AI reduces the cost of certain tasks to effectively zero. In doing so, it lowers the barriers to domains that would previously take years to build skills such as writing code, data analysis, and more. This is precisely why AI also increases the value of expertise and experience.
It’s one thing to write code, but as any engineer will tell you, there’s more to it than that. It might be easy to write the function, but large language models can’t reason about whether or not it’s the right thing to do. As Byrne Hobard writes in Working with a Copilot, “With a lower cost to making bad decisions fast, there’s a higher value on making good decisions.” Domain expertise and context are at much higher demand when the cost of low-context work goes to zero.
The same thing exists in business contexts. With AI tools that can summarize content from anywhere all the time, providing the write context (and specifying the right tasks) provided a multiplier on an experts time. When used effectively they just added a team of low-level workers at their beck and call.
See also:
- AI puts a higher premium on unique knowledge (previous thoughts about content in particular)
- Legal services has the highest AI occupational exposure
- AI is the next great interop layer which can greatly improve the impact of expertise
Links to this note
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46% of Developers Code Comes from Github Copilot
A blog post from GitHub says that their code assistance tool, Copilot, is behind 46% of developers' code, up from 27%. For Java, that number is 61%.
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Devin AI Fixes Bugs it Created
The “the first AI software engineer” Devin, from Cognition Labs, was found to be fixing bugs of it’s own doing, solving problems in a roundabout way, and taking a long time, in a debunking video by a human software engineer.
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AI Doubles Productivity of Top Researchers
A study of artificial intelligence on productivity at a materials research lab found that the bottom third of researchers saw no improvement but top researchers doubled in productivity (as measured by materials discovered, patents, and “downstream product innovation”). The top researchers used AI to offload 57% of idea generation to focus on evaluation of the most promising ones rather than chasing dead ends. This suggests AI multiplies the value of expertise rather than leveling the playing field.