Robots Are About to Take Most Jobs; Then What?
Some post Labor Day musings.
Next year, the Chinese company, GigaAI plans to start selling robots that load dishwashers and fold laundry. The price: About $14,000 each. Robots being developed by another Chinese company, UniX AI, will clean toilets, make beds and cook breakfast. Unipath’s general purpose household robot will operate appliances and tidy storage.
These robots were developed at massive training centers employing tens of thousands of human workers equipped with sensors that mimicked the myriad motions needed to perform specific tasks. Now, the results of that commitment are reaching the marketplace.
These are not Roomba-like vacuum cleaners. They’re humanoids, built to mirror human forms. The major difference is that for household work, the robots will be on wheels.
What humanoids can be trained to do in the home can, of course, be trained for work.
For years, robots have been building our cars and used in other forms of manufacturing. China ships nearly all of the industrial robots now in the world’s marketplace. The next generation will be more human-like, capable of doing small bore tasks like tightening screws, sorting parts, handling fragile electronic components, scanning barcodes and sorting irregularly shaped parcels.
Global Race to Train Advanced Robots
The Hangzhou Robot School trains for specialized career tracks, like healthcare and nursing, retail and hospitality. The Innovation Center in Shanghai gathers specialized robots from competing companies and pools their millions of data points into a single industrial “super brain,” allowing robots of any shape, size or brand to instantly download skills needed for any new job.
All of this is underwritten largely by the Chinese government.
Much of the same work is taking place in the U.S. by public and private companies using different methods. While China focuses heavily on the sheer volume of human laborers on physical factory lines, the U.S. is betting on super computing power to close the gap through advanced simulations and massive data processing.
Robots are being trained by human teleoperators to understand the relationship between what they see through their installed cameras and the physical jobs they are expected to perform. U.S firms are literally teaching robots to think for themselves.
Economic Impact and Job Displacement Predictions
Where is this leading us? The Boston Consulting Group estimates that 50% to 55% of all currently active U.S. jobs, blue collar and white collar alike, will be dramatically reshaped by AI. Millions of others will be completely eliminated. The World Economic Forum estimates that globally, 92 million jobs will be completely displaced or eliminated and that 40% of all global employment will be directly exposed to AI-driven change.
These are not far futurist projections. They anticipate all of this by 2030.
Of course, as with any change this massive, new jobs will be corrected. The World Economic Forum estimates that the workplace will actually net more new jobs than those that are lost.
Based on historic job transformations, like the industrial revolution’s impact on agriculture, and the rise of solar and wind on coal miners, it’s doubtful that every current worker will slide seamlessly into the new AI defined world. We’re in for a tsunami of near term job losses affecting entire communities—just as Asia’s emergence hollowed out once thriving U.S. manufacturing towns.
How will the U.S. cope, economically and politically? There’s no shortage of ideas.
Tax AI companies to pay for worker training, or give tax credits to companies that retrain their employees.
Create tax exempt personal accounts, matched by corporate contributions, to allow displaced works to pay for technical training or earn trade certificates.
Offer fast-tracked, 3-to-6-month certificates in highly secure human fields, such as specialized healthcare, like nurse practitioners, and advanced trades.
Distribute a portion of the tax revenue generated from tech conglomerates and automated data centers as a monthly stipend, establishing an absolute income floor.
Rather than distributing direct cash, some policymakers argue for expanding state-subsidized infrastructure: state-funded housing, universal healthcare, and free public transit to lower the baseline cost of living for displaced workers.
Labor unions propose shortening the standard work week to 32 hours with no loss in pay to broaden the workforce pool.
Political Realities and Government Leadership in an AI Era
Whatever the response, unless it meets the demand, we’re facing a flood of unemployed workers. China, which is converting at a faster pace than the U.S., has a 17% unemployment rate among young workers.
This is an enormous challenge for the next Congress and President. So is the fact that long forecast disastrous fires, droughts, storms, disease and killer heat waves resulting from global warming are here and accelerating in intensity. So is the imbalance of wealth and power. So are many other unmet challenges on a global scale, including the capacity for democratically elected governments to cope with an AI, robotic and quantum computing world.
Whatever the result of November’s election, the winners must emerge from Congress’s stalemates and address reality. The word “radical” is in great supply during this year’s campaigns. Think of it more as a necessity than an insult.
Always Get It’s Always Something
Sign up to get the most recent column set to your inbox for free.
What happens when a fun-loving, charismatic, reform-minded Mexican-American billionairess becomes president of the United States and strikes fear in the pocketbooks of a cabal of the rich and powerful?