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Ex-Google DeepMind researcher warns AI could “kill us all”, says humans running out of time

A former Google DeepMind researcher has warned that artificial intelligence could “kill us all”, saying there may be little time left to prevent such an outcome as advanced AI development accelerates.

Ex-Google DeepMind researcher warns AI could “kill us all”, says humans running out of time

A former Google DeepMind researcher has warned that artificial intelligence could “kill us all”, saying there may be little time left to prevent such an outcome as advanced AI development accelerates.

Bilal Chughtai, who worked as a research engineer on artificial general intelligence (AGI) safety and alignment research at Google DeepMind, made these comments on X on Monday.

Chughtai’s warning comes amid growing concern among AI researchers and global leaders about the potential consequences of rapidly advancing AI systems.

What Chughtai is saying

Chughtai said the risks posed by advanced AI are severe and that there may be limited time to prevent the worst-case scenarios.

  • “At Google, I witnessed AI development first hand. I too am extremely concerned by the default trajectory of this technology. I earnestly believe that AI has the potential to kill us all, and that we might be running out of time to avoid this outcome,” Chughtai wrote.

He said the pace of AI development over the past few years has been “staggering”, noting that AI systems have advanced significantly since he began working in the field in early 2022.

Chughtai also said he believes AI companies could succeed within the next few years in developing superintelligent systems that exceed human capabilities across every domain.

He said safely navigating AI development remains possible but would require greater coordination among companies developing increasingly advanced systems.

  • We need to pace AI development to a speed that society can handle, where emerging risks can be addressed before extreme harm is realised,” he said.

Chughtai also described AI alignment, the effort to ensure AI systems behave as intended, as a difficult and unresolved problem.

He said current understanding of how to train AI systems to reliably pursue human goals remains limited, while frontier AI capabilities are improving faster than researchers’ understanding of alignment.

Chughtai also called for coordination among AI companies to avoid what he described as a “manic race” in AI development.

Get up to speed

Chughtai’s comments follow warnings from researchers at Anthropic, another major AI company, over the potential risks posed by advanced AI.

  • Anthropic researcher Jacob Coxon said last week that he had resigned from the company because AI companies “are racing straight to self-improving superintelligence and gambling with our lives.”

Anthropic scientist Evan Hubinger subsequently backed Coxon’s assessment, saying he believed there was a greater than 10% chance that AI could kill all humans within the next decade.

The comments have added to an increasingly public debate over whether AI companies are developing increasingly powerful systems too quickly.

Anthropic CEO Dario Amodei, over the weekend, called for a slowdown in the pace of advanced AI development, amid concerns about the risks associated with the technology.

The call also received backing from SpaceX and xAI founder Elon Musk and OpenAI CEO Sam Altman.

What you should know

While warnings about AI’s potential to pose an existential threat remain a subject of debate, the technology is already changing the labour market, including how Nigerian companies recruit and structure their workforces.

Nairametrics reported in May that Nigerian startup founders and operators said AI was changing the type of workers companies wanted to hire, with businesses increasingly looking for professionals who can combine industry expertise with AI tools.

The shift is also affecting existing roles.

In June, business leaders across manufacturing, banking, consulting, legal services and media told Nairametrics that AI was improving productivity while reducing reliance on some traditional administrative, research and clerical functions.




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