Google's YouTube will soon hire more than 10,000 staff in an attempt to weed out extremist content.
The YouTube CEO also stated that the company had developed a "computer-learning" technology capable of weeding out radical content on the platform, where hundreds of minutes of videos are uploaded each minute.
Several advertisers, included Mars Inc., Adidas and Diageo, said they would pull their campaigns off YouTube in the aftermath, fearing the videos would attract pedophiles, according to the Wall Street Journal. The company said its new efforts to protect children from risky and abusive content and block hate speech on the site were modeled after the company's ongoing work to fight violent extremist content. Further, he noted that increased members would help YouTube fulfill the task better, and avoid inaccurate demonetizations, thus, giving creators more stability on the revenue front.
Wojcicki added to her statement that, "We will continue the significant growth of our teams into next year, with the goal of bringing the total number of people across Google working to address content that might violate our policies to over 10,000 in 2018".
Earlier this year, advertisers fled the site after ads appeared next to extremist content.
Wojcicki also revealed that 98 per cent of the videos the platform removes for violent extremism are now flagged by its machine-learning algorithm.
YouTube CEO Susan Wojcicki said "some bad actors are exploiting" the Google-owned service to "mislead, manipulate, harass or even harm".
"We believe this requires a new approach to advertising on YouTube, carefully considering which channels and videos are eligible for advertising".
Talking about the machine-learning program, Wojcicki noted that human reviewers are an essential part of removing content and training the machine-learning system because human judgment is significant in making "contextualized" decisions on content.
She said advances in machine learning meant Youtube could take down almost 70 per cent of violent extremist content within eight hours of it being uploaded and almost half of it within two hours.
"Because we have seen these positive results, we have begun training machine-learning technology across other challenging content areas, including child safety and hate speech", she said.