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Ex-Google DeepMind researcher adds to warnings that AI could ’kill all humans’

Ex-Google DeepMind researcher adds to warnings that AI could ’kill all humans’

In a recent development, a former Google DeepMind researcher has joined the chorus of AI experts who have warned that the technology could pose a threat to human existence. Bilal Chughtai, who worked on AGI safety and alignment research, expressed his concerns on social media platform X, stating that he believes AI has the potential to kill all humans and that time may be running out to prevent this outcome.

Chughtai's fears echo those of other prominent AI researchers, such as Jacob Coxon, who recently resigned from Anthropic, a leading AI research company. Coxon acknowledged that he resigned in part due to his belief that AI could pose an existential risk by the end of the decade. Responding to Coxon's comments, Evan Hubinger, another Anthropic scientist, confirmed that he agreed with the assessment and expressed his own belief that there was a greater than 10% chance that AI could pose such a threat within the next ten years.

Following this wave of warnings, Anthropic CEO Dario Amodei called for a slowdown in the pace of advanced AI development. His plea for caution was met with rare support from both Elon Musk, co-founder of SpaceX and Tesla, and Sam Altman, CEO of OpenAI. The debate surrounding AI doomerism, or the belief that AI could pose an existential threat, has intensified, with some experts advocating for a more measured approach to AI development.

Chughtai himself acknowledged that navigating AI safely is possible, but he emphasized the need for coordination to prevent a "manic race" between AI companies. He argued that society must pace AI development to a speed at which emerging risks can be addressed before extreme harm becomes a reality. Despite these warnings, President Donald Trump has dismissed the concerns, calling the industry's call for regulation a "hoax" on social media.

Written by urgent.news from Investing.com's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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