Category: Labor Economics

“Charging Scooters Is a Great Job for Independent-Minded Entrepreneurs”

(p. 1B) Downtown Omaha resident Rob Luhrs spends his early mornings and late nights hunting for scooters.

Luhrs, 41, is a “juicer” of Lime scooters (“Lime juicer” — get it?) who charges scooters and then sets them out again around town. He said he makes about $60 a day, seven days a week, doing the work. During the College World Series, he said, he was making between $80 and $90 a day.

Luhrs also is an instructor of Brazilian jiu-jitsu and a part-time real estate broker who works for a grocery delivery service. But he said he hopes to make charging scooters his primary source of income.

(p. 2B) “I want to work when I want to,” he said. “When I want to take a day off, I don’t want anybody complaining about it, and if I work extra hard, I want to get paid more. I can’t just go apply to somewhere and get that job.”

. . .

Luhrs said charging scooters is a great job for “independent-minded entrepreneurs.”

“For me personally, I’m willing to spend time during the day picking up scooters and make it a full-time gig,” he said. “I see other people out there, during the daytime, picking up scooters, so I know that they’re trying to make it a full-time gig, too.”

For the full story, see:

Adam Cole. “Lime ‘Juicer’ Doesn’t Feel Squeezed by Late Hours Charging Scooters.” Omaha World-Herald (Thursday, Jul 4, 2019): 1B-2B.

(Note: ellipsis added.)

(Note: the online version of the story has the date Jul 3, 2019, and has the title “Unorthodox working hours don’t steer Lime ‘juicer’ away from job charging scooters in Omaha.”)

75% “of All Wealth Is Created Anew in Each Generation”

(p. A17) Despite the liberal background of the author, however, “A Century of Wealth in America” offers comfort and support to those who favor less wealth taxation. A core element of Mr. Piketty’s indictment of contemporary wealth inequality was his claim that inheritance is the major source of wealth; he estimated that, given the slower economic growth that most economists anticipate in the future, inherited wealth would soon constitute 90% of wealth in economies such as that of the United States. But Mr. Wolff finds that, for modern America, wealth inheritance explains a much more modest share of private wealth: In 1989-2013, it was 23% on average. In other words, more than three-quarters of all wealth is created anew in each generation in the U.S. . . .

Even more surprising, inherited wealth is much more important in the lives of those who have relatively little wealth than it is in the lives of the super rich. For the top 1% of wealth holders from 1989 to 2013, inherited wealth accounted for only 17% of their assets. (The 1%, in this analysis, is an overwhelmingly self-made group.) By contrast, for those with assets of just $25,000-$50,000, inherited wealth accounted for 52% of their worth.

As a bizarre consequence of this pattern, African-Americans, who have low levels of net worth on average, are the social group for which inherited wealth represents the largest share of their net worth. Another odd implication is that inheritances tend to make overall wealth-holding more equal. Were inherited wealth to be completely abolished, the wealth of the poor would decline more than that of the rich. Inherited wealth is the great equalizer. Who knew?

. . .

. . . , Mr. Wolff calculates that the rich are not systematically generating higher returns on their assets than more modest wealth holders. The top 1% had a real return on net worth of around 3% over the 30 years from 1983 to 2013—the same return as the average wealth holder.

For the full review, see:

Gregory Clark. “BOOKSHELF; How the Richest Got That Way; In the U.S. more than three-quarters of all wealth is created anew in each generation, and the ‘1%’ is an overwhelmingly self-made group.” The Wall Street Journal (Tuesday, December 12, 2017): A17.

(Note: ellipses added.)

(Note: the online version of the review has the date Dec. 11, 2017, and has the title “BOOKSHELF; Review: How the Richest Got That Way; In the U.S. more than three-quarters of all wealth is created anew in each generation, and the ‘1%’ is an overwhelmingly self-made group.”)

The book under review is:

Wolff, Edward N. A Century of Wealth in America. Cambridge, MA: Belknap Press, 2017.

Regulators Allowed New York City to Exploit Taxi Medallion Buyers

(p. A1) . . . The New York Times published a two-part investigation revealing that a handful of taxi industry leaders artificially inflated the price of a medallion — the coveted permit that allows a driver to own and operate a cab — and made hundreds of millions of dollars by issuing reckless loans to low-income buyers.

The investigation also found that regulators at every level of government ignored warning signs, and the city fed the frenzy by selling medallions and promoting them in ads as being “better than the stock market.”

The price of a medallion rose to more than $1 million before crashing in late 2014, which left borrowers with debt they had little hope of repaying. More than 950 medallion owners have filed for bankruptcy, (p. A20) and thousands more are struggling to stay afloat.

For the full story, see:

Niraj Chokshi. “New York’s Top Lawyer Begins Inquiry Into Reckless Taxi Loans.” The New York Times (Tuesday, MAY 21, 2019): A1 & A20.

(Note: ellipsis added.)

(Note: the online version of the story has the date MAY 20, 2019, and has the title “Inquiries Into Reckless Loans to Taxi Drivers Ordered by State Attorney General and Mayor.” Where the online version includes a few extra words, or slightly different wording, the quotes above follow the online version.)

Amazon Will Fund Employees to Quit and Found Delivery Startups

(p. B6) First, Amazon made two-day shipping the norm. Now, as it aims to cut that to a single day, the company is encouraging its employees to quit and start their own delivery businesses.

Under a new incentive program, announced on Monday, Amazon said that it would fund up to $10,000 in start-up costs and provide three months of pay to any employee who decides to make the jump.

The new incentives build on a program the company started last June to encourage anyone, employee or not, to get into the competitive business of last-mile package delivery.

“We’ve heard from associates that they want to participate in the program but struggled with the transition,” Dave Clark, senior vice president for worldwide operations, said in a statement. “Now we have a path.”

For the full story, see:

Niraj Chokshi. “Amazon Has A Novel Idea For Delivery.” The New York Times (Tuesday, MAY 14, 2019): B6.

(Note: the online version of the story has the date MAY 13, 2019, and has the title “Amazon Will Pay Workers to Quit and Start Their Own Delivery Businesses.”)

Facebook Hires More Humans to Do What Its AI Cannot Do

(p. B5) If telling us what to look at next is Facebook’s raison d’être, then the AI that enables that endless spoon-feeding of content is the company’s most important, and sometimes most controversial, intellectual property.

. . .

At the same time, the company’s announcement that it is hiring more humans to screen ads and filter content shows there is so much essential to Facebook’s functionality that AI alone can’t accomplish.

AI algorithms are inherently black boxes whose workings can be next to impossible to understand—even by many Facebook engineers.

For the full commentary, see:

Christopher Mims. “KEYWORDS; The Algorithm Driving Facebook.” The Wall Street Journal (Monday, October 23, 2017): B1 & B5.

(Note: ellipses added.)

(Note: the online version of the commentary has the date Oct. 22, 2017, and the title “KEYWORDS; How Facebook’s Master Algorithm Powers the Social Network.”)

Much of the “Intelligence” in Artificial Intelligence Is Human, Not Artificial

(p. B5) Everything we’re injecting artificial intelligence into—self-driving vehicles, robot doctors, the social-credit scores of more than a billion Chinese citizens and more—hinges on a debate about how to make AI do things it can’t, at present.

. . .

On one side of this debate are the proponents of “deep learning”—an approach that, since a landmark paper in 2012 by a trio of researchers at the University of Toronto, has exploded in popularity.

. . .

On the other side of this debate are researchers such as Gary Marcus, former head of Uber Technologies Inc.’s AI division and currently a New York University professor, who argues that deep learning is woefully insufficient for accomplishing the sorts of things we’ve been promised. It could never, for instance, be able to usurp all white collar jobs and lead us to a glorious future of fully automated luxury communism.

Dr. Marcus says that to get to “general intelligence”—which requires the ability to reason, learn on one’s own and build mental models of the world—will take more than what today’s AI can achieve.

“That they get a lot of mileage out of [deep learning] doesn’t mean that it’s the right tool for theory of mind or abstract reasoning,” says Dr. Marcus.

To go further with AI, “we need to take inspiration from nature,” say Dr. Marcus. That means coming up with other kinds of artificial neural networks, and in some cases giving them innate, pre-programmed knowledge—like the instincts that all living things are born with.

. . .

Until we figure out how to make our AIs more intelligent and robust, we’re going to have to hand-code into them a great deal of existing human knowledge, says Dr. Marcus. That is, a lot of the “intelligence” in artificial intelligence systems like self-driving software isn’t artificial at all. As much as companies need to train their vehicles on as many miles of real roads as possible, for now, making these systems truly capable will still require inputting a great deal of logic that reflects the decisions made by the engineers who build and test them.

For the full commentary, see:

Christopher Mims. “KEYWORDS; Should Artificial Intelligence Copy the Brain?” The Wall Street Journal (Saturday, October 26, 2017): B5.

(Note: ellipses added.)

(Note: the online version of the commentary has the same date as the print version, and has the title “KEYWORDS; Should Artificial Intelligence Copy the Human Brain?”)

Big, Frequent Meetings Are Unproductive and Crowd Out Deep Thought

(p. 7) To figure out why the workers in Microsoft’s device unit were so dissatisfied with their work-life balance, the organizational analytics team examined the metadata from their emails and calendar appointments. The team divided the business unit into smaller groups and looked for differences in the patterns between those where people were satisfied and those where they were unhappy.

It seemed as if the problem would involve something about after-hours work. But no matter how Ms. Klinghoffer and Mr. Fuller crunched the data, there weren’t any meaningful correlations to be found between groups that had a lot of tasks to do at odd times and those that were unhappy. Gut instincts about overwork just weren’t supported by the numbers.

The two kept iterating until something emerged in the data. People in Mr. Ostrum’s division were spending an awful lot of time in meetings: an average of 27 hours a week. That wasn’t so much more than the typical team at Microsoft. But what really distinguished those teams with low satisfaction scores from the rest was that their meetings tended to include a lot of people — 10 or 20 bodies arrayed around a conference table coordinating plans, as opposed to two or three people brainstorming ideas.

The issue wasn’t that people had to fly to China or make late-night calls. People who had taken jobs requiring that sort of commitment seemed to accept these things as part of the deal. The issue was that their managers were clogging their schedules with overcrowded meetings, reducing available hours for tasks that rewarded more focused concentration — thinking deeply about trying to solve a problem.

Data alone isn’t insight. But once the Microsoft executives had shaped the data into a form they could understand, they could better question employees about the source of their frustrations. Staffers’ complaints about spending evenings and weekends catching up with more solitary forms of work started to make more sense. Now it was clearer why the first cuts of the data didn’t reveal the problem. An engineer sitting down to do individual work for several hours on a Saturday afternoon probably wouldn’t bother putting it on her calendar, or create digital exhaust in the form of trading emails with colleagues during that time.

Anyone familiar with the office-drone lifestyle might scoff at what it took Microsoft to get here. Does it really take that much analytical firepower, and the acquisition of an entire start-up, to figure out that big meetings make people sad?

For the full story, see:

Neil Irwin. “How to Win at Winner-Take-All.” The New York Times, SundayBusiness Section (Sunday, June 15, 2019): 1 & 6-7.

(Note: the online version of the story has the date June 15, 2019, and has the title “The Mystery of the Miserable Employees: How to Win in the Winner-Take-All Economy.”)

The article quoted above, is adapted from:

Irwin, Neil. How to Win in a Winner-Take-All World: The Definitive Guide to Adapting and Succeeding in High-Performance Careers. New York: St. Martin’s Press, 2019.

Robots Relieve Restaurant Workers of Small, Mundane, Tedious Tasks

(p. A1) John Miller, chief executive and founder of CaliBurger LLC, finds it harder to find employees these days. His solution is Flippy, a robot that turns the burgers and cleans the hot, greasy grill.

The chain plans to install Flippy in up to ten of its 50 restaurants by year end. CaliBurger doesn’t intend to kick humans to the curb as a result. Flippy will handle the gruntwork, freeing employees to tidy the dining rooms and refill drinks, less arduous work that might make it easier to recruit and retain workers.

“We’re a long way from teaching a robot to walk the restaurant and do those things,” Mr. Miller said.

Experts have warned for years that robots will replace humans in restaurants. Instead, a twist on that prediction is unfolding. Amid the lowest unemployment in years, fast-food restaurants are turning to machines—not to get rid of workers, but because they can’t find enough.

. . .

(p. A10) Dunkin’ conducted focus groups with former employees to pinpoint the mundane tasks that made them want to leave and geared automation around that.

Workers used to create thousands of hand-written labels daily for everything from coffee to cheese expirations. Last year, Dunkin’ installed small terminals that print out expiration times.

Brewing a single pot involved grinding and weighing coffee and comparing its fineness and coarseness to a perfect sample. Now, some Dunkin’ shops use digital refractometers to determine if coffee meets specifications.

. . .

Alexandra Guajardo, the morning shift leader at a Dunkin’ Donuts shop in Corona, Calif. said she’s likely to stick with the job longer now than she otherwise would have.

“I don’t have to constantly be worried about other smaller tasks that were tedious,” she said. “I can focus on other things that need my attention in the restaurant.”

Mr. Murphy said he can’t see a time when a Dunkin’ Donuts shop is fully automated. The company experimented with a robot barista nearly two years ago at an innovation lab in Massachusetts. The robot did fine at making simple drinks, but couldn’t grasp custom orders, such as “light sugar.”

The machine also required a lot of cleaning and maintenance, and at up to $100,000 per robot, Mr. Murphy said he couldn’t see a return on the investment.

For the full story, see:

Julie Jargon and Eric Morath. “Short of Workers, Robots Man the Grill.” The Wall Street Journal (Monday, June 25, 2018): A1 & A10.

(Note: ellipses added.)

(Note: the online version of the story has the date June 24, 2018, and the title “Short of Workers, Fast-Food Restaurants Turn to Robots.”)

More Workers Satisfied with Jobs Than in Recent Years

(p. B6) Just more than half of U.S. workers—51%—said they were satisfied with their jobs in 2017, the highest level since 2005, according to a new report from The Conference Board, a business-research group.

Over the past seven years, Americans report feeling better about their pay along with a greater sense of job security, both features of an economy with a low unemployment rate and a long decline in layoffs. In July [2018], jobless claims continued an extended post-recession slide and hit their lowest level in nearly 50 years.

For the full story, see:

Weber, Lauren. “Fewer Workers Move for New Jobs.” The Wall Street Journal (Thursday, August 30, 2018): B6.

(Note: bracketed year added.)

(Note: the online version of the story has the date Aug. 29, 2018, and the title “Fewer Americans Uproot Themselves for a New Job.”)

Job-Related Relocations Declining

(p. A1) Fewer U.S. workers are moving around the country to seek new job opportunities, as changing family ties and more openings near home make people less willing to uproot their lives for work.

About 3.5 million people relocated for a new job last year, according to U.S. census data, a 10% drop from 3.8 million in 2015. The numbers have fluctuated between 2.8 million and 4.5 million since the government started tracking annual job-related relocations in 1999—but have been trending lower overall, even as the U.S. population grew by nearly 20% over that stretch.

Experts cite a number of factors that in some periods have kept people in one place, including a depressed value for their home or limited job openings. In the current strong economy, real-estate values have rebounded, but that has made housing costs prohibitively high in some regions where jobs are abundant, such as major East and West Coast cities.

For the full story, see:

Rachel Feintzeig and Lauren Weber. “Fewer Workers Move for New Jobs.” The Wall Street Journal (Monday, August 20, 2018): A1-A2.

(Note: the online version of the story did not give a date, and has the title “Fewer Americans Uproot Themselves for a New Job.”)

If You Have Lost Your Spouse, Chatbot Asks: “What’s Your Tracking Number?”

(p. B4) When LivePerson Inc. started piloting chatbots in early 2018, one of them made an embarrassing faux pas, assuming a client’s customer was talking about a lost package after mentioning losing a spouse.

“And the bot goes, ‘All right, great, I can help you with that. What’s your tracking number?’” said Malik Jenkins, an employee at the artificial-intelligence software company who was involved in the pilots. He said the issue was immediately flagged by someone at the client company and his team tweaked the bot to avoid such responses in the future.

For the full story, see:

Jared Council. “A Human Touch Is Given to Chatbots.” The Wall Street Journal (Thursday, June 13, 2019): B4.

(Note: the online version of the story has the date June 12, 2019, and the title “When Chatbots Falter, Humans Steer Them the Right Way.”)