What percentage of people believe that artificial intelligence poses a significant threat to humanity's future?

A 2023 survey of AI experts found that 36% fear AI development could result in a "nuclear-level catastrophe."

61% of Americans believe AI poses risks to humanity, according to a Reuters/Ipsos poll.

Over 1,000 technology leaders, researchers, and pundits signed an open letter warning of AI's significant risks.

AI's potential risks include autonomous systems usurping decision-making from humans and catastrophic consequences.

AI100, a Stanford University project, monitors AI progress and guides its development.

A 2021 AI100 report assessed AI developments between 2016 and 2021, highlighting significant advancements.

Experts warn that the rapid growth of AI technology could threaten humanity's future.

Jobs involving repetitive tasks are at risk of being replaced by AI.

Regulating AI's growth and use of data is crucial to mitigate potential threats.

AI's impact on jobs, security, democracy, and businesses needs regulation.

AI-generated texts like TV scripts, school essays, and resumes are increasingly common.

The potential for AI to destroy humanity has led over 1,000 experts to sign an open letter warning of its risks.

AI's potential threats include job loss, privacy invasion, and the risk of autonomous systems' misuse.

There is a significant discrepancy between experts' and the general public's understanding of AI's risks and rewards.

Recent progress in AI, like the development of Generative AI, has expanded its capabilities and popularity.

42% of enterprises scaled businesses integrated AI into their operations, according to a 2023 IBM survey.

Fear of an AI "kill switch" emerged due to the potential misuse of AI by irresponsible entities.

Controlling AI's development and avoiding catastrophic outcomes requires global cooperation.

The possibility of AI superintelligence surpassing human intelligence fuels existential risks.

The ethical considerations of AI development are critical, including addressing biased algorithms and ensuring transparency.