The future of the workforce is one of the biggest issues facing CEOs today. It’s abundantly clear to all that artificial intelligence, big data analytics, and advanced robotics make it possible for machines to take on tasks that once required a person to do them. How should companies prepare, strategically, to thrive in this world?
Views on what to expect vary dramatically. By some accounts, almost half of all jobs in the U.S. economy could be made obsolete. Others have described how intelligent machines will actually create jobs — including entirely new categories of jobs. Some people even talk about a world of superabundance where work will be about pursuing your passion, on your own terms.
It’s critical for companies to understand the range of opinions on this issue, because implicitly or explicitly, they will influence the way business leaders create the workforce of the future. And while a lot will shake out in years to come, this issue is already front and center. Companies are making decisions today that will matter hugely to their ability to compete tomorrow and throughout the 2020s.
Most companies are already moving rapidly to acquire new capabilities. In a new Accenture survey (“Reworking the Revolution,” which published on January 23rd) of 1,200 C-level executives worldwide, 75% say that they are currently accelerating investments in AI and other intelligent technologies. And 72% say they are responding to a competitive imperative — they recognize the need for new tools to keep up with rivals, both by improving productivity and by finding new sources of growth. Some companies are transforming themselves into “intelligent enterprises,” in which all processes are digitized, decisions are data-driven, and machines do the heavy lifting — both physical and cognitive.
So, there’s a great deal at stake in the debate over productivity and jobs. Leaders must understand the debate and be prepared to address tough questions: What kind of new skills do we need? How should we be organized? How do we define jobs? How can we bring our people along with us, in a way that benefits everyone?
Position: Man and machine will wage a Darwinian struggle that machines will win. AI systems will take on tasks at the heart of middle- and high-skill jobs, while robots will perform menial work that requires low-skill labor. The result will be massive unemployment, falling wages, and wrenching economic dislocation. Falling incomes will have grave consequences in places like the United States and Europe, where consumption accounts for 56% or 69% of GDP, respectively, requiring new social supports, such as a universal basic income.
Position: Intelligent machines will take on even more work, but the result will be unprecedented wealth, not economic decline. AI and computing power will advance in the next two decades to achieve “the singularity” — when machines will be able to emulate the workings of the human brain in its entirety. Human brains will be “scanned” and “downloaded” to computers and billions of replicated human brains will do most of the cognitive work, while robots will do all the heavy lifting. Economic output could double every three months. The singularity may even lead to a world where little human labor is required, a universal income program covers basic needs, and people apply their talents to meaningful pursuits.
The Technology Optimists
Position: A burst of productivity has already begun but is not captured in official data because companies are still learning how intelligent technologies can change how they operate. When companies do take full advantage of intelligent technologies, a leap in productivity will produce a digital bounty — creating both economic growth and improvements in living standards not counted in GDP, such as consumer surplus (from better, cheaper products) and the value of free apps and information. However, based on current trends, the bounty won’t be distributed evenly, and many jobs will be displaced. To avoid negative income and employment effects, there will be a need to invest in education and training alongside investments in technology.
Read the source article at Harvard Business Review.
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