Facebook now deploys AI to combat offensive photos

Facebook’s artificial intelligence systems now report more offensive photos than humans do, marking a major milestone in the social network’s battle against abuse, the company says.

AI could quarantine obscene content before it ever hurts the psyches of real people.

The success of Facebook in ads has fueled investments into the science of AI and machine vision that could give it an advantage in stopping offensive content. Creating a civil place to share without the fear of bullying is critical to getting users to post their personal content that draws in friends’ attention.

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Twitter has been widely criticized for failing to adequately prevent or respond to claims of harassment on its platform, and last year former CEO, Dick Costolo admitted “We suck at dealing with abuse.” Twitter has yet to turn a profit, and doesn’t have the resources to match Facebook’s investments in AI, but has still been making a valiant effort.

To fuel the fight, Twitter acquired a visual intelligence startup called Madbits, and Whetlab, an AI neural networks startup. Together, their AI can identify offensive images, and only incorrectly flagged harmless images just 7 per cent of the time as of a year ago, according to Wired. This reduces the number of humans needed to do the tough job, though Twitter still requires a human to give the go-ahead before it suspends an account for offensive images.

When malicious users upload something offensive to torment or disturb people, it traditionally has to be seen and flagged by at least one human, either a user or paid worker. These offensive posts that violate Facebook’s or Twitter’s terms of service can include content that is hate speech, threatening or pornographic; incites violence; or contains nudity or graphic or gratuitous violence.

For example, a bully, jilted ex-lover, stalker, terrorist or troll could post offensive photos to someone’s wall, a Group, Event or the feed. They might upload revenge porn, disgusting gory images or sexist or racist memes. By the time someone flags the content as offensive so Facebook reviews it and might take it down, the damage is partially done.

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