Tech
Study Finds Most People Can No Longer Tell AI-Generated Voices from Real Ones
A new study has found that most people can no longer distinguish between human voices and their artificial intelligence (AI)-generated counterparts, raising growing concerns about misinformation, fraud, and the ethical use of voice-cloning technologies.
The research, published in the journal PLoS One by scientists from Queen Mary University of London, revealed that participants were able to correctly identify genuine human voices only slightly more often than they could identify cloned AI voices. Out of 80 voice samples—half human and half AI-generated—participants mistook 58 percent of cloned voices for real, while 62 percent of actual human voices were correctly identified.
“The most important aspect of the research is that AI-generated voices, specifically voice clones, sound as human as recordings of real human voices,” said Dr. Nadine Lavan, lead author of the study and senior lecturer in psychology at Queen Mary University. She added that these realistic voices were created using commercially available tools, meaning anyone can produce convincing replicas without advanced technical skills or large budgets.
AI voice cloning works by analyzing vocal data to capture and reproduce unique characteristics such as tone, pitch, and rhythm. This precise imitation has made the technology increasingly popular among scammers, who use cloned voices to impersonate loved ones or public figures. According to research by the University of Portsmouth, nearly two-thirds of people over 75 have received attempted phone scams, with about 60 percent of those attempts made through voice calls.
The spread of AI-generated “deepfake” audio has also been used to mimic politicians, journalists, and celebrities, raising fears about its potential to manipulate public opinion and spread false information.
Dr. Lavan urged developers to adopt stronger ethical safeguards and work closely with policymakers. “Companies creating the technology should consult ethicists and lawmakers to address issues around voice ownership, consent, and the legal implications of cloning,” she said.
Despite its risks, researchers say the technology also has significant potential for positive impact. AI-generated voices can help restore speech to people who have lost their ability to speak or allow users to design custom voices that reflect their identity.
“This technology could transform accessibility in education, media, and communication,” Lavan noted. She highlighted examples such as AI-assisted audio learning, which has been shown to improve reading engagement among students with neurodiverse conditions like ADHD.
Lavan and her team plan to continue studying how people interact with AI-generated voices, exploring whether knowing a voice is artificial affects trust, engagement, or emotional response.
“As AI voices become part of our daily lives, understanding how we relate to them will be crucial,” she said.
Tech
Global Rights Groups Call for AI Companies to Be Held Responsible for Children’s Safety
Tech
Study Says EU Regulations Are Slowing Rollout of Advanced AI Models
A new study by Governance.AI has found that European Union regulations are delaying the rollout of advanced artificial intelligence models, with technology companies increasingly pointing to the bloc’s regulatory framework as a key obstacle to launching new AI products in Europe.
The report examined 375 large language models (LLMs) released between June 2018 and May 2026, comparing their availability across the United States, the European Union and the United Kingdom. According to the findings, at least 11 percent of advanced AI model releases were either delayed or never launched in the EU compared with the United States. In the UK, the figure stood at 7 percent.
Researchers said they identified 68 cases in which AI models experienced delays or were withheld from specific markets. Regulatory factors were cited as the primary reason in 56 of those cases, making them the most common cause of restricted availability.
The study reviewed releases from major AI developers, including Meta, Google, OpenAI and Anthropic. Meta recorded the highest proportion of delayed or unavailable releases, with 26 percent of its AI models delayed or withheld in the EU and 15 percent in the UK. Anthropic’s Claude 3 Opus was highlighted as one example, with its web application arriving in the EU 71 days later than in the United States.
According to the report, data protection rules have emerged as the biggest regulatory hurdle, particularly for AI systems capable of processing images, audio and real-time video rather than text alone.
The researchers argued that uncertainty surrounding the application of the General Data Protection Regulation (GDPR) to AI model training and deployment has created additional challenges for developers. They also said enforcement of data protection rules has generally been stricter within the EU than in the UK, despite both jurisdictions sharing similar legal foundations following the adoption of the GDPR before Britain’s exit from the bloc.
The report noted that the full impact of newer legislation, including the Digital Markets Act, which began taking effect in 2023, and the Artificial Intelligence Act, adopted in 2024, has yet to be fully reflected in the data.
At the same time, the European Union is reviewing proposals aimed at making data rules more practical for AI development through its Digital Omnibus initiative. Lawmakers are also considering changes to copyright legislation and the AI Act’s copyright provisions to strengthen protections for creators, measures that researchers say could affect future AI model availability if implemented too strictly.
John Lidiard, a UK AI policy researcher and one of the report’s authors, said policymakers should consider the impact that regulatory barriers can have on businesses and consumers seeking access to the latest AI technologies. He said balancing innovation with effective oversight would remain a key challenge as governments continue to develop AI regulations.
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