Pope Rejects Market Mechanisms Because Pope Rejects Market’s Respect for Consumer Choice

(p. A19) The pope is not hostile to market mechanisms because he is a raving socialist, as some have suggested. Instead, his stance is a natural consequence of his theology.
To understand the pope’s position, remember that, even though he is adopting a progressive stance on the environment, he is not a liberal. Indeed, he rejects one of the central tenets of liberalism, which is a willingness to acknowledge genuine disagreement about the good.
The fundamental problem with markets, in Pope Francis’ view, is that they cater to people’s desires, whatever those desires happen to be. What makes the market a liberal institution is that it does not judge the relative merits of these desires. The customer is always right.
Pope Francis rejects this, describing it as part of a “culture of relativism.” The customer, in his view, is often wrong. He wants an economic system that satisfies not whatever desires people happen to have but the desires that they should have — a system that promotes the common good, according to the church’s specification of what that good is.

For the full commentary, see:
JOSEPH HEATH. “Pope Francis’ Climate Error.” The New York Times (Sat., JUNE 20, 2015): A19.
(Note: ellipses added.)
(Note: the online version of the commentary has the date JUNE 19, 2015.)

Starting in Late Middle Ages the State Tried “to Control, Delineate, and Restrict Human Thought and Action”

(p. C6) . . . transregional organizations like Viking armies or the Hanseatic League mattered more than kings and courts. It was a world, as Mr. Pye says, in which “you went where you were known, where you could do the things you wanted to do, and where someone would protect you from being jailed, hanged, or broken on the wheel for doing them.”
. . .
This is a world in which money rules, but money is increasingly an abstraction, based on insider information, on speculation (the Bourse or stock market itself is a regional invention) and on the ability to apply mathematics: What was bought or sold was increasingly the relationships between prices in different locations rather than the goods themselves.
What happened to bring this powerful, creative pattern to a close? The author credits first the reaction to the Black Death of the mid-14th century, when fear of contamination (perhaps similar to our modern fear of terrorism) justified laws that limited travel and kept people in their place. Religious and sectarian strife further limited the free flow of ideas and people, forcing people to choose one identity to the exclusion of others or else to attempt to disappear into the underground of clandestine and subversive activities. And behind both of these was the rise of the state, a modern invention that attempted to control, delineate, and restrict human thought and action.

For the full review, see:
PATRICK J. GEARY. “Lighting Up the Dark Ages.” The Wall Street Journal (Sat., May 30, 2015): C6.
(Note: ellipses added.)
(Note: the online version of the review has the date May 29, 2015.)

The book under review, is:
Pye, Michael. The Edge of the World: A Cultural History of the North Sea and the Transformation of Europe. New York: Pegasus Books LLC, 2014.

Rather than Debate Global Warming Skeptics, Some Label them “Denialists” to “Link Them to Holocaust Denial”

(p. D2) The contrarian scientists like to present these upbeat scenarios as the only plausible outcomes from runaway emissions growth. Mainstream scientists see them as being the low end of a range of possible outcomes that includes an alarming high end, and they say the only way to reduce the risks is to reduce emissions.
The dissenting scientists have been called “lukewarmers” by some, for their view that Earth will warm only a little. That is a term Dr. Michaels embraces. “I think it’s wonderful!” he said. He is working on a book, “The Lukewarmers’ Manifesto.”
When they publish in scientific journals, presenting data and arguments to support their views, these contrarians are practicing science, and perhaps the “skeptic” label is applicable. But not all of them are eager to embrace it.
“As far as I can tell, skepticism involves doubts about a plausible proposition,” another of these scientists, Richard S. Lindzen, told an audience a few years ago. “I think current global warming alarm does not represent a plausible proposition.”
. . .
It is perhaps no surprise that many environmentalists have started to call them deniers.
The scientific dissenters object to that word, claiming it is a deliberate attempt to link them to Holocaust denial. Some academics sharply dispute having any such intention, but others have started using the slightly softer word “denialist” to make the same point without stirring complaints about evoking the Holocaust.

For the full commentary, see:
Justin Gillis. “BY DEGREES; Verbal Warming: Labels in the Climate Debate.” The New York Times (Tues., FEB. 17, 2015): D1-D2.
(Note: ellipsis added.)
(Note: the online version of the commentary has the date FEB. 12 (sic), 2015.)

More Tech Stars Skip College, at Least for a While

(p. B1) The college dropout-turned-entrepreneur is a staple of Silicon Valley mythology. Steve Jobs, Bill Gates and Mark Zuckerberg all left college.
In their day, those founders were very unusual. But a lot has changed since 2005, when Mr. Zuckerberg left Harvard. The new crop of dropouts has grown up with the Internet and smartphones. The tools to create new technology are more accessible. The cost to start a company has plunged, while the options for raising money have multiplied.
Moreover, the path isn’t as lonely.
. . .
Not long ago, dropping out of school to start a company was considered risky. For this generation, it is a badge of honor, evidence of ambition and focus. Very few dropouts become tycoons, but “failure” today often means going back to school or taking a six-figure job at a big tech company.
. . .
(p. B5) There are no hard numbers on the dropout trend, but applicants for the Thiel Fellowship tripled in the most recent year; the fellowship won’t disclose numbers.
. . .
It has tapped 82 fellows in the past five years.
“I don’t think college is always bad, but our society seems to think college is always good, for everyone, at any cost–and that is what we have to question,” says Mr. Thiel, a co-founder of PayPal and an early investor in Facebook.
Of the 43 fellows in the initial classes of 2011 and 2012, 26 didn’t return to school and continued to work on startups or independent projects. Five went to work for large tech firms, including a few through acquisitions. The remaining 12 went back to school.
Mr. Thiel says companies started by the fellows have raised $73 million, a record that he says has attracted additional applicants. He says fellows “learned far more than they would have in college.”

For the full story, see:
DAISUKE WAKABAYASHI. “College Dropouts Thrive in Tech.” The Wall Street Journal (Thurs., June 4, 2015): B1 & B10.
(Note: ellipses added. The phrase “the fellowship won’t disclose numbers” was in the online, but not the print, version of the article.)
(Note: the online version of the article has the date June 3, 2015, and has the title “College Dropouts Thrive in Tech.”)

The Complementarity of Humans and Robots in Education

(p. 6) Computers and robots are already replacing many workers. What can young people learn now that won’t be superseded within their lifetimes by these devices and that will secure them good jobs and solid income over the next 20, 30 or 50 years? In the universities, we are struggling to answer that question.
. . .
Some scholars are trying to discern what kinds of learning have survived technological replacement better than others. Richard J. Murnane and Frank Levy in their book “The New Division of Labor” (Princeton, 2004) studied occupations that expanded during the information revolution of the recent past. They included jobs like service manager at an auto dealership, as opposed to jobs that have declined, like telephone operator.
The successful occupations, by this measure, shared certain characteristics: People who practiced them needed complex communication skills and expert knowledge. Such skills included an ability to convey “not just information but a particular interpretation of information.” They said that expert knowledge was broad, deep and practical, allowing the solution of “uncharted problems.”
. . .
When I arrived at Yale in 1982, there were no undergraduate courses in finance. I started one in the fall of 1985, and it continues today. Increasingly, I’ve tried to connect mathematical theory to actual applications in finance.
Since its beginnings, the course has gradually become more robotic: It resembles a real, dynamic, teaching experience, but in execution, much of it is prerecorded, and exercises and examinations are computerized. Students can take it without need of my physical presence. Yale made my course available to the broader public on free online sites: AllLearn in 2002, Open Yale in 2008 and 2011, and now on Coursera.
The process of tweaking and improving the course to fit better in a digital framework has given me time to reflect about what I am doing for my students. I could just retire now and let them watch my lectures and use the rest of the digitized material. But I find myself thinking that I should be doing something more for them.
So I continue to update the course, thinking about how I can integrate its lessons into an “art of living in the world.” I have tried to enhance my students’ sense that finance should be the art of financing important human activities, of getting people (and robots someday) working together to accomplish things that we really want done.

For the full commentary, see:
ROBERT J. SHILLER. “Economic View; What to Learn in College to Stay One Step Ahead of Computers.” The New York Times, SundayBusiness Section (Sun., MAY 24, 2015): 6.
(Note: ellipses added.)
(Note: the online version of the commentary has the date MAY 22, 2015, and has the title “Economic View; What to Learn in College to Stay One Step Ahead of Computers.”)

The Levy and Murnane book mentioned above, is:
Levy, Frank, and Richard J. Murnane. The New Division of Labor: How Computers Are Creating the Next Job Market. Princeton, NJ: Princeton University Press, 2004.
Some of the core of the Levy and Murnane book can be found in:
Levy, Frank, and Richard Murnane. “Book Excerpt: The New Division of Labor.” Milken Institute Review 6, no. 4 (Dec. 2004): 61-82.

McCulloch Endorses Strunk and White’s “Revise and Rewrite” and “Be Clear”

(p. 10) When you wrote your first book, on the Johnstown flood, did you have a model in mind, a kind of storytelling you admired?
Walter Lord’s “A Night to Remember,” about the sinking of the Titanic, was the best book about a disaster I had ever read. But in an odd way I think I was more influenced at the time by the novels of Conrad Richter, and particularly his Ohio trilogy, “The Trees,” “The Fields” and “The Town,” in the extremely skillful way he evoked a sense of place.
. . .
If you had to name one book that made you who you are today, what would it be?
“The Elements of Style,” by William Strunk Jr. and E. B. White. I read it first nearly 50 years ago and still turn to it as an ever reliable aid-to-navigation, and particularly White’s last chapter, with its reminders to “Revise and Rewrite” and “Be Clear.”

For the full interview, see:
“By the Book: David McCullough.” The New York Times Book Review (Sun., MAY 31, 2015): 10.
(Note: ellipsis added, bold in original. The bold questions are from an anonymous New York Times interviewer.)
(Note: the online version of the interview has the date MAY 28, 2015, and has the title “David McCullough: By the Book.”)

A wonderful book by McCullough, is:
McCullough, David. The Wright Brothers. New York: Simon & Schuster, 2015.

“Buy Local” Inefficiently Wastes Resources

(p. 8) Much is . . . made about the eco-friendliness of handmade.
“Buying handmade (especially really locally) can greatly reduce your carbon footprint on the world,” reads a post on the popular website Handmadeology.
But few economists give much credence to the idea that buying local necessarily saves energy. Most believe that the economies of scale inherent in mass production outweigh the benefits of nearness. These same economies of scale most likely make a toothbrush factory less wasteful, in terms of materials, than 100 individual toothbrush makers each handcrafting 10 toothbrushes a day.

For the full commentary, see:
EMILY MATCHA. “OPINION; It’s Chic. Not Morally Superior. That Handmade Scarf Won’t Save the World.” The New York Times, SundayReview Section (Sun., MAY 3, 2015): 8.
(Note: ellipses added.)
(Note: the online version of the coomentary has the date MAY 2, 2015, and has the title “OPINION; Sorry, Etsy. That Handmade Scarf Won’t Save the World.”)

Average Length of 10-K Reports Rises to 41,911 Words

WordLength10KannualReportGraph2015-07-05.jpgSource of graph: online version of the WSJ article quoted and cited below.

(p. B1) General Electric Co.’s chief financial officer was taken aback by the industrial conglomerate’s 246-page annual report.

The 10-K and supporting documents his finance team and others at the company produced was meant to give investors a comprehensive picture of GE’s businesses and financial performance over the previous 12 months. It did everything but.
Packed with text on the company’s internal controls, auditor statements and regulator-mandated boilerplate on “inflation, recession and currency volatility,” the 2013 annual report was 109,894 words long. “Not a retail investor on planet Earth could get through” it, let alone understand it, said GE finance chief Jeffrey Bornstein.
Companies are spending an increasing amount of time and energy beefing up their regulatory filings to meet disclosure requirements. The average 10K is getting longer–about 42,000 words in 2013, up from roughly 30,000 words in 2000. By comparison, the text of the Sarbanes-Oxley Act of 2002 has 32,000 words.

For the full story, see:
VIPAL MONGA and EMILY CHASAN. “The 109,894-Word Annual Report.” The Wall Street Journal (Tues., June 2, 2015): B1 & B10.

“Big Data” Does Not Tell Us What to Measure, and Ignores What Cannot Be Measured

(p. 6) BIG data will save the world. How often have we heard that over the past couple of years? We’re pretty sure both of us have said something similar dozens of times in the past few months.
If you’re trying to build a self-driving car or detect whether a picture has a cat in it, big data is amazing. But here’s a secret: If you’re trying to make important decisions about your health, wealth or happiness, big data is not enough.
The problem is this: The things we can measure are never exactly what we care about. Just trying to get a single, easy-to-measure number higher and higher (or lower and lower) doesn’t actually help us make the right choice. For this reason, the key question isn’t “What did I measure?” but “What did I miss?”
. . .
So what can big data do to help us make big decisions? One of us, Alex, is a data scientist at Facebook. The other, Seth, is a former data scientist at Google. There is a special sauce necessary to making big data work: surveys and the judgment of humans — two seemingly old-fashioned approaches that we will call small data.
Facebook has tons of data on how people use its site. It’s easy to see whether a particular news feed story was liked, clicked, commented on or shared. But not one of these is a perfect proxy for more important questions: What was the experience like? Did the story connect you with your friends? Did it inform you about the world? Did it make you laugh?
(p. 7) To get to these measures, Facebook has to take an old-fashioned approach: asking. Every day, hundreds of individuals load their news feed and answer questions about the stories they see there. Big data (likes, clicks, comments) is supplemented by small data (“Do you want to see this post in your News Feed?”) and contextualized (“Why?”).
Big data in the form of behaviors and small data in the form of surveys complement each other and produce insights rather than simple metrics.
. . .
Because of this need for small data, Facebook’s data teams look different than you would guess. Facebook employs social psychologists, anthropologists and sociologists precisely to find what simple measures miss.
And it’s not just Silicon Valley firms that employ the power of small data. Baseball is often used as the quintessential story of data geeks, crunching huge data sets, replacing fallible human experts, like scouts. This story was made famous in both the book and the movie “Moneyball.”
But the true story is not that simple. For one thing, many teams ended up going overboard on data. It was easy to measure offense and pitching, so some organizations ended up underestimating the importance of defense, which is harder to measure. In fact, in his book “The Signal and the Noise,” Nate Silver of fivethirtyeight.com estimates that the Oakland A’s were giving up 8 to 10 wins per year in the mid-1990s because of their lousy defense.
. . .
Human experts can also help data analysts figure out what to look for. For decades, scouts have judged catchers based on their ability to frame pitches — to make the pitch appear more like a strike to a watching umpire. Thanks to improved data on pitch location, analysts have recently checked this hypothesis and confirmed that catchers differ significantly in this skill.

For the full commentary, see:
ALEX PEYSAKHOVICH and SETH STEPHENS-DAVIDOWITZ. “How Not to Drown in Numbers.” The New York Times, SundayReview Section (Sun., MAY 3, 2015): 6-7.
(Note: ellipses added.)
(Note: the online version of the commentary has the date MAY 2, 2015.)

Spread of Robots Creates New and Better Human Jobs

(p. A11) The issues at the heart of “Learning by Doing” come into sharp relief when James Bessen visits a retail distribution center near Boston that was featured on “60 Minutes” two years ago. The TV segment, titled “Are Robots Hurting Job Growth?,” combined gotcha reporting with vintage movie clips–scary-looking Hollywood robots–to tell a chilling tale of human displacement and runaway job loss.
Mr. Bessen isn’t buying it. Although robots at the distribution center have eliminated some jobs, he says, they have created others–for production workers, technicians and managers. The problem at automated workplaces isn’t the robots. It’s the lack of qualified workers. New jobs “require specialized skills,” Mr. Bessen writes, but workers with these skills “are in short supply.”
It is a deeply contrarian view. The conventional wisdom about robots and other new workplace technology is that they do more harm than good, destroying jobs and hollowing out the middle class. MIT economists Erik Brynjolfsson and Andrew McAfee made the case in their best-selling 2014 book, “The Second Machine Age.” They describe a future in which software-driven machines will take over not just routine jobs–replacing clerks, cashiers and warehouse workers–but also tasks done by nurses, doctors, lawyers and stock traders. Mr. Bessen sets out to refute the arguments of such techno-pessimists, relying on economic analysis and on a fresh reading of history.

For the full review, see:
TAMAR JACOBY. “BOOKSHELF; Technology Isn’t a Job Killer; Many predicted ATMs would eliminate bank tellers, but the number of tellers in the U.S. has risen since the machines were introduced.” The Wall Street Journal (Thurs., May 21, 2015): A11.
(Note: the online version of the review has the date May 20, 2015.)

The book under review, is:
Bessen, James. Learning by Doing: The Real Connection between Innovation, Wages, and Wealth. New Haven, CT: Yale University Press, 2015.

Computer Programs “Lack the Flexibility of Human Thinking”

(p. A11) . . . let’s not panic. “Superintelligent” machines won’t be arriving soon. Computers today are good at narrow tasks carefully engineered by programmers, like balancing checkbooks and landing airplanes, but after five decades of research, they are still weak at anything that looks remotely like genuine human intelligence.
. . .
Even the best computer programs out there lack the flexibility of human thinking. A teenager can pick up a new videogame in an hour; your average computer program still can only do just the single task for which it was designed. (Some new technologies do slightly better, but they still struggle with any task that requires long-term planning.)

For the full commentary, see:
GARY MARCUS. “Artificial Intelligence Isn’t a Threat–Yet; Superintelligent machines are still a long way off, but we need to prepare for their future rise.” The Wall Street Journal (Sat., Dec. 13, 2014): A11.
(Note: ellipsis added.)
(Note: the online version of the commentary has the date Dec. 11, 2014.)