AI Dark Output: The Visible Cost of Invisible Output
The article discusses the challenges of measuring the economic impact of AI, particularly the concept of 'Dark Output.' This invisible output could represent a significant portion of economic activity, yet current metrics fail to capture its value. As AI continues to evolve, the implications for productivity statistics and economic growth will be profound.
- ▪AI 'Dark Output' refers to economic value generated by AI that is not currently measurable in traditional metrics.
- ▪Historical parallels are drawn to the computer revolution, where productivity gains were not reflected in economic data.
- ▪The article highlights two types of Dark Output: substitution dark output, which replaces human labor with AI, and new dark output, which represents entirely new tasks enabled by AI.
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AI Dark Output: The Visible Cost of Invisible OutputWhy AI's increasing output is going to be one of the hardest economic measurement problems in history. AI "Dark Output" could end up being the majority of economic activity, but a challenge to measureMalcolm Spittler and Dylan PatelMay 29, 202628922ShareDuring the 1980s and 90s, macroeconomic data could not detect the contribution of the emerging computer revolution. Famously, Robert Solow quipped “You can see the computer age everywhere, but in the productivity statistics.” And yet, despite the dot com boom and bust the Magnificent 7 now have a market cap 1.8x that of Europe.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Semianalysis.
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