The Turn to Technological Unemployment: A Paradigm Shift in Economic Forecasting

Friday, 20 July 2018: 08:43
Oral Presentation
Riccardo CAMPA, Jagiellonian University at Krakow, Poland
By adopting the perspective of the “sociology of socio-technical expectations,” this paper analyzes recent reports on the future of work and argues that we are in the midst of a turn in economic forecasting in relation to technological unemployment. The problem of technological unemployment has usually been denied by mainstream economics, in particular by the so-called marginalist or neoclassic school, and sometimes dismissed as “the Luddite fallacy.” The narration of economists has typically been based on the axiom that “for every job destroyed by automation, a new and better-paid position will become available.” Sociologists of work, futurists, and Keynesian economists have sometimes challenged this view by calling it a “myth,” but their scenario analyses have been largely ignored. Recently, however, prestigious institutions, usually promoting the neoliberalist paradigm, or at least not hostile to it, are beginning to consider massive technological unemployment as a possible threat. Reports by institutions such as the McKinsey Institute, the World Economic Forum, the Bank of England, and Oxford University, predict that about half of present jobs could disappear within the next two decades because of automation and artificial intelligence. While it is true that new jobs will be created, no existing socio-economic mechanism can guarantee full employment. Outstanding scientists and businessmen (i.e. Steven Hawking, Bill Gates, Elon Musk) have added their voices to the debate by reinforcing the idea that without the intervention of governments, a future of mass unemployment is waiting. In other words, the new narration is based on the axiom that “for every job created by automation, several more will be eliminated entirely,” and that the reduction of working hours, or the implementation of a universal basic income, could be answers to this problem.