Will robots kill jobs, or create them?

Will robots kill jobs, or create them?

A lot of people are worried about losing their jobs to either a robot or a line of code.

This anxiety is fair – just ask Encyclopedia Britannica.  Some say 6% of all US jobs will be lost to robots by 2021, others say 38% of US jobs will be automated by 2030, and even in Australia the government estimates 40% of Australian jobs could be replaced by technology by 2025. Despite the political focus on job losses due to foreign trade, a study conducted at Indiana’s Ball State University found around 85% of US job losses were attributable to technology and automation, not trade. In other words, technology may be the top cause of job loss today. Yikes!

Before you run off to build an underground bunker with electromagnetic pulses to repel Skynet drones, it may help to know the historical relationship between humans and machines has created more jobs than it’s destroyed.  For example, a Deloitte study found technology has created more jobs than it’s destroyed since 1871 (140 years of data).  While “hard, dangerous and dull jobs” have declined, such as clothes washing services, “knowledge-intensive” and luxury-consumption jobs have created overall job gains.

So which is it?  Is technology taking more jobs?  Is it making more jobs?  Or does the answer depend on whether labor is high-skilled or low-skilled?

The high-skilled versus low-skilled distinction is historically accurate, but less meaningful every day.

Unlike the past 140 years, we now live in a historical period where technology has begun automating high-skilled as well as low-skilled labor. Instead of robotic arms replacing blue-collar welders in car factories, today we also have algorithms replacing white-collar forecasters who used to figure out how many cars to build in the first place.

It’s been around 22 years since the Internet was commercialized, and 18 years since the first popular smartphone. With all that data and today’s advanced algorithms to interpret it, there are ever-fewer safe places for high-skilled jobs to hide.

Technology is, at its core, the automation of labor.

Since the first sharp stick was used to defend against a hungry predator, technology has always been about doing less work. In this way, it inherently cuts in one direction.

That said, technology isn’t monolithic – as we’ve seen in the past 140 years it can both create and destroy jobs. The future depends on whether saving one kind of work (ex. not having to wrestle saber tooth tigers) frees us up to do even more kinds of work (ex. grow crops, make pottery, weave fabric).

In other words, the future could be bleak if technology kills all kinds of work. However, the future could be bright if technology kills old types of work, only to let us to discover more types of new work.

This isn’t just academic – the fate of employment itself may be on the line. For the past century, humans have been lucky because technology has sparked new work faster than it’s smothered old work. Yet what if this is starting to change? What if technology is now solving more problems than it creates?

At a minimum, job creation can’t be taken for granted. So if technology is part of the problem, maybe it can also be part of the solution.

Just as it can destroy jobs, can technology be used to deliberately create jobs?

What might that look like? Will job-creating innovations simply emerge by happenstance, as they have for the past 140 years? Or, this time, does humanity need to figure out how to do it on purpose?

This Post Has 2 Comments

  1. With Elon Musk and Stephen Hawking openly worrying about the dangers of technology, I hope it does in the end create more jobs than it kills. Thanks

  2. Thomas Thurston this is the topic at the top of my mind. I’ve put some thoughts down about how it will change white collar jobs close to those of us working on AI and AI products (https://venturebeat.com/2017/04/11/3-ways-ai-will-change-project-management-for-the-better/).

    I see AI creating jobs or more likely shifting jobs, particularly white collar jobs, to focusing more on the problem at hand and less on the mechanics of execution to do with the problem at hand.

    AI doesn’t know what question to ask but once you’ve asked the question and narrowed the possible solutions, it can help execute freeing you to ask more questions.

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