Category: Labor Economics

The Most Powerful A.I. Systems Still Do Not Understand, Have No Common Sense, and Cannot Explain Their Decisions

(p. B1) David Ferrucci, who led the team that built IBM’s famed Watson computer, was elated when it beat the best-ever human “Jeopardy!” players in 2011, in a televised triumph for artificial intelligence.

But Dr. Ferrucci understood Watson’s limitations. The system could mine oceans of text, identify word patterns and predict likely answers at lightning speed. Yet the technology had no semblance of understanding, no human-style common sense, no path of reasoning to explain why it reached a decision.

Eleven years later, despite enormous advances, the most powerful A.I. systems still have those limitations.

. . .

(p. B7) The big, so-called deep learning programs have conquered tasks like image and speech recognition, and new versions can even pen speeches, write computer programs and have conversations.

They are also deeply flawed. They can generate biased or toxic screeds against women, minorities and others. Or occasionally stumble on questions that any child could answer. (“Which is heavier, a toaster or a pencil? A pencil is heavier.”)

“The depth of the pattern matching is exceptional, but that’s what it is,” said Kristian Hammond, an A.I. researcher at Northwestern University. “It’s not reasoning.”

Elemental Cognition is trying to address that gap.

. . .

Eventually, Dr. Ferrucci and his team made progress with the technology. In the past few years, they have presented some of their hybrid techniques at conferences and they now have demonstration projects and a couple of initial customers.

. . .

The Elemental Cognition technology is largely an automated system. But that system must be trained. For example, the rules and options for a global airline ticket are spelled out in many pages of documents, which are scanned.

Dr. Ferrucci and his team use machine learning algorithms to convert them into suggested statements in a form a computer can interpret. Those statements can be facts, concepts, rules or relationships: Qantas is an airline, for example. When a person says “go to” a city, that means add a flight to that city. If a traveler adds four more destinations, that adds a certain amount to the cost of the ticket.

In training the round-the-world ticket assistant, an airline expert reviews the computer-generated statements, as a final check. The process eliminates most of the need for hand coding knowledge into a computer, a crippling handicap of the old expert systems.

Dr. Ferrucci concedes that advanced machine learning — the dominant path pursued by the big tech companies and well-funded research centers — may one day overcome its shortcomings. But he is skeptical from an engineering perspective. Those systems, he said, are not made with the goals of transparency and generating rational decisions that can be explained.

“The big question is how do we design the A.I. that we want,” Dr. Ferrucci said. “To do that, I think we need to step out of the machine-learning box.”

For the full story, see:

Steve Lohr. “You Can Lead A.I. to Answers, but Can You Make It Think?” The New York Times (Monday, August 29, 2022): B1 & B7.

(Note: ellipses added.)

(Note: the online version of the story was updated Sept. 8, 2022, and has the title “One Man’s Dream of Fusing A.I. With Common Sense.”)

Communists Renege on “Implicit Bargain” to Give Chinese “Stability and Comfort” in Exchange for Lost Freedom

(p. 1) After violently crushing pro-democracy demonstrations at Tiananmen Square in 1989, Beijing struck an implicit bargain: In exchange for limitations on political freedoms, the (p. 9) people would get stability and comfort.

But now the stability and comfort have dwindled, even as the limitations have grown.

. . .

Atop a hill in Shenzhen’s Lianhuashan Park stands a 20-foot bronze statue of Deng Xiaoping. Mr. Deng, the leader who pioneered China’s embrace of market forces after Mao’s death, watches over the city that is a living reminder of the country’s ability to change direction. Mr. Deng is shown in midstride, to honor his credo that opening should only accelerate.

Chen Chengzhi, 80, a retired government cadre who hikes to that statue every day for exercise, credits Mr. Deng with changing his life. Mr. Chen moved to Shenzhen in the 1980s, soon after Mr. Deng allowed economic experimentation here. The city then had just a few hundred thousand people, but Mr. Chen, who had endured famine and the Cultural Revolution, believed in Mr. Deng’s vision.

“At the end of the day, all good things in China are related to Shenzhen,” Mr. Chen said on one of his daily walks, adding that he cheered when China’s premier, Li Keqiang, visited the statue in August and pledged that China would continue opening to the world.

If it doesn’t do so, Mr. Chen said, “China will hit a dead end.”

But Mr. Li is retiring, even as the Xi Jinping era of rising state control stretches on.

For now, Mr. Chen continues climbing the hill — looking over the city that he helped build, that he believes in still.

For the full story, see:

Vivian Wang. “Covid Crackdowns Shake Chinese People’s Faith in Progress.” The New York Times, First Section (Sunday, December 4, 2022): 1 & 9.

(Note: ellipsis added.)

(Note: the online version of the story also has the date December 4, 2022, and has the title “The Chinese Dream, Denied.” The online version says that the title of the print version was “Beijing’s Bargain With Its People Is Shaken” but my National Edition of the print version had the title “Covid Crackdowns Shake Chinese People’s Faith in Progress.”)

To Force Use of Organic Farming, Government Banned Chemical Fertilizers; A Ban Which “Devastated” Crops and “Destroyed the Farmers”

(p. A6) GALENBINDUNUWEWA, Sri Lanka—For more than half a century, Pahatha Mellange Jayaappu has tilled the field on his modest farm in Sri Lanka’s agricultural heartland, unswayed by recurrent political and economic turmoil.

Now the 71-year-old is just trying to eke out enough of a harvest to feed his family after an abrupt ban on chemical fertilizers last year devastated his crops. He says he has given up on planting for profit.

“We have lived through armed insurrections and bad government policies,” Mr. Jayaappu said. “This is the worst year I’ve ever seen. They have destroyed the farmers.”

Many Sri Lankans aren’t getting enough to eat, and farmers and agricultural experts say the food shortages are set to worsen. The government reversed the ban in November and promised fresh supplies of chemical fertilizers, but farmers said many received only a small amount, and too late for the current growing season.

. . .

The ban on imports of agricultural chemicals took effect in May 2021, and the rice harvest the following March was down 40%, according to government data. Prices soared. Sri Lanka, which had been largely self-sufficient in rice, was forced to use some of its fast-dwindling foreign reserves to import the key staple. Other crops, like tea, an important foreign-exchange earner, have also suffered. In May, the country defaulted on its external debt.

. . .

Mr. Wickremesinghe was installed by Parliament last month after his predecessor, Gotabaya Rajapaksa, fled the country and resigned in the face of mass protests over fuel shortages and food prices.  . . .

Mr. Rajapaksa billed the ban as a nationwide shift to organic farming, but agricultural experts say that requires a yearslong transition. Opposition lawmakers said cutting off imports of fertilizer, which the government heavily subsidizes for farmers, was a shortsighted attempt to hold on to foreign reserves.

. . .

Farmers complained that the organic fertilizers that came on the market after the ban took effect were poor quality, full of material that wasn’t fully decomposed. And the haste of the ban left insufficient time to make their own compost, or learn how to farm organically.

For the full story, see:

Shan Li and Philip Wen. “Sri Lanka’s Farmers Struggle to Survive.” The Wall Street Journal (Saturday, August 20, 2022): A6.

(Note: ellipses added.)

(Note: the online version of the story was updated Aug. 19, 2022, and has the title “Sri Lanka’s Farmers Struggle to Feed the Country—and Themselves.”)

Productivity Increases from AI May Create New Valuable Tasks and Occupations

(p. A2) For centuries, new waves of automation have been greeted by predictions of widespread job loss and convulsive disruption. For centuries, the predictions have been wrong.

. . .

Predictions of technology’s labor-market impacts are notoriously flawed. Experiments like those involving AI often fail to replicate in the real world. Nearly two decades ago, the advent of international fiber-optic connections led some scholars to estimate a fifth of U.S. jobs, such as radiologist, could be offshored. Nothing even close to that happened. A decade ago, economists began warning that self-driving trucks would deprive millions of high-school graduates of good-paying jobs. Today, there are more truck drivers than ever and employers are begging for more.

Often, the technology isn’t good enough or human tasks are too complicated to be replaced. Regulation and inertia get in the way, so the impact unfolds over many years and can’t be detected amid countless other forces at work.

Joshua Gans, an economist specializing in AI at the University of Toronto, said: “Technological changes turn something that was scarce into something that is abundant,” and in the process, “reveal to us what the real value of that stuff is.” Journalists’ greatest value, he said, will be in asking good questions and judging the quality of the answers, not writing up the results.

Spreadsheets made math-intensive analysis easy and cheap, and as a result, led to the creation of countless new tasks and occupations. Large language models could similarly lead to an explosion in applications requiring the synthesis of large amounts of information into serviceable prose.

For the full commentary, see:

Greg Ip. “CAPITAL ACCOUNT; The Robots Have Finally Come for My Job.” The Wall Street Journal (Thursday, April 6, 2023): A2.

(Note: ellipsis added.)

(Note: the online version of the commentary has the date April 5, 2023, and has the same title as the print version.)

Milton Friedman Made the Case for Freedom to 15 Million Viewers

New York Times reviewer Szalai says that watching Milton Friedman’s “Free to Choose” documentary today is a surreal experience. To the contrary, I say that watching Milton Friedman’s documentary today is an exhilarating experience and watching the the evening news today is a surreal experience. (As a graduate student at the University of Chicago, I was in the audience for a couple of the episodes of Milton Friedman’s “Free to Choose” documentary.)

(p. C1) The documentary series “Free to Choose,” which aired on public television in 1980 and was hosted by the libertarian economist Milton Friedman, makes for surreal watching nowadays. Even if Ronald Reagan would go on to win the presidential election later that year, it was still a time when capitalism’s most enthusiastic supporters evidently felt the need to win the public over to a vision of free markets and minimal government.  . . .

They had an enormous audience: The 15 million viewers who watched the first episode saw an avuncular Friedman (diminutive and smiling), leaning casually against a chair in a Chinatown sweatshop (noisy and crowded), surrounded by women pushing fabric through clattering sewing machines. “They are like my mother,” Friedman said, gesturing at the Asian women in the room. She had worked in a factory too, after immigrating as a 14-year-old from Austria-Hungary in the late 19th century. Friedman explained that these low-wage garment workers weren’t being exploited; they were gaining a foothold in the American land of plenty. The camera then cut to a tray of juicy steaks.

For the full review, see:

Jennifer Szalai. “Sounding an Alarm Over America’s Values.” The New York Times (Saturday, February 18, 2023): C1 & C4.

(Note: ellipsis added.)

(Note: the online version of the review was updated Feb. 17, 2023, and has the title “Is the Marriage Between Democracy and Capitalism on the Rocks?”)

The book based on Milton Friedman’s documentary is:

Friedman, Milton, and Rose D. Friedman. Free to Choose: A Personal Statement. New York: Harcourt Brace Jovanovich, Inc., 1980.

Blacks Leaving New York City to Find Jobs, Housing, and Wealth

(p. A1) From 2010 to 2020, a decade during which the city’s population showed a surprising increase led by a surge in Asian and Hispanic residents, the number of Black residents decreased. The decline mirrored a national trend of younger Black professionals, middle-class families and retirees leaving cities in the Northeast and Midwest for the South.

The city’s Black population has declined by nearly 200,000 people in the past two decades, or about 9 percent. Now, about one in five residents are non-Hispanic Black, compared with one in four in 2000, according to the latest census data.

The decline is starkest among the youngest New Yorkers: The number of Black children and teenagers living in the city fell more than 19 percent from 2010 to (p. A22) 2020. And the decline is continuing, school enrollment data suggests. Schools have lost children in all demographic groups, but the loss of Black children has been much steeper as families have left and as the birthrate among Black women has decreased.

The factors propelling families . . . out of the city are myriad, including concerns about school quality, a desire to be closer to relatives and tight urban living conditions. But many of those interviewed for this article pointed to one main cause: the ever-increasing cost of raising a family in New York.

Black families drawn to opportunities in places where jobs and housing are more plentiful are finding new chances to spread out and build wealth.

For the full story, see:

Troy Closson and Nicole Hong. “A Black Exodus and Its Effect on New York City.” The New York Times (Wednesday, February 1, 2023): A1 & A22.

(Note: ellipsis added.)

(Note: the online version of the story was updated Feb. 3, 2023, and has the title “Why Black Families Are Leaving New York, and What It Means for the City.” Where there are minor differences in wording between the versions, the passages quoted above follow the online version.)

Experienced Nurses Can Be Disciplined If They Use Hunches from Clinical Observations to Override AI Protocols

(p. A1) Melissa Beebe, an oncology nurse, relies on her observation skills to make life-or-death decisions. A sleepy patient with dilated pupils could have had a hemorrhagic stroke. An elderly patient with foul-smelling breath could have an abdominal obstruction.

So when an alert said her patient in the oncology unit of UC Davis Medical Center had sepsis, she was sure it was wrong. “I’ve been working with cancer patients for 15 years so I know a septic patient when I see one,” she said. “I knew this patient wasn’t septic.”

The alert correlates elevated white blood cell count with septic infection. It wouldn’t take into account that this particular patient had leukemia, which can cause similar blood counts. The algorithm, which was based on artificial intelligence, triggers the alert when it detects patterns that match previous patients with sepsis. The algorithm didn’t explain (p. A9) its decision.

Hospital rules require nurses to follow protocols when a patient is flagged for sepsis. While Beebe can override the AI model if she gets doctor approval, she said she faces disciplinary action if she’s wrong. So she followed orders and drew blood from the patient, even though that could expose him to infection and run up his bill. “When an algorithm says, ‘Your patient looks septic,’ I can’t know why. I just have to do it,” said Beebe, who is a representative of the California Nurses Association union at the hospital.

As she suspected, the algorithm was wrong. “I’m not demonizing technology,” she said. “But I feel moral distress when I know the right thing to do and I can’t do it.”

. . .

In a survey of 1,042 registered nurses published this month by National Nurses United, a union, 24% of respondents said they had been prompted by a clinical algorithm to make choices they believed “were not in the best interest of patients based on their clinical judgment and scope of practice” about issues such as patient care and staffing.” Of those, 17% said they were permitted to override the decision, while 31% weren’t allowed and 34% said they needed doctor or supervisor’s permission.

. . .

Jeff Breslin, a registered nurse at Sparrow Hospital in Lansing, Mich., has been working at the Level 1 trauma center since 1995. He helps train new nurses and students on what signs to look for to assess and treat a critically ill or severely injured patient quickly.

“You get to a point in the profession where you can walk into a patient’s room, look at them and know this patient is in trouble,” he said. While their vital signs might be normal, “there are thousands of things we need to take into account,” he said. “Does he exhibit signs of confusion, difficulty breathing, a feeling of impending doom, or that something isn’t right?”

. . .

Nurses often describe their ability to sense a patient’s deterioration in emotional terms. “Nurses call it a ‘hunch,’ ” said Cato, the University of Pennsylvania professor who is also a data scientist and former nurse. “It’s something that causes them to increase surveillance of the patient.”

. . .

At UC Davis earlier this spring, Beebe, the oncology nurse, was treating a patient suffering from a bone cancer called myeloid leukemia. The condition fills the bones with cancer cells, “they’re almost swelling with cancer,” she said, causing excruciating pain. Seeing the patient wince, Beebe called his doctor to lobby for a stronger, longer-lasting pain killer. He agreed and prescribed one, which was scheduled to begin five hours later.

To bridge the gap, Beebe wanted to give the patient oxycodone. “I tell them, ‘Anytime you’re in pain, don’t keep quiet. I want to know.’ There’s a trust that builds,” she said.

When she started in oncology, nurses could give patients pain medication at their discretion, based on patient symptoms, within a doctor’s parameters. They gave up authority when the hospital changed its policies and adopted a tool that automated medication administration with bar-code scanners a few years ago.

In its statement, UC Davis said the medication tool exists as a second-check to help prevent human error. “Any nurse who doesn’t believe they are acting in the patient’s best interests…has an ethical and professional obligation to escalate those concerns immediately,” the hospital said.

Before giving the oxycodone, Beebe scanned the bar code. The system denied permission, adhering to the doctor’s earlier instructions to begin the longer-acting pain meds five hours later. “The computer doesn’t know the patient is in out-of-control pain,” she said.

Still, she didn’t act. “I know if I give the medication, I’m technically giving medication without an order and I can be disciplined,” she said. She watched her patient grimace in pain while she held the pain pill in her hand.

For the full story, see:

Lisa Bannon. “Nurses Clash With AI Over Patient Care.” The Wall Street Journal (Friday, June 16, 2023): A1 & A9.

(Note: ellipses added.)

(Note: the online version of the story has the date June 15, 2023, and has the title “When AI Overrules the Nurses Caring for You.”)

Did Theranos Fail Because It Had a Flat Structure or Because It Had a Hierarchy with Holmes at the Top (Or Simply Because They Failed at Something Very Hard)?

André Spicer and Elizabeth Holmes infer that Theranos failed due to its flat structure. But weren’t there some employees, such as George Shultz’s grandson, whose efforts to identify the problems that led to failure and fraud, were suppressed by Elizabeth Holmes? If so, then can’t you say that the failure was due to Holmes’s power at the top of the firm? Meaning due to a kind of hierarchy rather than due to flatness? (I remain unclear and conflicted on whether and when flatness or hierarchy is better.)

(p. B2) . . . do flat structures work? André Spicer, a professor of organizational behavior at the Bayes Business School in London, said that, while the “cultural zeitgeist when I was growing up was that hierarchies are bad,” there’s been an increasing recognition of both the need for them and the fact that they often reappear in businesses ‌that, at least theoretically, reject them.

. . .

Mr. Spicer is particularly critical of start-ups that have attempted, or claimed to attempt, flat structures, suggesting that failures — and at least one major scandal — have emerged from these workplaces. He pointed to Elizabeth Holmes and Theranos, her health care technology start-up. In a 2015 interview, Ms. Holmes said that Theranos was “a very flat organization and if I have learned anything, we are only as good as the worst people on our team.”

“The claim that companies like Theranos had a flat structure meant the company fitted into a well-recognized type of agile tech firms,” Mr. Spicer said. In addition to attracting investors and employees, the myth “meant that these companies don’t have to do the difficult and tedious process of putting into place all the systems and controls you would normally find.”

He added that he believed those systems “would have likely stopped much of the wrongdoing.” Ms. Holmes and Ramesh Balwani, the former chief operating officer of Theranos, were each recently sentenced to prison time for defrauding investors and patients.

The notion that start-ups in particular are ill suited to a flat structure was supported in a 2021 study by Professor Lee of Wharton. A flat structure “can result in haphazard execution and commercial failure by overwhelming managers with the burden of direction and causing subordinates to drift into power struggles and aimless idea explorations,” he wrote.

For the full story, see:

Charlie Brinkhurst-Cuff. “‘Flat’ Company Structures Sound Appealing. But Do They Work?” The New York Times (Wednesday, July 5, 2023): B2.

(Note: ellipses added.)

(Note: the online version of the story has the same date as the print version, and has the title “In Business, ‘Flat’ Structures Rarely Work. Is There a Solution?” Where there are minor differences in wording between the versions, the passages quoted above follow the online version.)

The academic paper by Lee mentioned in the passage quoted above is:

Lee, Saerom. “The Myth of the Flat Start-Up: Reconsidering the Organizational Structure of Start-Ups.” Strategic Management Journal 43, no. 1 (Jan. 2022): 58-92.

Blacks Are Migrating Away from Northern Cities, Due Partly to Rising Costs and Violence

(p. B3) The waves of migration that brought Black Americans to many northern cities are reversing.

Departing residents are heading everywhere from nearby suburbs to high-growth areas in the southern U.S., such as metro Atlanta, according to demographers, real-estate agents and public officials.

The latest U.S. Census Bureau estimates, released Thursday, indicate Black residents are continuing to leave many urban centers in the North and elsewhere, adding to decades of decline. These losses have hit many major cities with historically large Black populations, including Chicago, Detroit, Cleveland and Oakland, Calif.

. . .

Some are motivated by rising housing costs and worries about safety.

“I wanted some peace and quiet. I was tired of the gunshots, the sirens,” said Mary Hall-Rayford, a retired teacher who moved from Detroit to neighboring Eastpointe, Mich., in 2012. “Eastpointe was a nice little city.”

She serves on the school board and is running for mayor.

For the full story, see:

Jimmy Vielkind, Jon Kamp, Paul Overberg and Jack Gillum. “Black People Are Departing Cities in North.” The Wall Street Journal (Friday, June 23, 2023): B1 & B4.

(Note: ellipsis added.)

(Note: the online version of the story has the date June 22, 2023, and has the title “Black Americans Are Leaving Cities in the North and West.”)

For Musk “Hard Core” Means “Long Hours at High Intensity”

(p. A24) Have you ever gotten an email at midnight from the boss with ​an ominous subject line like “a fork in the road”? Granted, email etiquette today says we’re not supposed to get midnight emails from bosses at all. But Elon Musk is no ordinary boss, and it’s safe to assume he didn’t get the memo on empathetic leadership. So, true to form, as chief executive of Twitter, after laying off nearly half of his staff, bringing a sink to work and proclaiming he would be sleeping at the office “until the org is fixed,” Mr. Musk recently issued this late-night ultimatum to his remaining employees: From this point forward, Twitter was going to be “extremely hard core.” Were they ready to be hard core? They could select “yes” — or opt for three months of severance pay.

To Mr. Musk, “hard core” meant “long hours at high intensity,” a workplace where only the most “exceptional performance” would be accepted and a culture in which midnight emails would be just fine. I’d wager that more than a few workaholics, bosses or otherwise, weren’t entirely turned off by the philosophy behind that statement, and yet it immediately conjured images of sweaty Wall Street bankers collapsing at their desks, Silicon Valley wunderkinds sleeping under theirs and the high-intensity, bro-boss cultures of companies like Uber and WeWork, with their accompanying slogans about doing what you love and sleeping when you’re dead.

For the full commentary, see:

Jessica Bennett. “Elon, the Mosh Pit Called. It Wants ‘Hard Core’ Back.” The New York Times (Friday, November 25, 2022): A24.

(Note: the online version of the commentary has the date Nov. 23, 2022, and has the title “The Worst Midnight Email From the Boss, Ever.”)

“In Tokyo Good Things Have Been Created Through Private Initiative”

(p. A22) Yuta Yamasaki and his wife moved from southern Japan to Tokyo a decade ago because job prospects were better in the big city. They now have three sons — ages 10, 8 and 6 — and they are looking for a larger place to live. But Mr. Yamasaki, who runs a gelato shop, and his wife, a child-care worker, aren’t planning to move far. They are confident they can find an affordable three-bedroom apartment in their own neighborhood.

As housing prices have soared in major cities across the United States and throughout much of the developed world, it has become normal for people to move away from the places with the strongest economies and best jobs because those places are unaffordable. Prosperous cities increasingly operate like private clubs, auctioning off a limited number of homes to the highest bidders.

Tokyo is different.

. . .

Small apartment buildings can be built almost anywhere, and larger structures are allowed on a vast majority of urban land. Even in areas designated for offices, homes are permitted. After Tokyo’s office market crashed in the 1990s, developers started building apartments on land they had purchased for office buildings.

“In progressive cities we are maybe too critical of private initiative,” said Christian Dimmer, an urban studies professor at Waseda University and a longtime Tokyo resident. “I don’t want to advocate a neoliberal perspective, but in Tokyo good things have been created through private initiative.”

Tokyo makes little effort to preserve old homes. Historic districts subject to preservation laws exist in other Japanese cities, but the nation’s largest city has none. New construction is prized. People treat homes like cars: They want the latest models.

For the full commentary, see:

Binyamin Appelbaum and Andrew Faulk. “Tokyo, the Big City Where Housing Isn’t Crazy Expensive.” The New York Times (Saturday, September 16, 2023): A22.

(Note: ellipsis added.)

(Note: the online version of the commentary has the date September 11, 2023, and has the title “The Big City Where Housing Is Still Affordable.”)