Toward Economic Foundations of Supply and Demand for Automation in Production Agriculture
AbstractTwo general purpose technologies have dominated innovation since World War II. Information
Technology emerged as an applied discipline and economic sector during the
1950s. At about that time too discoveries in genetics laid the foundations for precise biological
engineering as a tool-set available to the health, agriculture and industrial sectors.
Our interest is in how these innovations have a↵ected labor and capital use in production
agriculture. Labor and capital inputs have di↵ered in their comparative provision
of two critical services, physical work and information processing. Labor’s comparative
advantage has traditionally been in Bayes-type information processing rather than
Newton-type work. Thus the laborer can adjust the point at which a stem is cut and
will discard potentially problematic produce. Capital, being unable to adjust so readily,
was limited in where it could replace labor. Over time, however, raw ingredients were
adapted to become more uniform and capital smartened by way of sensors and related
technologies. These innovations have decreased demand for labor-sourced information
processing capacity. The proposed analysis will construct a Bayesian model of energy
and decision-making needs in food production so as to understand how agriculture’s capital
and labor requirements have evolved over time. Raw product heterogeneity will be
parameterized as a determinant of demand for information processing while both factors
will be endowed with decision-making types I and II error probabilities to parameterize
information processing capabilities. Factors will also di↵er in the unit cost of work done.
An equilibrium displacement model may be used to calibrate welfare e↵ects.