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Google staff resign in backlash over its AI contracts with military
She said Google’s military work could help kill people and intensify war, after internal protests and a public demonstration with colleagues.
- Research engineer Sofia Liguori resigned from Google DeepMind in protest over the company's military contracts, stating she could no longer support technology facilitating the brutality of war.
- Liguori's discovery of Google's Project Nimbus, a $1.2bn joint contract with Amazon providing AI infrastructure to Israel, prompted her moral opposition. Watching news from Gaza in 2024 while on maternity leave solidified her decision.
- In her resignation letter to colleagues, Liguori urged them to "stay human" regarding military work. She told the BBC that while contractually barred from criticizing Google, speaking out about facts was essential.
- Sarah Shoker, former head of OpenAI's Geopolitics team, warned that "AI compresses the time an operator has to make a decision," while similar military contracts span Microsoft, SpaceX, and Oracle.
- Former Google employee Andreas Kirsch argues current AI models lack robustness for battlefield tasks, while anonymous DeepMind staff warn of a "changing of the guard" as motivated employees depart.
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The American giant Google is facing some resignations from its employees who protest for the military use of artificial intelligence technologies developed within the company. It reveals BBC...
·Milan, Italy
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Some employees at Google's AI company DeepMind have resigned in protest against the company's AI contracts with the US military. One of the departing engineers said he was ashamed to have worked at Google.
Google faces critical reactions from employees, dissatisfied with how the company puts its artificial intelligence technology at the disposal of the army.
·Bucharest, Romania
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Total News Sources5
Leaning Left1Leaning Right1Center1Last UpdatedBias Distribution34% Left, 33% Center, 33% Right
Bias Distribution
- 34% of the sources lean Left, 33% of the sources are Center, 33% of the sources lean Right
34% Left
L 34%
C 33%
R 33%
Factuality
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