Twitch launches artificial intelligence tool

Twitch has released a tool that uses machine learning to detect users trying to rejoin chat channels that have been banned for abusive behavior.

The game-focused livestream website said “bad actors” often created new accounts to continue harassing people.

But the new system would warn streamers and chat moderators if a user was a “probable” or “possible” ban evader.

It is part of Twitch’s long-term efforts to reduce hate and bullying.

Hate speech
The company has been criticized for “hate forays”, in which unscrupulous streamers send their followers or even automated bots to other channels to harass someone.

Often the victims belong to minority or marginalized groups.

The creators had demanded that the Amazon-owned company do more to counter this type of hate speech.

In September, Twitch announced a “verified phone chat,” which allows streamers to require that some or all users verify a phone number before chatting.

And the same month, it took legal action against unidentified users allegedly involved in “chat-based attacks against marginalized streamers.”

Final call
The new suspicious user detection system is “powered by machine learning” and uses “a series of account signals” to detect ban evaders, Twitch said.

“Machine learning” describes computer systems that, in effect, “learn from experience.”

The new system will be enabled by default, but moderators and creators can adjust its settings or disable it.

It compares a number of factors, including the behavior and account characteristics of users attempting to join a chat channel, with those of banned accounts, Twitch said, and singles out suspected ban evaders in two ways:

likely: in which case your chat messages will be blockedpossible: in which case your messages will continue to appear
“No machine learning will be 100% accurate,” Twitch said, so the chat moderators would make the “final call,” but the tool will “learn from the actions you take, and the accuracy of your predictions should improve over time.” .

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