  A central question in economics is whether automation will displace human
labor and diminish standards of living. Whilst prior works typically frame this
question as a competition between human labor and machines, we frame it as a
competition between human consumers and human suppliers. Specifically, we
observe that human needs favor long tail distributions, i.e., a long list of
niche items that are substantial in aggregate demand. In turn, the long tails
are reflected in the goods and services that fulfill those needs. With this
background, we propose a theoretical model of economic activity on a long tail
distribution, where innovation in demand for new niche outputs competes with
innovation in supply automation for mature outputs. Our model yields analytic
expressions and asymptotes for the shares of automation and labor in terms of
just four parameters: the rates of innovation in supply and demand, the
exponent of the long tail distribution and an initial value. We validate the
model via non-linear stochastic regression on historical US economic data with
surprising accuracy.
