News Research

How to prepare for the AI productivity boom

After years of decline, productivity is poised to accelerate. The next challenge is preparing workers, and making sure benefits aren’t distributed unequally.

Copyright by mitsloan.mit.edu 

SwissCognitive, AI, Artificial Intelligence, Bots, CDO, CIO, CI, Cognitive Computing, Deep Learning, IoT, Machine Learning, NLP, Robot, Virtual reality, learningThe last 15 years have brought what Stanford University professor Erik Brynjolfsson calls the “productivity paradox.” While there’s been continuing advances in technology, such as , automation, and teleconferencing tools, the U.S. and other countries have seen flagging productivity.

But a productivity boom is coming soon, Brynjolfsson said at the recent EmTech Next conference hosted by MIT Technology Review.  He pointed to advances in technology, particularly programs that are as good as — or better — than humans at some things. Businesses should now focus on incorporating the technology into work processes and preparing employees, he said, and policymakers should make sure its adoption doesn’t contribute to inequality.

Brynjolfsson has been tracking the lag between introduction of and corresponding productivity gains. United States productivity grew by about 1.3% in the past decade, he said, compared to more than 2.8% in the late 1990s and early 2000s. This productivity slowdown extends to other countries as well, according to research from the Organization for Economic Cooperation and Development. Brynjolfsson predicted a productivity J-curve, in which productivity declines after a technology is introduced and then rises when businesses have been able to integrate technologies into their workflow, a trajectory over time that has a J-shape.

“I think we’re near the bottom of that J-curve right now and we’re about to see the takeoff,” Brynjolfsson said.

The productivity paradox: why productivity declined despite new technology

Lagging productivity can be explained two main ways, Brynjolfsson said.

Mismeasurement. Productivity is traditionally measured using a country’s gross domestic product, which is based on things that are bought and sold. But many digital goods — teleconferencing, smartphone apps, Wikipedia — are available for free. Even though people get some benefit from these goods, they don’t show up in productivity statistics. The information sector’s share of the economy has barely budged since the 1980s, Brynjolfsson noted. “I think most of us realize that’s just not a real representation of what’s going on,” he said.

Happiness surveys also fail to capture the complete picture. Brynjolfsson suggested a new metric called GDP-B that would measure the benefit people gain from items. “I think it’s far from perfect, but it’s a lot more precise than happiness, and I think it’s a lot more meaningful than GDP,” he said.

Implementation and restructuring in businesses. It isn’t enough to just add new technology to an organization. Companies need a complete paradigm shift. “To get the full benefit, leaders need to rethink business processes, management practices, and employee skills,” Brynjolfsson said.

This “intangible organizational capital” is essential for companies to see benefit from technological advances, but many companies put misplaced focus on technology itself.  

“The complete reconceptualization of a business process takes a lot. More creativity, effort, and frankly, time, than simply plugging in new technologies into old business processes,” he said. “We just haven’t been doing that in most industries.” […]

Read more: mitsloan.mit.edu 

 

0 Comments

Leave a Reply

Your email address will not be published. Required fields are marked *