The underlying API used to determine "toxicity" scores phrases like "I am a gay black woman" as 87 percent toxicity, and phrases like "I am a man" as the least toxic. To broadly determine what is and isn't toxic, Disqus uses the Perspective API--software from Alphabet's Jigsaw division that plugs into its system. Pasting her "Dear white people" into Perspective's API got a score of 61 percent toxicity. It's possible that the tool is seeking out comments with terms like black, gay, and woman as high potential for being abusive or negative, but that would make Perspective an expensive, overkill wrapper for the equivalent of using Command-F to demonize words that some people might find upsetting.
They say the data will boost efforts to train software to understand and police online harassment. The collaborators have already used the data to train machine-learning algorithms that rival crowdsourced workers at spotting personal attacks. When they ran it through the full collection of 63 million discussion posts made by Wikipedia editors, they found that only around one in 10 attacks had resulted in action by moderators. Wikimedia Foundation made reducing harassment among Wikipedia editors a priority last year.
And Russian app FindFace lets you match a photograph you've taken of someone to their social media profile on the country's popular social media platform Vkontakte. Carl Gohringer, founder and director at Allevate, a facial recognition firm that works with law enforcement, intelligence and government agencies, says: "The amount of media - such as videos and photos - available to us as individuals, organisations and businesses, and to intelligence and law enforcement agencies, is staggering. But Ruth Boardman, data privacy specialist at international law firm Bird & Bird, says individual rights still vary from one EU state to another. And the automation of security vetting decisions based on facial recognition tech raises serious privacy issues.
Question: can AI vision systems from Microsoft and Google, which are available for free to anybody, identify NSFW (not safe for work, nudity) images? Can this identification be used to automatically censor images by blacking out or blurring NSFW areas of the image? Method: I spent a few hours creating in some rough code in Microsoft office to find files on my computer and send them to Google Vision and Microsoft Vision so they could be analysed. I spent a few hours over the weekend just knocking some very rough code. Yes, they did reasonably well at (a) identifying images that could need censoring and (b) identifying where on the image things should be blocked out.