Month: May 2026

Tech giants sued for using voice samples to train artificial intelligence without consent. Google is facing a new lawsuit under the Biometric Information Privacy Act (BIPA), in which the company is accused of training voice AI models using biometric voice samples from journalists, investigative podcasters, and audiobook narrators.

The lawsuit was filed by seven plaintiffs who allege that Google created its core models based on thousands of hours of recorded speech to extract biometric voice samples. These models were used to power products such as Gemini Live, NotebookLM Audio Overviews, YouTube automatic dubbing, Google Cloud Text-to-Speech, and Google Assistant.

The plaintiffs include award-winning radio journalists Carol Marin and Philip Rogers, investigative podcasters Yohance Lacour, Alison Flowers and Robin Amer, and audiobook narrators Lindsey Dorcus and Victoria Nassif.

Separate but related class action lawsuits filed by the same group of defendants also target Amazon, Apple Inc., Meta Platforms, Microsoft, NVIDIA, ElevenLabs, Adobe, and Samsung Electronics.

According to the allegations, these companies built commercial AI-based voice systems using voice samples collected from the internet and other sources without obtaining written consent, providing notice, or publishing biometric retention policies required by BIPA.

The BIPA deems biometric identifiers to be “biologically unique to an individual,” meaning that once they are disclosed or misused, they cannot be easily replaced or invalidated by an individual.



https://www.biometricupdate.com/202605/tech-giants-sued-under-bipa-over-voiceprints-used-to-train-ai

According to Biometric Update, facial images on T-shirts can be subject to counterfeiting. T-shirts have become a threat to facial recognition, but a new study shows how to prevent it!

Discussions about biometric attacks typically focus on financial fraud attempts, but the increasing use of facial recognition in public places has prompted researchers to develop ways to trick the technology into bypassing security or surveillance. One method that has proven effective in controlled experiments involves images of attackers on T-shirts. The latest development in this field involves replacing images with face-presentation attacks: a T-shirt with a printed human face is presented to the camera, fooling the facial recognition system into believing it’s seeing a real, three-dimensional face.

A new paper by a group of researchers at the University of Applied Sciences in Germany presents a way to prevent these very facial attacks.

The researchers tested 3 widely used open-source face detection algorithms: RetinaFace, MTCNN, and dlib, against the T-shirt Face Presentation Attack (TFPA) database. The database contains over 1,600 images from 100 different T-shirts, each with a face printed on it.

8 people wore T-shirts with their faces printed on them in various poses, and their images were captured using a RealSense D435 camera, capable of capturing depth information in 3D images.

In almost all cases, the facial detection algorithms detected the face on the T-shirt. The average estimated detection rate of the three algorithms exceeded 99% for all eight poses, according to the results. The study also found that if the attacker concealed the face by covering it with hands, wearing a face mask, or tilting the head, the facial biometric system would likely return a match to the T-shirt—meaning the attack would be successful.

The success of this presentation attack is concerning because T-shirts are easy to create. They can also be concealed under a jacket, making them easier to use under surveillance than something conspicuous, such as a paper mask. T-shirt attacks have already been identified by border authorities as a potential threat.

To address this issue, the researchers expanded the database to include 152 authentic presentations and proposed a new detection method. According to the research results, the proposed algorithm can be easily combined with traditional presentation attack detection algorithms.

Text based on https://www.biometricupdate.com/202605/t-shirts-have-become-a-facial-recognition-threat-a-new-study-shows-how-to-stop-it