I want to talk about YouTube recommendation system. I believe it is a strong AI tool that is worth paying attention to and discussing its pros and cons. This site has an incalculable amount of content and in order to retain its audience, it needs an application that will suggest videos that the user will want to watch – that’s the recommendation system.
What are the advantages of Youtube recommendation system?
The youtube recommendation system offers the user what is popular in their region when they first enter. Gradually as views, likes and subscriptions increase, the suggestions become more personalized and precise. This creates the feeling that Youtube knows the user and can offer them what they want to see, even if they don’t realize their preferences themselves. It definitely saves time in finding interesting videos, which naturally improves the user experience
Also, recommendations increase user engagement. That is, a recommendation system is able to keep users on the platform by offering them content that they will want to watch. Because of this, the total viewing time increases, which is beneficial for the platform and content creators. Engagement is a key metric for the success of videos and channels, as well as for the growth of advertising revenue.
The recommendation system supports content creators, especially new and small creators. If a video is popular among users, it will be offered to a wider audience, which increases reach and chances of success. This helps channels to grow and find their audience and users to get new and interesting channels. This provides a more level playing field for promotion on the platform.
What are the limitations of Youtube recommendation system?
One of the main disadvantages of any recommendation system is the echo chamber effect. Users begin to see only content that matches their actions on youtube. If at the beginning the viewer watched content about cats, and they also like technology, but didn’t watch it, this topic will most likely be ignored. This creates what is known as a “vicious circle” or “echo chamber” effect, where the user only sees highly specialized content that is relevant to their past actions, which is hard to break out of. This narrows access to diverse content and narrows horizons.It can also lead to increased bias by not offering an alternative point of view.
Additionally, algorithms tend to promote content that elicits strong emotional reactions, including extreme and misinforming videos. As algorithms seek to increase engagement, they may inadvertently promote blatantly harmful, dangerous or radical content, as it often generates more views and interactions. There is a risk of content creators becoming dependent on algorithms – this is when authors become algorithm-driven rather than audience-driven in their pursuit of views. This leads to lower quality and monotonous content. Smaller channels that do not conform to algorithm preferences may find it difficult to popularize their content.
Since the key objective of recommendation systems is to increase user engagement, the logical fulfillment of this objective is to create dependency in viewers. This is one of the most popular problems when a person can’t stop and keeps watching videos one after another, even if they originally planned to spend only a few minutes on the platform. Despite being aware of this phenomenon, such companies rarely make changes that could reduce user addiction, as the main goal is audience retention, which brings advertising contracts.
Thus the Youtube recommendation system is a powerful tool that on the one hand makes Youtube user-friendly, but on the other hand can lead to a number of negative consequences. It is important to realize that despite the obvious benefits, Youtube and other platforms should be aware of their responsibility to users and society. Only a balanced approach that takes into account the benefits and risks can ensure a healthy and sustainable development of the Internet space.
