Job automation
Discussion paper
Racing with or against the machine? Evidence from Europe
A fast-growing literature shows that technological change is replacing labor in routine tasks, raising concerns that labor is racing against the machine. This paper is the first to estimate the labor demand effects of routine-replacing technological change (RRTC) for Europe as a whole and at the level of 238 European regions. We develop and estimate...
Article
Where machines could replace humans - and where they can't (yet)
As automation technologies such as machine learning and robotics play an increasingly great role in everyday life, their potential effect on the workplace has, unsurprisingly, become a major focus of research and public concern. The discussion tends toward a Manichean guessing game: which jobs will or won’t be replaced by machines?
Report
The risk of automation for jobs in OECD countries: a comparative analysis
In recent years, there has been a revival of concerns that automation and digitalisation might after all result in a jobless future. The debate has been fuelled by studies for the US and Europe arguing that a substantial share of jobs is at “risk of computerisation”. These studies follow an occupation-based approach proposed by Frey...
Article
Four fundamentals of workplace automation
The potential of artificial intelligence and advanced robotics to perform tasks once reserved for humans is no longer reserved for spectacular demonstrations by the likes of IBM’s Watson, Rethink Robotics’ Baxter, DeepMind, or Google’s driverless car. Just head to an airport: automated check-in kiosks now dominate many airlines’ ticketing areas. Pilots actively steer aircraft for...
Report
Machines that learn in the wild: machine learning capabilities, limitations and implications
This short report comes out of a workshop exploring the capabilities and limitations of machine learning algorithms. Rather than a complete resource looking at the specific capabilities of different algorithms, this report is an introduction to some of the current capabilities and limitations in the field.