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W. Brian Arthur

The economist whose theory of increasing returns proved that technology markets are governed not by the neat equilibria of classical economics but by positive feedback, lock-in, and winner-take-all dynamics—the operating manual for understanding why AI is consolidating as fast as it is.
W. Brian Arthur spent four decades demonstrating that the economics textbooks were wrong about technology. Classical economics rested on diminishing returns—the assumption that each additional unit of input produces less additional output. Arthur's landmark 1989 paper in The Economic Journal proved that in technology markets the opposite holds: success breeds success, advantage compounds upon itself, and the result is not a comfortable competitive equilibrium but lock-in, a condition in which a technology maintains dominance not because it is best but because its accumulated network effects and switching costs have made displacement prohibitively expensive. From his decades at the Santa Fe Institute he extended this into a theory of technology itself—that technologies arise from combinations of earlier technologies in a recursive, self-generating cascade that produces the combinatorial explosion of innovation now visible in AI. In 2019, when most observers were still debating whether AI was “just another technology,” Arthur stated the contrary with characteristic directness:
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