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Matt Lucas and Hugh Bonneville among actors calling for law on AI voice cloning
Around 80 actors back a petition and open letter seeking statutory voice rights as campaigners warn AI clones can be made in 3 seconds.
- Over 80 performers, including Nicola Coughlan and Hugh Bonneville, have urged Prime Minister Andy Burnham to introduce legislation granting citizens legal ownership of their own voices to protect against unauthorized AI voice cloning.
- Save Our Voices Now founder Peter Caulfield warned that AI systems can clone voices in "just three seconds," leaving users vulnerable to fraud and identity theft. He noted 28% of UK adults have been targeted by voice-cloning scams.
- Audiobook narrator Alice Sockett called AI voice replication "an existential threat to our entire industry," while singer Sandi Thom emphasized her voice is "unique to me and was handed to me at birth." Both cited creative protections as essential.
- A government spokesperson acknowledged "digital replicas can be a powerful tool" while announcing a consultation on potential harms. Some individuals with medical conditions have welcomed technology that restores lost voices.
- Denmark has introduced legal reforms giving citizens ownership of their voice and body, allowing individuals to demand removal of unauthorized AI content and seek compensation. This precedent may influence UK legislation.
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Nicola Coughlan, Matt Lucas, Hugh Bonneville and More Back Campaign Against AI Voice Cloning: ‘An Existential Threat to Our Entire Industry’
Nicola Coughlan and Matt Lucas are among the high-profile names backing a campaign against AI voice cloning and calling for legislation.
·Los Angeles, United States
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Evening Standard+4 Reposted by 4 other sources
Hugh Bonneville among stars backing campaign against AI voice cloning
Around 80 people have added their signatures to an open letter to Prime Minister Andy Burnham.
·London, United Kingdom
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Total News Sources9
Leaning Left5Leaning Right0Center3Last UpdatedBias Distribution63% Left
Bias Distribution
- 63% of the sources lean Left
63% Left
L 63%
C 37%
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