The challenge of content moderation is almost as old as the internet itself.
Naturally, the liberal realm of the internet is difficult to censor with regard to harmful, offensive, or illegal content. As a result, content moderation has had to grapple with the moral and ethical dynamics of censorship and freedom of speech while creating a safe environment for internet users.
While the legal and ethical dynamics of content moderation are often under intense scrutiny, there is a general consensus that some forms of content should be prevented from being published, especially when many websites are not subject to strict age controls.
Facebook has unsurprisingly spearheaded content moderation practices. To date, Facebook employs hundreds of thousands of human content moderators who sift through user and AI-flagged content, assessing whether or not it should be posted.
In 2019, Facebook stated they now remove some 80% of content before users report it, compared to just 24% in 2017. In addition, AIs and machine learning algorithms are now adept at analyzing written content, images, video, GIFs, and even emoji usage.
Meanwhile, content moderation as a job and practice has come under fire for questionable working conditions. Facebook content moderators report PTSD and other mental health issues due to being repeatedly exposed to traumatic, harmful, and distressing content.
Training proactive content moderation algorithms lower the burden on human content moderators. While some forms of content moderation are highly sensitive to local and cultural concepts and ideas, most highly traumatic content is culturally immutable and can be proactively moderated or triaged and pre-censored before passing to human teams.
Advertisers are now harnessing content moderation algorithms to reduce the risk of placing online adverts. Advert placements need to discriminate between legitimate and credible website and webpage content and potentially harmful or defamatory material. Placing adverts next to harmful content is a risk and reputation management issue.
To mitigate this risk, AI-assisted content moderation uses NLP and other parsing methods to check webpage content.
Once vetted, the advertiser can place their advert without risk of association with harmful content. This doesn’t just apply to webpage content, but social media pages, YouTube channels, and practically anywhere else on the Google Display Network, Adsense, Facebook ads, etc.
Aya Data works with advertisers to secure optimal ad placements with minimal risk. Our content moderation services are fully attentive to ethical practices - we never risk our staff’s exposure to traumatic content. Through NLP parsing, it’s possible to proactively screen content for risky content at scale.
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