Today, YouTube is a major source of entertainment and one of the most popular social sites. You can view, create, upload and download all kinds of content. YouTube Premium has over 2 billion active users and over 30 million subscribers. With services available in over 100 countries, it is important to ensure that the platform is a safe place for everyone. With a huge amount of compelling content and features uploaded to YouTube, AI and machine learning become a very useful weapon for a platform like YouTube to streamline its cycles and operations. The launch of COVID-19 has generally increased YouTube’s reliance on AI, as the platform’s employees are not allowed to work from home for security reasons.
Some of the ways YouTube uses AI and machine learning include:
Automatic removal of malicious and fake content.
Social platforms such as YouTube, Facebook and Twitter have been tackling fake news and offensive content for half a decade. YouTube has used artificial intelligence algorithms to block such hateful content.
In the first quarter of this year, YouTube appeared to focus more on AI and machine learning to remove around 11 million videos from its platform. More than 75% of content was automatically identified and removed, and about 70% of videos containing harmful content were removed before they were viewed. According to YouTube’s latest report on the implementation of the EU guidelines, this is the highest number of videos it has successfully removed in a single quarter, the second quarter of 2020. Of the 11.4 million records removed in the middle of the second quarter, about 10.8 million were removed by AI researchers.
Violence, spam, misinformation and child safety were the main reasons why these videos were removed from the platform. According to the report, 1.9 channels/shows were also removed because they contained more than 90% spam and misleading content.
Forward function and new effects for videos
The path to video sharing has always been accessible, but it was a complex process. Google‘s AI researchers have developed a neural algorithm that can bring backgrounds to videos without special equipment. The researchers prepared the algorithm with carefully labeled images, which allowed the algorithm to learn patterns, resulting in a fast system capable of tracking videos.
If you’ve used YouTube’s “Up Next” feature, you’ll know that this is a feature of the platform that simulates artificial intelligence. As YouTube’s database is constantly changing, with users uploading videos every minute, YouTube also needed AI to drive its recommendation mechanism so that it doesn’t look like Netflix or Spotify. It needs to be able to handle constant recommendations, as users are constantly adding new content.
Maintaining age restrictions
YouTube recently announced the availability of advanced artificial intelligence to ensure that content created specifically for an adult audience is not shown to young people. Since its inception, YouTube has featured apps for children under the age of 13, and the platform’s advertised content has age barriers that include accessible radical content. In 2017, the platform introduced machine learning technology to remove these videos. The platform is currently looking to introduce a similar innovation to decide which content is only suitable for an adult/adult audience.
These are all amazing ways YouTube is using artificial intelligence and machine learning to streamline various processes and tasks.