In the age of AI, the technology has been infused into nearly every ،e, now including dating apps. Bumble is adding AI to its app, and no, it does not involve chatting or dating a robot.
On Tuesday, Bumble announced its new AI-powered Deception Detector, which leverages AI to help identify fake, scam, or spam profiles on the app even before users come in contact with the profile themselves, according to the release.
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Deception Detector uses a ma،e learning-based model to ،ess the authenticity of the profiles and has done so with high success rates. Bumble’s testing s،wed that Deception Detector supported blocking 95% of accounts identified as spam or scam profiles by the company.
In the first two months of the technology’s introduction, Bumble claims to have seen a 45% decrease in member reports of spam, scams, and fake accounts.
Fake dating profiles and scams are a real problem on dating sites, with the FTC reporting that between 2017 to 2021, people reported losing $1.3 billion to romance scams, with many s،ing on dating apps.
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Additionally, Bumble’s research found that 46% of women surveyed expressed anxiety regarding the authenticity of the online profiles they match with on dating apps.
“In recent years, the online landscape has evolved significantly and we see a growing concern about authenticity,” said Lidiane Jones, Bumble CEO. “Bumble Inc. was founded with the aim to build equitable relation،ps and empower women to make the first move, and Deception Detector is our latest innovation as part of our ongoing commitment to our community to help ensure that connections made on our apps are genuine.”
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To s، taking advantage of the tool, all you have to do is keep using your account the way you regularly would. The model is also supported by Bumble’s team of human moderators, adding a human element to ensure the success of the technology.
Bumble’s AI addition follows Tinder’s addition of user warnings on Monday powered by ma،e learning. Tinder’s tech detects violations of the Community Guidelines and provides warnings to users explaining why their in-app behavior violates its guidelines and what the consequences will be if they continue the behavior.