From Wired:

While these technologies may appear to represent a turning point in the debate around hate speech on the internet, recent research has shown that they are still far from being able to distinguish context or intent.

SOCIAL MEDIA PLATFORMS like Facebook, Twitter, and YouTube have been making significant investments in the development of artificial intelligence to moderate content and automate the removal of harmful posts. These decision­making technologies typically rely on machine-learning techniques and are specific to types of content, such as images, videos, sounds, and written text. Some of these AI systems, developed to measure the “toxicity” of text-based content, make use of natural language processing and sentiment assessment to detect harmful text.

Dennys Antonialli is a privacy law scholar and executive director of InternetLab, an internet law and policy think tank based in São Paulo, Brazil. 07.25.1909:00 AM

I.e., Dennys Antonialli knows who are the Good Guys whose tweets should be promoted and who are the Bad Guys whose tweets should be banned, but the stupid AI tries to decide whether a tweet is Good or Bad based not on who wrote it but on what it says.

If such AI tools are entrusted with the power to police content online, they have the potential to suppress legitimate speech and censor the use of specific words, particularly by vulnerable groups.

At InternetLab, we recently conducted a study focused on Perspective, an AI technology developed by Jigsaw (owned by Google’s parent company, Alphabet). The AI measures the perceived level of “toxicity” of text-based content. Perspec­tive defines “toxic” as “a rude, disrespectful, or unreason­able comment that is likely to make you leave a discussion.” Accordingly, the AI model was trained by asking people to rate internet comments on a scale from “very healthy” to “very toxic.” The level of perceived toxicity indicates the likelihood that a specific comment will be considered toxic.

We used Perspective’s API to compare the perceived levels of toxicity of well-known drag queens and far-right political figures. The study compared the Twitter accounts of all the former participants of RuPaul’s Drag Race with those of far-right leaders such as David Duke, Richard Spencer, Stefan Molyneux, and Faith Goldy. Additionally, we included prom­inent non-LGBTQ Twitter users, including Donald Trump and Michelle Obama. We analyzed over 114,000 tweets posted in English with Perspective’s most recent version.

Our results indicate that a significant number of drag queen Twitter accounts were calculated to have higher perceived levels of toxicity than white nationalist leaders. On average, the toxicity levels of the drag queens’ accounts ranged from 16.68 percent to 37.81 percent, while the white nationalists’ averages spanned from 21.30 percent to 28.87 percent. The toxicity level of President Trump’s Twitter account was 21.84 percent. …

In person, it is easier to understand context and see this as a form of self-expression. But when reading such missives online, it is significantly more challenging to distinguish between harmful and legitimate speech—especially when that assessment is made by machines. These in-group uses were also found in various tweets we analyzed. But in many of those cases, Perspective still deemed the post extremely toxic:

Mayhem Miller



@TheOnlyMayhem

I AM BLACK. I AM GAY. I AM A MAN. I AM A DRAG QUEEN. If those are not enough for you…kindly, F--- OFF!!!

4,568

11:37 AM – Jul 28, 2018

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Level of toxicity: 95.98 percent

… Though the ideas promoted by white nationalist tweets may target vulnerable groups, Perspective’s AI often categorized them as much less toxic than the drag queens’ tweets:

David Duke

@DrDavidDuke

“Italy is a beautiful country and I love it so much, from its food to its fashion, from its history to its arts, but I am very worried about the current trends which are reminding me of the 1930s,”

So let’s import Somalians to change up the food, fashion, history and arts? https://twitter.com/V_of_Europe/status/1070773005205295104 …

Level of toxicity: 7.17 percent