed into the algorithm. The goal is to keep you engaged. This sounds neutral, but the mechanics are important: platforms want you to spend as much time as possible on their sites because more time means more advertising revenue. This is how the algorithm serves the platform's financial interest, not necessarily yours. When algorithms show you content based on what they predict you will like, they create something called a filter bubble. This means the algorithm consistently shows you content that matches your existing views and interests. If you watch videos about a topic, the algorithm learns this preference and shows you more similar content. If you follow certain people, it recommends more of their views. Over time, this filter bubble narrows your world. You see more of what you already like, and less that challenges you. Another phenomenon is algorithmic amplification. Some content spreads much faster than its quality might justify. If a post generates strong emotional reactions—anger, fear, outrage—the algorithm amplifies it, showing it to more people. This can help important information reach people quickly, but it also means that misinformation spread with emotional appeal can travel rapidly before fact-checking catches up. These mechanics raise real concerns. A filter bubble that only shows you views similar to your own can deepen polarisation. If you only see content that confirms what you already believe, it is harder to understand other perspectives. Algorithmic amplification of emotional content means sensational or misleading information can spread faster than careful, accurate information. This affects how people understand major issues. Because of these concerns, regulators in several countries are now examining whether algorithm design should be subject to legal oversight. They are asking: should platforms have to be transparent about how algorithms work? Should there be rules about what content can be amplified? These are not simple questions, but the stakes are high—algorithms shape not just what we see, but how we understand the world.