Tech innovators open the digital economy to job seekers, financially underserved – Irving Wladawsky-Berger

MIT Sloan Visiting Lecturer Irving Wladawsky-Berger

MIT Sloan Visiting Lecturer Irving Wladawsky-Berger

From The Wall Street Journal

The future of work is a prime interest of the MIT Initiative on the Digital Economy, started in 2013 by researchers Erik Brynjolfsson and Andy McAfee. To help come up with answers to questions about the impact of automation on jobs and the effects of digital innovation, the group launched the MIT Inclusive Innovation Challenge last year, inviting organizations around the world to compete in the realm of improving the economic opportunities of middle- and base-level workers.

 More than $1 million in prizes went to winners of the 2017 competition in Boston last month in four categories: Job creation and income growth, skills development and matching, technology access, and financial inclusion. Awards were funded with support from Google.org, The Joyce Foundation, software firm ISN, and ISN President and CEO Joseph Eastin.

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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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Artificial intelligence, predictive analytics: How MBA campus recruiting is changing – Jean Ann Schulte

MIT Sloan Director of Employer Relations & Recruiting Services Jean Ann Schulte

From Business Because

Traditionally, recruiting is an on-campus, very structured, time-intensive, and expensive process. Students and employers learn about each other through a series of organized activities like mixers, presentations, coffee chats, treks, interview prep sessions, invite-only dinners, and interviews.

While the largest, most prominent companies continue to host a full schedule of events at their preferred schools, new approaches are emerging.

Employers seek to cut the cost and time required to hire, while increasing the predictability of a new hire’s success. Students have less time and more employment options. Given the rising demand for talent, they expect a more personalized approach and put greater emphasis on cultural fit.

Enter Artificial Intelligence (AI) and predictive analytics. Together, they automate much of the process of sourcing and engaging qualified, interested candidates. It’s a hot field—the number of VC-backed startups focused on the hiring process and employment has increased six-fold in 10 years, with more than 100 companies entering the space in each of the past three years.

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Good managers, not machines, drive productivity growth – John Van Reenen

MIT Sloan Professor John Van Reenen

From Bloomberg View

When people discuss what drives long-run productivity, they usually focus on technical change. But productivity is about more than robots, new drugs and self-driving vehicles. First, if you break down the sources of productivity across nations and firms there is a large residual left over (rather inelegantly named “Total Factor Productivity” or TFP for short). And observable measures of technology can only account for a small fraction of this dark matter.

On top of this, a huge number of statistical analyses and case studies of the impact of new technologies on firm performance have shown that there is a massive variation in its impact. What’s much more important than the amount spent on fancy tech is the way managerial practices are used in the firms that implement the changes.

Although there is a tradition in economics starting with the 19th-century American economist Francis Walker on the importance of management for productivity, it has been largely subterranean. Management is very hard to measure in a robust way, so economists have been happy to delegate this task to others in the case study literature in business schools.

Managers are more frequently the butt of jokes from TV shows like “The Office” to “Horrible Bosses,” than seen as drivers of growth. But maybe things are now changing.

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