CONCEPT
The Turing Trap
Brynjolfsson's 2022 diagnosis of the systemic bias in AI development toward
replacing rather than
amplifying human workers — a trap set by the Turing Test's implicit goal of human-indistinguishable machines, reinforced by tax codes, research incentives, and organizational defaults.
The Turing Trap names the structural bias in contemporary AI development toward building systems that substitute for human labor rather than augment it. The trap is set by
Alan Turing's 1950 proposal that machine intelligence be measured by indistinguishability from human performance — a standard that, applied as a research
goal, orients the entire field toward replacement rather than partnership. The trap is reinforced by a tax code that subsidizes capital investment while taxing labor, by research benchmarks that measure machine-vs-human competition rather than
human-AI collaboration, and by organizational incentives that favor cost reduction over capability expansion. The resulting bias is not a conspiracy but an emergent property of thousands of locally rational decisions that, in aggregate, produce a technology trajectory that concentrates economic and political power among those who control the automated systems. Brynjolfsson laid out the argument in a 2022 Dædalus paper and sharpened it in subsequent public lectures, calling for