Pessimistic Are Best Prepared for Bad News

(p. A13) In a study published in the journal “Emotion” in February, 2016, Dr. Sweeny and colleagues at the University of California, Riverside, showed that people resort to a number of coping strategies to manage their discomfort while waiting for an outcome. Dr. Sweeny calls this “misery management.”
. . .
None of these coping mechanisms worked, according to the study. They failed to reduce the participants’ distress–and some even made it worse. . . .
A better way to wait, the researchers found, is when participants agonized through their waiting period, ruminating and feeling anxious and pessimistic rather than attempting to minimize their anxiety and worry. Those who did this responded more productively to bad news and more joyfully to good news than participants who suffered little during the wait. This is “waiting well.”

For the full commentary, see:
Elizabeth Bernstein. “When a Little Agonizing Helps.” The Wall Street Journal (Tues., May 23, 2017): A13.
(Note: ellipses added.)
(Note: the online version of the commentary has the date May 22, 2017, and has the title “How to Manage a Long Wait for News.”)

The paper co-authored by Sweeney, and mentioned above, is:
Sweeny, Kate, Chandra A. Reynolds, Angelica Falkenstein, Sara E. Andrews, and Michael D. Dooley. “Two Definitions of Waiting Well.” Emotion 16, no. 1 (Feb. 2016): 129-43.

Higher-Paid Finance Jobs Moving from NYC and San Francisco to Phoenix, Salt Lake City, and Dallas

FinanceJobsMigrateFromNYCandSF2017-08-15.pngSource of graph: online version of the WSJ article quoted and cited below.

(p. B1) Traditional finance hubs have yet to recover all the jobs lost during the recession, but the industry is booming in places like Phoenix, Salt Lake City and Dallas. The migration has accelerated as investment firms face declining profitability and soaring real estate costs.
. . .
“San Francisco is a wonderful place, but unfortunately it’s an expensive place from a real estate standpoint,” said Brian McDonald, a senior vice president for Schwab. “So we had to identify other places where we could make things work.”
While the finance industry has been relocating entry-level jobs since the late 1980s, today’s moves are claiming higher-paid jobs in human resources, compliance and asset management, chipping away at New York City’s middle class, said (p. B2) Kathryn Wylde, president and chief executive of the Partnership for New York City, a nonprofit that represents the city’s business leadership.
“This industry isn’t just a bunch of rich Wall Street guys,” Ms. Wylde said. “It’s a big source of employment that’s disappearing from New York.”

For the full story, see:
Asjylyn Loder. “Wall Street’s New Frontier.” The Wall Street Journal (Thurs., JULY 27, 2017): B1-B2.
(Note: ellipsis added.)
(Note: the online version of the story has the date JULY 26, 2017, and has the title “Passive Migration: Denver Wins Big as Financial Firms Relocate to Cut Costs.”)

Seattle Increase in Minimum Wage Results in Fewer Hours Worked, and Lower Incomes

(p. A13) By now you have read 15 articles on the Seattle minimum-wage fiasco. Since the city boosted its local minimum from $9.47 in 2014 to $13 last year (on its way to $15), a detailed investigation by University of Washington economists finds that beneficiaries actually saw their incomes fall by a net $125 a month because employers cut their hours.
. . .
The impetus came from people who don’t actually earn the minimum wage–labor-union leaders and think-tankers and activist organizations.
. . .
Organizers look fondly to Denmark, where a McDonald’s line worker receives $41,000 a year and five weeks of paid vacation. As the Atlantic put it two years ago, “Unionizing workers at McDonald’s and other fast-food chains might be a long shot, but if it succeeds, it might help lift a million or more workers into the middle class (or at least into the lower middle class) and create a model for low-wage workers in other industries.”
This sounds pretty but is misleading in a fundamental way. The workers a McDonald’s franchise would hire at $15 an hour are different from those it would hire at $8.29, the average earned by a fast-food worker today.
Costs would go up. The industry would likely shrink, it would likely replace workers with automation, but it would still create jobs at $15 an hour for people whose productivity can justify $15 an hour. The people who work at McDonald’s today, typically, would already be earning $15 an hour somewhere else if their productivity could justify $15 an hour.
Everybody needs to start somewhere, including the unskilled and those who lack a work history. Some need a job that doesn’t demand much of them. They have other obligations. They accept less pay to maximize flexibility and freedom from responsibility. They don’t plan to make a career of it. The fast-food industry in America is built on such people.

For the full commentary, see:
Holman W. Jenkins, Jr. “Seattle Aims at McDonald’s, Hits Workers.” The Wall Street Journal (Sat., July 1, 2017): A13.
(Note: ellipses added.)
(Note: the online version of the commentary has the date June 30, 2017.)

The Seattle minimum wage paper, mentioned above, is:
Jardim, Ekaterina, Mark C. Long, Robert Plotnick, Emma van Inwegen, Jacob Vigdor, and Hilary Wething. “Minimum Wage Increases, Wages, and Low-Wage Employment: Evidence from Seattle.” National Bureau of Economic Research Working Paper Series, # 23532, June 2017.

“Splendid Tutorial” of Bitcoin, Distributed Ledgers, and Smart Contracts

(p. A13) ‘The future is already here–it’s just not very evenly distributed.” The aphorism coined by novelist William Gibson explains why Andrew McAfee and Erik Brynjolfsson’s tour of the technologies that are shaping the future of business, “Machine, Platform, Crowd: Harnessing Our Digital Future,” contains sights that are already familiar and others that are not. This is a book for managers whose companies sit well back from the edge and who would like a digestible introduction to technology trends that may not have reached their doorstep–yet.
. . .
In the penultimate chapter, the authors present a splendid tutorial on things that are too new for most civilians to have gained a good understanding of–cryptocurrencies like Bitcoin, distributed ledgers, and smart contracts. The authors present the theoretical possibility that conventional contracts and the human handling of disputes could be rendered obsolete by dense networks of sensors in the physical world and extremely detailed contracts anticipating all contingencies so that machines alone can handle enforcement. But they show that computing power, however much it grows, seems unlikely to replace the human component for dispute resolution.

For the full review, see:
Randall Stross. “BOOKSHELF; The Future On Fast Forward; GE used ‘crowdfunding’ to gauge interest in a new ice maker. McDonald’s has begun adding self-service ordering in all its U.S. locations..” The Wall Street Journal (Thurs., July 6, 2017): A13.
(Note: ellipsis added.)
(Note: the online version of the review has the date July 5, 2017.)

The book under review, is:
McAfee, Andrew, and Erik Brynjolfsson. Machine, Platform, Crowd: Harnessing Our Digital Future. New York: W. W. Norton & Company, 2017.

Some New Jobs Require Same Skills as Old Jobs Did

(p. B1) . . . many of the skills needed to do fading jobs are applicable to growing jobs.
. . .
(p. B2) A New York Times review of the activities and skills that jobs entail, based on the Labor Department’s O*Net database, shows how much overlap there is between many seemingly dissimilar occupations. Service industry jobs, for example, require social skills and experience working with customers — which also apply to sales and office jobs.
. . .
. . . , employers hire based on credentials that job applicants can’t change — a college degree or previous job title — rather than assessing the skills an applicant has developed, said Mr. Auguste, who was an economic adviser in the Obama administration. He said the approach should instead be, “If you learned it at Harvard or Cal State Northridge or on the job as a secretary or in the Navy or as a volunteer, awesome.”

For the full commentary, see:
CLAIRE CAIN MILLER and QUOCTRUNG BUI. “The Upshot; Old Skills, New Career.” The New York Times (Fri., JULY 28, 2017): B1-B2.
(Note: ellipses added.)
(Note: the online version of the commentary has the date JULY 27, 2017, and has the title “The Upshot; Switching Careers Doesn’t Have to Be Hard: Charting Jobs That Are Similar to Yours.”)

Solid Tumor Gene Therapy Studies Plod Along

(p. A1) The approval of gene therapy for leukemia, expected in the next few months, will open the door to a radically new class of cancer treatments.
Companies and universities are racing to develop these new therapies, which re-engineer and turbocharge millions of a patient’s own immune cells, turning them into cancer killers that researchers call a “living drug.” One of the big goals now is to get them to work for many other cancers, including those of the breast, prostate, ovary, lung and pancreas.
“This has been utterly transformative in blood cancers,” said Dr. Stephan Grupp, director of the cancer immunotherapy program at the Children’s Hospital of Philadelphia, a professor of pediatrics at the University of Pennsylvania and a leader of major studies. “If it can start to work in solid tumors, it will be utterly transformative for the whole field.”
But it will take time to find that out, he said, at least five years.

For the full story, see:

DENISE GRADY. “Companies Rush to Develop ‘Utterly Transformative’ Gene Therapies.” The New York Times (Mon., JULY 24, 2017): A1 & A17.

(Note: the online version of the story has the date JULY 23, 2017, and has the title “Racing to Alter Patients’ Cells To Kill Cancer.”)

A.I. “Continues to Struggle in the Real World”

The passages quoted below are authored by an NYU professor of psychology and neural science.

(p. 6) Artificial Intelligence is colossally hyped these days, but the dirty little secret is that it still has a long, long way to go. Sure, A.I. systems have mastered an array of games, from chess and Go to “Jeopardy” and poker, but the technology continues to struggle in the real world. Robots fall over while opening doors, prototype driverless cars frequently need human intervention, and nobody has yet designed a machine that can read reliably at the level of a sixth grader, let alone a college student. Computers that can educate themselves — a mark of true intelligence — remain a dream.

Even the trendy technique of “deep learning,” which uses artificial neural networks to discern complex statistical correlations in huge amounts of data, often comes up short. Some of the best image-recognition systems, for example, can successfully distinguish dog breeds, yet remain capable of major blunders, like mistaking a simple pattern of yellow and black stripes for a school bus. Such systems can neither comprehend what is going on in complex visual scenes (“Who is chasing whom and why?”) nor follow simple instructions (“Read this story and summarize what it means”).
Although the field of A.I. is exploding with microdiscoveries, progress toward the robustness and flexibility of human cognition remains elusive. Not long ago, for example, while sitting with me in a cafe, my 3-year-old daughter spontaneously realized that she could climb out of her chair in a new way: backward, by sliding through the gap between the back and the seat of the chair. My daughter had never seen anyone else disembark in quite this way; she invented it on her own — and without the benefit of trial and error, or the need for terabytes of labeled data.
Presumably, my daughter relied on an implicit theory of how her body moves, along with an implicit theory of physics — how one complex object travels through the aperture of another. I challenge any robot to do the same. A.I. systems tend to be passive vessels, dredging through data in search of statistical correlations; humans are active engines for discovering how things work.

For the full commentary, see:
GARY MARCUS. “Gray Matter; A.I. Is Stuck. Let’s Unstick It.” The New York Times, SundayReview Section (Sun., JULY 30, 2017): 6.
(Note: the online version of the commentary has the date JULY 29, 2017, and has the title “Gray Matter; Artificial Intelligence Is Stuck. Here’s How to Move It Forward.”)