Biden Announces Meaningless Deal with AI Companies


Last week, Biden announced a new set of AI safety rules that will apply to seven of the largest AI companies: Amazon, Google, Meta, Microsoft, OpenAI, Anthropic, and Inflection. The new rules require AI-generated content to be watermarked, require AI systems be subjected to cybersecurity and capability testing before release to the general public, and require AI systems be made available to external vulnerability auditers.

However, the announcement is pure theater. The new rules are not regulations or laws. They are just voluntary commitments by the tech companies involved — voluntary commitments to safety measures that the companies have already implemented or are working on implementing. The voluntary deal accomplishes nothing that wasn’t already going to happen, despite Biden emphasizing in a press statement that the commitments were “real”.

In fact, pushing this misleading narrative that AI companies are adopting new safety rules may actually lower the probability that AI safety legislation is passed in the U.S. anytime soon. However, when AI safety legislation is eventually passed in the U.S., and make no mistake, it will be, it will likely include provisions similar to the requirements in this voluntary deal. Why do I say that? Because it’s what happened to the car industry 80 years ago.

References

[1] WSJ: White House says Amazon, Google, Meta, and Microsoft agree to AI Safeguards

[2] White House Fact Sheet: Biden-Harris administration secures voluntary commitments from leading AI companies to manage the risks posed by AI

[3] A Tsunami of Regulation is Coming for Big Tech

[4] U.S. Senators Propose New AI Regulatory Agency

Ricky Nave

In college, Ricky studied physics & math, won a prestigious research competition hosted by Oak Ridge National Laboratory, started several small businesses including an energy chewing gum business and a computer repair business, and graduated with a thesis in algebraic topology. After graduating, Ricky attended grad school at Duke University in the mathematics PhD program where he worked on quantum algorithms & non-Euclidean geometry models for flexible proteins. He also worked in cybersecurity at Los Alamos during this time before eventually dropping out of grad school to join a startup working on formal semantic modeling for legal documents. Finally, he left that startup to start his own in the finance & crypto space. Now, he helps entrepreneurs pay less capital gains tax.

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