AI and the productivity paradox – Irving Wladawsky-Berger

MIT Sloan Visiting Lecturer Irving Wladawsky-Berger

MIT Sloan Visiting Lecturer Irving Wladawsky-Berger

From The Wall Street Journal

Artificial intelligence is now applied to tasks that not long ago were viewed as the exclusive domain of humans, matching or surpassing human level performance. But, at the same time, productivity growth has significantly declined over the past decade, and income has continued to stagnate for the majority of Americans. This puzzling contradiction is addressed in “Artificial Intelligences and the Modern Productivity Paradox,” a working paper recently published by the National Bureau of Economic Research.

As the paper’s authors, MIT professor Erik Brynjolfsson, MIT PhD candidate Daniel Rock and University of Chicago professor Chad Syverson, note: “Aggregate labor productivity growth in the U.S. averaged only 1.3% per year from 2005 to 2016, less than half of the 2.8% annual growth rate sustained from 1995 to 2004… What’s more, real median income has stagnated since the late 1990s and non-economic measures of well-being, like life expectancy, have fallen for some groups.”

After considering four potential explanations, the NBER paper concluded that there’s actually no productivity paradox. Given the proper context, there are no inherent inconsistencies between having both transformative technological advances and lagging productivity. Over the past two centuries we’ve learned that there’s generally a significant time lag between the broad acceptance of new technology-based paradigms and the ensuing economic transformation and institutional recomposition. Even after reaching a tipping point of market acceptance, it takes considerable time, often decades, for the new technologies and business models to be widely embraced by companies and industries across the economy, and only then will their benefits follow, including productivity growth. The paper argues that we’re precisely in such an in-between period.

Let me briefly describe the four potential explanations explored in the paper: false hopes, mismeasurements, concentrated distribution, and implementation and restructuring lags.

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Artificial intelligence and the future of work – Thomas Kochan

MIT Sloan Professor Thomas Kochan

MIT Sloan Professor Thomas Kochan

From InfoTechnology

Artificial intelligence is quickly coming of age and there remain lingering questions about how we will manage this change.

AI will eliminate some jobs, there’s no question, but it will also create some new ones. So the first question we will face as business people, workers and citizens is about balance: are we going to create more jobs than we eliminate or not?

The second and much more fundamental question is: how are we going to proactively manage our AI investments so we can use AI to create new jobs or career opportunities for the future? And how will we make sure those jobs reach out to various sectors of our society increasing our overall wealth and well being and not overly increasing the inequities that already exist in our society.

I believe if we think about it strategically and if we engage more people in the design of AI systems, we’ll be able to make this transition successfully. It will require a proactive strategy. The American public and people all over the world have been shown the negative consequences of not being proactive—take global trade for example. The benefits of global trade have not been widely shared and we are now witnessing the effects of the anger and frustrations this has produced in the movement to more extreme politics and the deeper social divisions laid bare by recent events. We can’t make the same mistake about the future developments of technology.

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Beer’s role in innovation – Joe Hadzima

Joe Hadzima,
MIT Sloan Senior Lecturer

From Huffington Post

Many great—or seemingly great—ideas come to fruition during the course of drinking a beer. When you’re out with the guys (or girls), one or two cold ones could have you rhapsodizing about how you’re going to change the world. This is most likely when self-lowering toilet seats, automatic pet petters, and self-twirling ice cream cones were all dreamed into existence.

As great as these and other inventions are, we’re not sure beer had any role in their creation. But has beer had a role in actual innovation?

Self-driving cars are all the rage in the news lately, with Google and Uber fighting it out over patents and racing to the front of the line for consumer release. While they were focused on cars for the everyday driver, the first self-driving truck delivered 50,000 cans of Budweiser 120 miles in Colorado.

That’s right. The first self-driven truck was used to deliver beer.

Budweiser has come a long way since the days of the horse and cart, right? In the first days of beer delivery, customers only had access because their drink of choice was brought daily by horse and wagon.

You’re probably familiar with the Clydesdales, still often used in Budweiser commercials to tug at heartstrings. These horses were bred by farmers along the banks of the River Clyde in Lanarkshire, Scotland. The Great Flemish Horse was the forerunner of the Clydesdale, which was bred to pull loads of more than one ton at a walking speed of five miles per hour. While that kind of pulling power was amazing during those days, it was still slow and expensive. Each hitch horse needed 20 to 25 quarts of whole grains, minerals and vitamins, 50 to 60 pounds of hay, and 30 gallons of water per day.

Is it any wonder that Anheuser Busch was the exclusive US licensee of the Rudolph Diesel patents? One might assume Ford or the railroad would have been first on board with the development of diesel powered trucks, but it was actually beer.

Knowing how much was needed to keep those magnificent horses healthy and hardy, it seems diesel was a logical next step. This is a classic example of early adopter customers driving a new technology.

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Watch Now: “The Truth About Fake News” with Sinan Aral and Tim O’Reilly

Sinan Aral, MIT Sloan David Austin Professor of Management

Our latest installment of the MIT Sloan Experts Series includes a conversation about fake news with Sinan Aral, David Austin Professor of Management and author of the forthcoming book, The Hype Machine. We’ll discuss insights from the latest research from Aral and his co-researchers Soroush Vosoughi and Deb Roy of the MIT Media Lab which overturns conventional wisdom about how misinformation spreads, what causes it to spread so fast, and who—or what—is spreading it.

It is the largest study of its kind about fake news and is featured in the latest issue of Science, “The Spread of True and False News Online”,  March 9, 2018.

Tim O’Reilly, the founder, CEO, and Chairman of O’Reilly Media, and the author of many books including, WTF: What’s the Future and Why It’s Up to Us, also appears on the program to discuss possible technological and algorithmic solutions.

Watch the show here:

 

 

“The Future of American Innovation”– a podcast with David Schmittlein

MIT Sloan Dean David Schmittlein

MIT Sloan Dean David Schmittlein

MIT Sloan’s David Schmittlein appeared on CEO Global Foresight to discuss how the United States is leading world innovation in life sciences, information technology, and energy.

The segment was recently made available as an 8-minute podcast on the Innovation Gamechangers podcast, available on iTunes.

Dean Schmittlein also discusses innovation clusters and how the MIT community encourages a culture of collaboration and action learning. The program also includes interviews DARPA director Arati Prabhakar and Carl Dietrich, an MIT alumnus and CEO of flying car company Terrafugia.

Listen to Innovation Gamechangers podcast, available on iTunes.

David Schmittlein is the John C Head III Dean and Professor of Marketing at the MIT Sloan School of Management.