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Revisiting The Luddite Fallacy.

Revisiting The Luddite Fallacy.

The Luddite Fallacy is commonly leveled at the notion that technological unemployment – unemployment caused by technological changes – leads to widespread structural unemployment. It is deemed a fallacy because ever since the rise of printing presses and looms and other automation or labour-saving technologies we have not only destroyed old jobs but created new ones for people to work at – new jobs that could not have been foreseen. Through the seeming miracle of market growth and consumption, structural unemployment has been avoided. 

However, I’m firmly in the camp that think that this time is different, and I share the views of the likes of commentators like Martin Ford ( and others. I do not think that the Luddite Fallacy is applicable to the present era of technological change with advanced automation, robotics, expert AI’s, software development, and other solutions driving technological unemployment ( 

This is most certainly a minority viewpoint at the present time. The vast majority of economists, especially those advising governments, big business, and think tanks believe that this time will be the same as all the others and the Luddite Fallacy is alive and well. 

The other day I came across a recent example of this on an economics blog that I check out from time to time The key excerpt is:

Debate over whether technological advancement is killing jobs is as old as the hills. When the automobile was introduced, stagecoach drivers protested at the loss of jobs. Ditto the 19th century mill worker and the 20th century bank teller. In all cases, new jobs were created in areas unthought of at the time. The same will happen again. New jobs will come from somewhere, although for some workers whose skills are made obsolete, they will be forced to take on less financially rewarding work.

One of the reasons I think it is different this time, and why those economists who still persist with the Luddite Fallacy are wrong is as follows:


In times past our technological development, our automation, our labour-saving machines were focused on enhancing or compensating or replacing our bodies. We basically built bigger, stronger, and faster arms and legs that were tireless; think of the massive presses, pumps, and rollers of industrial mechanisation, forklifts, trucks, and rapid transit, turbines, drills, and excavators. Or we built louder voices and symbolic projections; think of telecommunications and anything that allows your voice, your image, or your writing to be rapidly reproduced and projected around the globe to instantly reach vast audiences. There are myriad examples. 


This time around we are not enhancing our bodies, but our minds. We are guiding our technological evolution towards engineering intelligence – our species’ core competitive advantage, and the thing that enabled us to learn, adapt, get smarter and discover more complex things that needed doing. We will engineer machines that remember better than we do, solve problems better than we do, and make creative associations better than we do. IBM’s Watson program, DARPA’s SyNAPSE program, the various Big Brain programs, and others, are all laying the foundation on which these machines will be built. When a machine is eventually created that has the intelligence and problem solving ability of a human and the means to manipulate its environment, then there would seem to be, by definition, no conceivable job that a human could do that a machine could not do faster, better, and cheaper. 

I also don’t believe this to be a bad thing. Quite the contrary. I think we should measure our progress by increases in our quality of life and collective standards of living, and this time around we’ll be capable of delivering simply unimaginable progress. There is no guarantee that we won’t mess this up, but I can’t help but be optimistic that we’ll muddle our way through. 

Sure, we can nit-pick over the finer details, argue about the ever-shrinking pool of jobs that machines can’t yet do, or of clever humans exploiting early machine intelligence in niche expert areas to accomplish more than either humans or machines can alone. But in the end near-complete technological unemployment seems to me to be unavoidable, and it is good to see this getting occasional coverage – good or bad – in the mainstream media. 



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