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Can AI Be Regulated?

Frontier AI labs are calling for government oversight.

Can AI Be Regulated?

The discussion surrounding the regulation of artificial intelligence (AI) has intensified in the United States. U.S. President Donald Trump opposes new strictures on the industry, but the public has expressed concern about the potential for AI to produce catastrophic consequences for the economy and human society. One question that emerged during a recent conversation between journalist Cameron Abadi and economics columnist Adam Tooze is whether normal liability law would be sufficient to regulate AI technology.

Abadi and Tooze explore various legal avenues that could mitigate the dangers of AI, such as negligence, product liability, nuisance, professional malpractice, contract, and consumer protection law. However, the complex nature of AI and the potential for catastrophic consequences raises questions about the applicability of these legal frameworks.

For instance, AI algorithms are not deterministic, meaning that the same inputs may not always produce the same outputs. This raises concerns about the ability to pinpoint causation in cases of AI-related harm.

Moreover, the financial value of AI companies could potentially fuel the push for regulation. Even though some AI industry leaders, such as Jensen Huang of Nvidia and Mark Zuckerberg of Meta, argue that market forces are sufficient to ensure product safety, others believe that new regulations may be necessary if companies are not confident in the functionality, capability, or safety of their products.

The question of whether the U.S. government has sufficient expertise to regulate AI also surfaces in the conversation. Additionally, it is unclear how effective liability law would be in such a rapidly evolving technological landscape. The lack of a binding reporting system for AI incidents further complicates the potential implementation of conventional legal frameworks.

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

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