AI Voice Scan

Vocal scams commonly used.

AI Voice Scam, an example of some of the dangers involved.  

They Thought Loved Ones Were Calling for Help. It Was an AI Scam  By The Washington Post, March 14, 2023

In 2022, impostor scams were the second-most-popular racket in America, according to data from the Federal Trade Commission.

Technology is making it easier and cheaper for bad actors to mimic voices, convincing people, often the elderly, that their loved ones are in distress.

Credit: Elena Lacey/The Washington Post

More sophisticated artificial intelligence (AI) tools are being used to replicate a person's voice.

Fraudsters increasingly are using such tools for impostor scams, which often target the elderly, making them believe loved ones are in trouble and in need of quick cash.

University of California, Berkeley's Hany Farid said AI voice-generating software can recreate the pitch, timbre, and individual sounds of a person's voice using a short audio sample.

Said Farid, "If you have a Facebook page ... or if you've recorded a TikTok and your voice is in there for 30 seconds, people can clone your voice."

Software from the startup ElevenLabs, for example, allows users to turn a short audio sample into a synthetically generated voice using a text-to-speech tool. The software is free or costs $5 to $330 per month, depending on the amount of audio generated.

From The Washington Post

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Pentagon Hacks Itself

A former employer of mine tests a by now classic approach.  Note aiming at AI efforts here in particular.  

The Pentagon Is Bolstering Its AI Systems—by Hacking Itself

By Wired, July 21, 2021

Intelligence as a way to outfox, outmaneuver, and dominate future adversaries. But the brittle nature of AI means that without due care, the technology could perhaps hand enemies a new way to attack.

The Joint Artificial Intelligence Center, created by the Pentagon to help the US military make use of AI, recently formed a unit to collect, vet, and distribute open source and industry machine learning models to groups across the Department of Defense. Part of that effort points to a key challenge with using AI for military ends. A machine learning "red team," known as the Test and Evaluation Group, will probe pretrained models for weaknesses. Another cybersecurity team examines AI code and data for hidden vulnerabilities.

Machine learning, the technique behind modern AI, represents a fundamentally different, often more powerful, way to write computer code. Instead of writing rules for a machine to follow, machine learning generates its own rules by learning from data. The trouble is, this learning process, along with artifacts or errors in the training data, can cause AI models to behave in strange or unpredictable ways.

"For some applications, machine learning software is just a bajillion times better than traditional software," says Gregory Allen, director of strategy and policy at the JAIC. But, he adds, machine learning "also breaks in different ways than traditional software."

From Wired     View Full Article