Twitter Trusts AI More Than Its Employees for Content Moderation
JAKARTA - Under the ownership of Elon Musk, Twitter apparently trusts artificial intelligence (AI) more than its employees in terms of moderating content on social media.
This content moderation aims to check tweets of misinformation, hate speech and others. Now, the company is reportedly relying more on AI to moderate content.
The company's vice president of Trust and Security Products Ella Irwin, said the platform eliminates manual review by its employees, and supports restrictions instead of removing some content outright.
"The biggest thing that's changed is the team is fully empowered to move quickly and be as aggressive as possible," Irwin told Reuters.
Since Musk's takeover, hate speech has soared on Twitter, as evidenced by data revealed last week by the Center for Digital Countering (CCDH).
“From a triple increase in racial slurs to a shocking increase in antisemitic and misogynistic tweets, Musk's Twitter has become a safe haven for hate,” CCDH tweeted.
The non-governmental organization added that climate-sceptic tweets had also increased since Musk became Twitter's new CEO.
Another research group, the Network Contagion Research Institute (NCRI) previously found N-word usage increased by nearly 500 percent in the 12 hours following Musk's purchase of Twitter.
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Research has also shown an increase in insults towards gay men and antisemitic postings. However, Musk disputes these claims, and considers them grossly wrong.
Last week, the microblogging platform was also flooded for hours with adult spam content, which it claimed was an attempt to divert news about protests against the widespread COVID-19 lockdown measures across China.
Quoted from The Independent, Tuesday, December 6, Irwin said recently, Twitter will now use automation to more aggressively limit abuse-prone hashtags as well as search results in areas such as child exploitation.
She added that the platform will now automatically delete tweets reported by trusted figures who have a track record of properly tagging such content.