Robohub.org
 

Ability to do creative, non-routine work will be a must in the coming automation era. Is this realistic for most workers?


by
13 April 2013



share this:

There can be no doubt that technological progress has resulted in a far more prosperous society. Technology has often disrupted entire industries and, in some cases — as with the mechanization of agriculture — destroyed millions of jobs. In the long run, however, the economy has always adjusted and new  jobs have been created, often in entirely new industries. Why then should we be concerned that the revolution in robotics and artificial intelligence will lead to sustained unemployment? I think the answer has to do with the nature the work that most members of our workforce are best equipped to perform.

This post is part of Robohub’s Jobs Focus.

Martin Ford: The Lights in the Tunnel

A strong argument can be made that a very large percentage of jobs are, on some level, essentially routine and repetitive in nature. In other words, the job can be broken down into a discrete set of tasks that tend to get repeated on a regular basis and can be predicated based on historical data. It seems likely that, as both computer hardware and software continue to progress, a large fraction of these job types are ultimately going to be susceptible to robotic or software automation, and in particular to machine learning technology.

Recent innovations like IBM’s Watson computer suggest that machine learning algorithms may soon be able to take on a number of cognitive tasks. As technology accelerates, I think there is little doubt that these systems will begin to match or exceed the capability of human workers in many routine job categories — and this includes a lot of workers with college degrees or other significant training.

As robots and smart algorithms increasingly take on the more routine, predictable jobs, this will leave much of our workforce with an unprecedented challenge. Historically, most workers have been able to move from routine occupations in one area to similarly routine jobs in a new emerging area, perhaps acquiring some new skills as part of the transition. However, as technology impacts virtually all routine work across the board, workers will have to find work in areas that are genuinely non-routine or creative in order to remain relevant. There are good reasons to be concerned that a significant fraction of our workforce will have great difficulty with such a transition: after all, if we assume a normal distribution or capability, then by definition, 50% of workers are average or below average.

Jobs_2
In order to solve the distributional problems that will be created by automation — and to ensure continued, broad-based prosperity — we will need to reform our economic systems.

None of this is intended to argue against continuing progress in areas like robotics, big data and AI. However, as these technologies continue to accelerate, the impact on employment and income inequality is likely to become more and more visible to the general public. Ultimately, I think that in order to solve the distributional problems that will be created by automation — and to ensure continued, broad-based prosperity — we will need to reform our economic systems. If we fail to do this, it seems very likely that a public backlash against automation technologies, as well as significant social and economic upheaval could well result.



tags: , , , , , ,


Martin Ford is the author of "The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future.
Martin Ford is the author of "The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future.





Related posts :



Meet the AI-powered robotic dog ready to help with emergency response

  07 Jan 2026
Built by Texas A&M engineering students, this four-legged robot could be a powerful ally in search-and-rescue missions.

MIT engineers design an aerial microrobot that can fly as fast as a bumblebee

  31 Dec 2025
With insect-like speed and agility, the tiny robot could someday aid in search-and-rescue missions.

Robohub highlights 2025

  29 Dec 2025
We take a look back at some of the interesting blog posts, interviews and podcasts that we've published over the course of the year.

The science of human touch – and why it’s so hard to replicate in robots

  24 Dec 2025
Trying to give robots a sense of touch forces us to confront just how astonishingly sophisticated human touch really is.

Bio-hybrid robots turn food waste into functional machines

  22 Dec 2025
EPFL scientists have integrated discarded crustacean shells into robotic devices, leveraging the strength and flexibility of natural materials for robotic applications.

Robot Talk Episode 138 – Robots in the environment, with Stefano Mintchev

  19 Dec 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Stefano Mintchev from ETH Zürich about robots to explore and monitor the natural environment.

Artificial tendons give muscle-powered robots a boost

  18 Dec 2025
The new design from MIT engineers could pump up many biohybrid builds.



 

Robohub is supported by:




Would you like to learn how to tell impactful stories about your robot or AI system?


scicomm
training the next generation of science communicators in robotics & AI


 












©2025.05 - Association for the Understanding of Artificial Intelligence