Machine Learning and the Economy

November 2018, by Professor Noel Gaston | Economics

This blog post is featured in Issue 1 of the #AICollaborative Network Newsletter. View a full copy of the Newsletter. Forward the Newsletter to a friend. Subscribe to receive the Network Newsletter in your inbox.

Needless to say, considerable effort is being spent on thinking about machine learning and economic regulation. Paul Romer shared this year’s Nobel prize for Economics. He emphasised the role that technology plays as a crucial driver of economic growth and recognised that technology is itself spurred by the right environment for innovation and invention. Good public policy has a role to play. The legislation pertaining to intellectual property, antitrust, privacy protection and tort law, in all likelihood, needs to be remoulded. We need to get the balance right between consumer protection and innovation incentives.

Incidentally, in September this year, Romer presented an interesting paper titled Machine Learning as a 'Wind Tunnel' for Research on Human Learning.

Much of Romer’s most recent work is done using a set of tools and frameworks that are familiar to every machine learning developer: Jupyter notebooks and Python. This, along with the New York Federal Reserve’s recent release of their economic model as open source shows the impact that machine learning approaches are having on a field like economics, which is outside the traditional areas of interest for machine learning and artificial intelligence.

Interestingly, while there seem to have been seismic shifts in technology and innovation, for almost two decades developed economies have experienced a marked productivity slowdown. (By the way, that’s the real reason why average wages haven’t grown for so long.) The new technologies for all their promise, have yet to bear much fruit in terms of realised productivity growth. Early days still, perhaps?

Many of the issues mentioned here were discussed at recent conferences sponsored by the Cambridge, US-based National Bureau of Economic Research in 2017 and 2018.

Professor Noel Gaston

Noel has been a member of the Artificial Intelligence Collaborative Network since October 2018 and is the current Editor of the Network Newsletter.

Noel is the Adjunct Professor of Economics at the School of Commerce, University of SA and Former Principal Research Adviser at the Australian Productivity Commission.