People around the world watch over 1 billion hours of YouTube videos every day everything from cat videos to videos for cats. AI algorithm shapes the information billions of people consume, and YouTube has controls that purport to allow people to adjust what it shows them. The YouTube algorithm offers up a diverse array of videos that it thinks that person might like to watch. YouTube's recommendation engine for a better user experience. YouTube takes time for a post to build huge numbers of views and signal to the algorithm that it's worth promoting.
YouTube's algorithm has changed over the years and how it works today. Youtube Algorithm changes enacted in early 2019, for example, have reduced consumption of borderline content by 70%. Youtube's search algorithm relies on the keywords you use in your video's metadata to decide what your video is about. YouTube needs data to base the recommendations on and there's no data without people watching your videos. YouTube has said in previous work describing its artificial intelligence algorithm that users like fresher content, all else being equal.
Researchers found that YouTube's controls have a negligible effect on the recommendations participants received. YouTube recommended it more than 650 times among the 696,468 suggestions. Researchers' report raises center on recommendations for potentially traumatizing content. YouTube wants to recommend things people will like, and the clearest signal of that is whether other people like them. YouTube has its struggles, like all platforms, with this gap between the rule they have written and their enforcement.
YouTube began measuring viewer satisfaction directly with user surveys as well as prioritizing direct response metrics like Shares, Likes, and Dislikes. YouTube working on collecting more satisfaction metrics and providing them to creators in their analytics. YouTube's algorithm also uses different signals and metrics to rank and recommend videos on each section of its platform. YouTube's AI is powerful enough to offer users tools to shape the content they see.
The YouTube algorithm is the AI recommendation system that decides which videos YouTube suggests to those 2 billion-plus human users. Users have little power to keep unwanted videos including compilations of car crashes, live streams from war zones, and hate speech out of their recommendations. When suggesting videos for people to watch next, YouTube employs slightly different considerations.
The YouTube platform has also repeatedly come under fire for promoting sexually explicit or suggestive videos of children pushing content that violated its own policies to virality. The research report doesn't take into account how YouTube's algorithm actually works. But that is something no one outside of YouTube really knows, given the algorithm's billions of inputs and the company's limited transparency. Researcher says the platform should allow people to proactively train the algorithm by excluding keywords and types of content from their recommended videos.
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