Anthropic says the change was motivated by a "collective action problem" stemming from the competitive AI landscape and the US's anti-regulatory approach. "If one AI developer paused development to implement safety measures while others moved forward training and deploying AI systems without strong mitigations, that could result in a world that is less safe," the new RSP reads. "The developers with the weakest protections would set the pace, and responsible developers would lose their ability to do safety research and advance the public benefit."
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The Penn-Wharton model found in a preliminary analysis that AI could reduce deficits by $400 billion by 2035. But the Congressional Budget Office framed AI and associated investment as wild cards in determining the U.S. fiscal and economic outlook. While the CBO projects AI will enhance total productivity by 1% in the next decade, its most recent budget report conceded that this prediction was “highly uncertain.” If adoption is slow or costs higher than anticipated, it would significantly alter GDP growth and, consequently, government revenue.
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