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Nathan Lambert says expert humans are needed to diffuse AI into knowledge work

AINathan Lambert argues that AI adoption in knowledge work will take a long time because the work is interpersonal, messy and context-driven, and he says data companies should position experts as helping AI companies improve tools for workers rather than replacing them. He says this framing cuts against the labs' narrative that ASI will replace all knowledge work.
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It could be vastly underestimated how much human expertise is needed to diffuse the benefits of AI to the long-tail of knowledge work. I think more data companies should figure out this branding, where experts help AI companies understand how to improve the tools that make them more effective, rather than replaced.

Some jobs will be replaced for sure, but I think a lot of knowledge work is deeply interpersonal, messy, and context driven in a way where AI adoption will be a productivity boon to existing employees. We are seeing this with the demand for SWEs today.

This rebrand will serve the AI industry writ large very well, but goes against the RSI narratives of the labs as "ASI will replace all knowledge work." In some ways, the difference is more philosophical about "what is the nature of work." I believe knowledge work is much more human than the evals give credit for, and this will make diffusion take a long time. Seems like Mercor can be at the center of this diffusion puzzle.

Disclosure: Yes, I advise Mercor on trying to realize this puzzle, as I think it's super interesting.

Brendan (can/do)@BrendanFoody
We raised our $750 million Series D at a $20 billion valuation from @benchmark, @generalcatalyst, @nvidia, @salesforce, and @zoom. @mercor scaled from $1M to $3B in run-rate revenue in 27 months, the fastest in history to $3B. For 2 years, we've organized human intelligence to build evals and training data for every frontier lab. The labs are the leading indicator for AI startups, then the Fortune 500. Our growth has accelerated over the past 6 months as enterprises start evaluating and training their own models. For many, owning their intelligence is existential.
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Original title: It could be vastly underestimated how much human expertise is needed to diffuse the benefits of AI to the long-tail of knowledge work. I ...