Google is finding all it’s best possible ways to make sure that YouTube content is safe for all brands through the implementation machine learning that better identifies the content which estimated as offensive for the audience and advertisers.
We can observe YouTube transformation from the day it launched to till now. Through the launch of experiments and user intended redesigns in the field of artificial intelligence elevating the best capability of YouTube as the #1 entertaining video platform. By comparing with the past activity of YouTube now, it’s predicting and featuring the user interested content for which the audience is looking for.
YouTube also stated that machines flagged above 83% of now-deleted videos to review rather than humans.
Above three-quarters of videos taken down before they were getting views, and most of them are related to spam or porn.
Without human involvement, artificial intelligence technology lets them train algorithms on data which can be used to spot the objectionable videos and take actions.
Table of Contents
YouTube Recommendation Algorithm
Google Brain drives YouTube recommendations, which is opensource TensorFlow. With the help of this, one can conduct experiments on multiple deep neural network architectures with distributed training.
This system works on two neural networks in that one is a candidate generation in which it takes the audience to watch history and filters videos in hundreds.
For the performance of the recommendation algorithm, Google uses offline metrics and then conducts A/B testing between the best performing algorithms to get the final decision.
The only intention of developing this recommendation algorithm is to serve the audience what they want to watch and improve the long-term engagement of the viewers.
The YouTube recommendation algorithm affects ‘in search results, in trending streams, in notifications, in the recommended streams, in channel subscriptions, and on the YouTube homepage.’
YouTube Spam Video Cleaning and Comments Cleaning
YouTube is cleaning the offensive videos, unsolicited bulk subscriptions, and spam comments on the platform. Due to this, most of the YouTube creators have a rapid drop in subscribers count. YouTube has given a clear and clever explanation about the efforts and effects of it to the creators.
YouTube stated that they verify the legality of YouTube accounts and actions on your channel.
YouTube sorted the most recent posts in removing the comments. The cleaning of spam videos, subscribers, and comments building the fidelity of YouTube towards the audience and creators as well.
Creating Mix Playlists using the User Search Query
Depending on the audience watch history, the YouTube Mix provides playlist automatically.
YouTube Mix Playlists can be created randomly and automatically or by calling the same playlists through bookmark or link.
This never leads to the same video result again. The user can find YouTube Mixes ‘in search results, on music cards, on the home page, and in the suggested sections.’
Cracking Down Extremist Video Content
YouTube cracks down on the extremist videos that promote neo-Nazi, white supremacy, and other types of hate speech.
The expansion of this takedown policy will affect the video content who feature the violent content or hate speech projecting the groups or individual.
The implementation of machine learning technology helps YouTube to identify and delete the offensive extremism and terrorism relevant video content.
By the execution of machine learning technology, YouTube removes 75% of offensive videos before flagged by anyone. The accurate flagging of videos has been observed than compared to a human.
YouTube is making the best use of artificial intelligence to monitor and manage user activity in all possible ways. The above discussed are the unique ways that YouTube implements artificial intelligence that ultimately makes it be as the top user-friendly platform in the world.