In 1930, the influential economist John Maynard Keynes coined the term 'technological unemployment” to describe what happens when mechanical labor makes human labor obsolete.

He predicted that by 2030 we could all be working just 15 hours a week.

That hasn't happened yet, because until now most technology has only been able to replace narrow slices of human capability, like physical strength or mathematical calculations.

But things are changing. A recent analysis by McKinsey showed that up to 45% of all current job tasks could be automated with existing technology.

Over the next couple of decades, the artificial intelligence and robotics now emerging from academia and tech companies will be able to substitute for a much broader set of important human skills.

They will have the capability to perceive, move in, and manipulate unstructured environments, process information, make decisions, and understand and communicate with people.

Many of the tasks that simply had to be done by humans in the past will in the near future fall within their growing capabilities — as we are already seeing with jobs as diverse as security guards, call center workers, and truck drivers.

Strikingly, the president's annual Economic Report just forecast that over 80% of low-wage jobs could be automated in the next 10 to 20 years. The other critical difference with these new technologies is that they will not need to be laboriously programmed by highly skilled, expensive, and hard-to-find engineers.

The hottest technology today is machine learning, a set of computer algorithms that are able to learn to detect patterns, develop strategies, and refine their behavior by analyzing streams of digital data. Rather than relying on programming, AI will learn through trial and error as well as its own observations — meaning it will be deployed much more quickly to take on new tasks in the economy. And it is not just AI and robotics that will disrupt human labor.

What characterizes this era is the variety of technologies that are being created. 3D printing, drones, the blockchain (which can securely store verifiable transactions), and synthetic biology are wildly different technological developments that leverage advances in materials science, sensor technology, and raw computing power. They all have the potential to significantly disrupt industries that employ tens of millions of people. And the speed with which they are being developed, combined, and adopted is increasing. We have of course had disruptive technologies in the past, and significant migration in the workforce from farm to factory to services.

In each transition, we increased education levels and moved human labor into tasks that machines could not yet perform. But the difficulty is that the set of available tasks only humans can do will get narrower and narrower over time. Some argue that we will invent all kinds of new jobs and industries 'we can't even imagine,” but the fact is that brand new occupations and industries actually employ very few people.

Of the top 100 occupations (~75% of U.S. employment), only 10 did not exist 100 years ago. And those ten only employ about 6% of the U.S. workforce. New industries do not employ that many people either, both because they leverage new technology and because they are often subject to winner-take-all dynamics, where just one or very few firms win all the revenue.

A recent Oxford Martin analysis showed less than 0.5% of employment was in new industries created since 2000. Growth in employment has instead come in lower paying jobs in food services, healthcare, and education, which are all ripe for disruption. Some skeptics argue against this concern about technological unemployment using an economic theory called the lump of labor fallacy, which argues that since human needs are infinite, there will always be demand for labor. But there is nothing in economics that says the 'labor” has to be provided by humans.

In a world where products can be ordered, produced, and delivered through conversational interfaces, 3D printing, and drone delivery — and services can be implemented as intelligent algorithms— there are indeed many human needs, but all being served by 'robots” of one form or another.

We need to begin preparing for this inevitability and reimagine a society where most people cannot 'work for a living,” but instead can be liberated to pursue their own vision of a meaningful life. Several prominent AI researchers including Andrew Ng and Jeremy Howard have added their voices to those advocating for a Universal Basic Income, a monthly payment to every citizen independent of employment and with no means testing.

There is a growing global movement to explore basic income, which can provide economic security to people as we shift into a world where machines do most of the work. This can and should be a very positive development for humanity — we just need to prepare for a potentially difficult transition, as human labor becomes less and less necessary.

Gerald Huff is principal software engineer at a major Silicon Valley manufacturer and a commenter on technology and society.