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Alec Harris

Titles as the sources gave them. In 1 entry, with 3 checked quotations.

What they said

Newest first. Each quotation was found word for word in the source.

“However, an alternative possibility is that Anthropic’s AIs might be assisting with ML research in a way that overfits to AECI such that this acceleration will not be sustained.”
Do verifiable metrics overestimate RSI?LessWrong, November 11, 2026. Speaking as: Other. Harris sets out the central alternative to reading METR's finding as the start of a recursive self-improvement loop.
“As long as you think that even a small fraction of verifiable capabilities transfer to fuzzy tasks, a FOOM on verifiable tasks will quickly transfer to fuzzy tasks.”
Do verifiable metrics overestimate RSI?LessWrong, November 11, 2026. Speaking as: Other. Harris explains why little weight belongs on the concern that gains on verifiable tasks will not carry over to fuzzy ones.
“My all-things-considered view is that there is a 60% chance we will see a deceleration in AI progress in the next two years, but a significant, maybe 30%, chance we will see ASI by the end of 2027.”
Do verifiable metrics overestimate RSI?LessWrong, November 11, 2026. Speaking as: Other. Harris closes the post with an overall forecast.

In the Base

Every entry they appear in.

  1. EssayLessWrongWrote it

    Do verifiable metrics overestimate RSI?

    In a five-minute LessWrong post, Alec Harris argues that the acceleration METR measured at Anthropic may partly reflect AIs overfitting to Anthropic's internal capability index, and so may not last. Harris puts 60% on a slowdown within two years and about 30% on ASI by the end of 2027.