Economics of Technology – Page 50

“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.

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.”)

Inventor Haber and Entrepreneur Bosch Created “an Inflection Point in History”

(p. C7) . . . , Mr. Kean’s narrative of scientific discovery jumps back and forth. The first episode narrated in detail is Fritz Haber and Carl Bosch’s conversion of nitrogen into ammonia, the crucial step in producing artificial fertilizer, which Mr. Kean characterizes as “an inflection point in history” that in the 20th century “transformed the very air into bread.” The process consumes 1% of the global energy supply, producing 175 million tons of ammonia fertilizer a year and generating half the world’s food. Haber and Bosch both won Nobel Prizes but were subsequently tainted by their involvement in developing chlorine gas for the German military.
The book’s middle section turns back the clock to steam power, the technology that launched the Industrial Revolution. James Watt was its master craftsman, though Mr. Kean confesses that, as “a sucker for mechanical simplicity,” he regards Watt’s pioneering engine, with its separate condenser, as “a bunch of crap cobbled together.” A more elegant application of gases was Henry Bessemer’s process for making steel, which used blasts of compressed air to make obsolete the laborious and energy-hungry mixing of liquid cast iron and carbon.

For the full review, see:
Mike Jay. “Adventures in the Atmosphere.” The Wall Street Journal (Sat., July 22, 2017): C7.
(Note: ellipsis added.)
(Note: the online version of the review has the date July 21, 2017.)

The book under review, is:
Kean, Sam. Caesar’s Last Breath: Decoding the Secrets of the Air Around Us. New York: Little, Brown and Company, 2017.

Russian Regulators Jail Entrepreneur for Innovating “Too Fast and Too Freely”

(p. A1) AKADEMGORODOK, Russia — Dmitri Trubitsyn is a young physicist-entrepreneur with a patriotic reputation, seen in this part of Siberia as an exemplar of the talents, dedication and enterprise that President Vladimir V. Putin has hailed as vital for Russia’s future economic health.
Yet Mr. Trubitsyn faces up to eight years in jail after a recent raid on his home and office here in Akademgorodok, a Soviet-era sanctuary of scientific research that was supposed to showcase how Mr. Putin’s Russia can harness its abundance of talent to create a modern economy.
A court last Thursday [August 3, 2017] extended Mr. Trubitsyn’s house arrest until at least October, which bars him from leaving his apartment or communicating with anyone other than his immediate family. Mr. Trubitsyn, 36, whose company, Tion, manufactures high-tech air-purification systems for homes and hospitals, is accused of risking the lives of hospital patients, and trying to lift profits, by upgrading the purifiers so they would consume less electricity.
Most important, he is accused of doing this without state regulators certifying the changes.
It is a case that highlights the tensions between Mr. Putin’s aspirations for a dynamic private sector and his determination to enhance the powers of Russia’s security apparatus. Using a 2014 law meant to protect Russians from counterfeit medicine, investigators from the Federal Security Service, the post-Soviet KGB, and other agencies have accused Mr. Trubitsyn of leading a criminal conspiracy to, essentially, innovate too fast and too freely.
. . .
(p. A9) Irina Travina, the founder of a software start-up and head of the local technology-business association, said Akademgorodok was “the best place in Russia,” with “outstanding schools, low crime and a high concentration of very smart people.”
But she said Mr. Trubitsyn’s arrest had delivered a grave blow to the community’s sense of security.
“In principle, anyone can fall into this situation,” Ms. Travina said, praising Mr. Trubitsyn as a patriot because he had not moved abroad and had invested time and money in science education for local children. “It can happen to anybody,” she added. “Everyone has some sort of skeleton in their closet. Maybe nothing big, but they can always find something to throw you in jail for.”

For the full story, see:
ANDREW HIGGINS. “Russia Wants Innovation, but Jails Innovators.” The New York Times (Thurs., AUG. 10, 2017): A1 & A9.
(Note: ellipsis, and bracketed date, added.)
(Note: the online version of the story has the date AUG. 9, 2017, and has the title “Russia Wants Innovation, but It’s Arresting Its Innovators.”)

“Shannon’s Principles of Redundancy and Error Correction”

(p. C7) There were four essential prophets whose mathematics brought us into the Information Age: Norbert Wiener, John von Neumann, Alan Turing and Claude Shannon. In “A Mind at Play: How Claude Shannon Invented the Information Age,” Jimmy Soni and Rob Goodman make a convincing case for their subtitle while reminding us that Shannon never made this claim himself.
. . .
The only one of the four Information Age pioneers who was also an electrical engineer, Shannon was practical as well as brilliant.
. . .
Wiener’s theory of information, drawing on his own background in thermodynamics, statistical mechanics and the study of random processes, was cloaked in opaque mathematics that was impenetrable to most working engineers.
. . .
“Before Shannon,” Messrs. Soni and Goodman write, “information was a telegram, a photograph, a paragraph, a song. After Shannon, information was entirely abstracted.” He derived explicit formulas for rates of transmission, the capacity of an ideal channel, ability to correct errors and coding efficiency that could be understood by anyone familiar with logarithms to the base 2.
Mathematicians use mathematics to understand things. Engineers use mathematics to build things. Engineers love logarithms as a carpenter loves a familiar tool. The electronic engineers who flooded into civilian life in the aftermath of World War II adopted Shannon’s theory as passionately as they had avoided Wiener’s, bringing us the age of digital machines.
. . .
Despite the progress of technology, we still have no clear understanding of how memories are stored in our own brains: Shannon’s principles of redundancy and error correction are no doubt involved in preserving memory, but how does the process work and why does it sometimes fail? Shannon died of Alzheimer’s disease in February 2001. The mind that gave us the collective memory we now so depend on had its own memory taken away.

For the full review, see:
George Dyson. “The Elegance of Ones and Zeroes.” The Wall Street Journal (Sat., July 22, 2017): C7.
(Note: ellipses added.)
(Note: the online version of the review has the date July 21, 2017.)

The book under review, is:
Soni, Jimmy, and Rob Goodman. A Mind at Play: How Claude Shannon Invented the Information Age. New York: Simon & Schuster, 2017.

Code Schools Provide Intense 12 Week Training, and Jobs

(p. B1) Across the U.S., change is coming for the ecosystem of employers, educational institutions and job-seekers who confront the increasingly software-driven nature of work. A potent combination–a yawning skills gap, stagnant middle-class wages and diminished career prospects for millennials–is bringing about a rapid shift (p. B4) in the labor market for coders and other technical professionals.
Riding into the breach are “code schools,” a kind of vocational training that rams students through intense 12-week crash courses in precisely the software-development skills employers need.

For the full commentary, see:
Christopher Mims. “Code-School Boot Camps Offer Fast Track to Jobs.” The Wall Street Journal (Mon., Feb. 27, 2017): B1 & B4.
(Note: the online version of the commentary has the date Feb. 26, 2017, and has the title “A New Kind of Jobs Program for Middle America.”)

Employment Grows as Productivity Rises

(p. C3) In a recent paper prepared for a European Central Bank conference, the economists David Autor of MIT and Anna Salomons of Utrecht University looked at data for 19 countries from 1970 to 2007. While acknowledging that advances in technology may hurt employment in some industries, they concluded that “country-level employment generally grows as aggregate productivity rises.”
The historical record provides strong support for this view. After all, despite centuries of progress in automation and recurrent warnings of a jobless future, total employment has continued to increase relentlessly, even with bumps along the way.
More remarkable is the fact that today’s most dire projections of jobs lost to automation fall short of historical norms. A recent analysis by Robert Atkinson and John Wu of the Information Technology & Innovation Foundation quantified the rate of job destruction (and creation) in each decade since 1850, based on census data. They found that an incredible 57% of the jobs that workers did in 1960 no longer exist today (adjusted for the size of the workforce).
Workers suffering some of the largest losses included office clerks, secretaries and telephone operators. They found similar levels of displacement in the decades after the introduction of railroads and the automobile. Who is old enough to remember bowling alley pin-setters? Elevator operators? Gas jockeys? When was the last time you heard a manager say, “Take a memo”?
. . .
. . . , if artificial intelligence is getting so smart that it can recognize cats, drive cars, beat world-champion Go players, identify cancerous lesions and translate from one language to another, won’t it soon be capable of doing just about anything a person can?
Not by a long shot. What all of these tasks have in common is that they involve finding subtle patterns in very large collections of data, a process that goes by the name of machine learning.
. . .
But it is misleading to characterize all of this as some extraordinary leap toward duplicating human intelligence. The selfie app in your phone that places bunny ears on your head doesn’t “know” anything about you. For its purposes, your meticulously posed image is just a bundle of bits to be strained through an algorithm that determines where to place Snapchat face filters. These programs present no more of a threat to human primacy than did automatic looms, phonographs and calculators, all of which were greeted with astonishment and trepidation by the workers they replaced when first introduced.
. . .
The irony of the coming wave of artificial intelligence is that it may herald a golden age of personal service. If history is a guide, this remarkable technology won’t spell the end of work as we know it. Instead, artificial intelligence will change the way that we live and work, improving our standard of living while shuffling jobs from one category to another in the familiar capitalist cycle of creation and destruction.

For the full commentary, see:
Kaplan, Jerry. “Don’t Fear the Robots.” The Wall Street Journal (Sat., June 22, 2017): C3.
(Note: ellipses added.)
(Note: the online version of the commentary has the date June 21, 2017.)

The David Autor paper, mentioned above, is:

Autor, David, and Anna Salomons. “Does Productivity Growth Threaten Employment?” Working Paper. (June 19, 2017).

The Atkinson and Wu report, mentioned above, is:
Atkinson, Robert D., and John Wu. “False Alarmism: Technological Disruption and the U.S. Labor Market, 1850-2015.” (May 8, 2017).

The author’s earlier book, somewhat related to his commentary quoted above, is:
Kaplan, Jerry. Artificial Intelligence: What Everyone Needs to Know. New York: Oxford University Press, 2016.

Toyota’s Solid-State, Lithium-Ion Batteries Increase Electric Car Range

(p. B6) TOKYO–Toyota Motor Corp. believes it has mastered the technology and production process for a new lithium-ion battery that could slash charging time and double the range of electric vehicles, according to U.S. patent filings and one of the inventors.
On Tuesday [July 25, 2017] Toyota said that by the early 2020s it planned to sell cars equipped with solid-state batteries, which replace the damp electrolyte used to transport lithium ions inside today’s batteries with a solid glass-like plate.
Behind Toyota’s brief statement lay years of research aimed at solving issues that have long bedeviled batteries for electric cars. Current lithium-ion batteries can’t be packed too tightly together because of fire risk. That is one reason electric cars tend to have limited range compared with traditional gasoline-powered cars.
With the solid-state battery, “you can improve the output and reduce the charge time–hopefully,” said Ryoji Kanno, a professor at the Tokyo Institute of Technology. Prof. Kanno led a team including Toyota scientists that discovered the materials for the glass-like electrolyte.

For the full story, see:
McLain, Sean. “Toyota: Battery Can Make Electric Cars Go Farther.” The Wall Street Journal (Fri., July 28, 2017): B6.
(Note: bracketed date, added.)
(Note: the online version of the story has the date July 27, 2017, and has the title “Toyota’s Cure for Electric-Vehicle Range Anxiety: A Better Battery.”)

Process Innovations Increase Access to Natural Resources

(p. B6) SUPERIOR, Ariz.–One of the world’s largest untapped copper deposits sits 7,000 feet below the Earth’s surface. It is a lode that operator Rio Tinto PLC wouldn’t have touched–until now.
. . .
Advances in mining technology are making that possible–just as developments in oil and gas drilling heralded the fracking revolution. Now, using everything from sensors and data analytics to autonomous vehicles and climate-control systems, Rio aims to pull ore from more than a mile below ground, where temperatures can reach nearly 175 degrees Fahrenheit.
. . .
While a deep underground block-cave mine costs much more to develop, Rio says it can match the operating costs per ton of ore of a surface mine, partly because it is so mechanized.
. . .
As with the development of new hydraulic-fracturing and horizontal-drilling techniques to extract oil from shale-rock deposits, locating and extracting the copper successfully requires deployment of new technologies such as cheaper, more powerful sensors and breakthroughs in the use of data.
, , ,
Electrical gear buzzes constantly, and a network of pipes pumps water out of the shaft at the rate of 600 gallons a minute. A ventilation system cools the area to 77 degrees.
Over the next few years, Rio plans to deploy tens of thousands of electronic sensors, as well as autonomous vehicles and complex ventilation systems, to help it bring 1.6 billion tons of ore to the surface over the more than 40-year projected life of the mine.

For the full story, see:
Steven Norton. “Rio Digs Deeper for Copper.” The Wall Street Journal (Thurs., June 8, 2017): B6.
(Note: ellipses added.)
(Note: the online version of the story has the date June 7, 2017, and has the title “Mining a Mile Down: 175 Degrees, 600 Gallons of Water a Minute.”)

Health Innovations Launch Where Regulations Are Few

(p. A15) One type of mobile device that is likely to appear first in the Far East and be widely adopted there is the digital stethoscope. This device is able to detect changes in pitch and soon will be able to detect asthma in children, pneumonia in the elderly, and, in conjunction with low-cost portable electrocardiographs, cardiopulmonary disease.
An additional advantage is that this part of the world–particularly India and Africa–has limited regulation, which makes it much easier to launch these kinds of health-care tools. In India and much of Africa, there are few government drug agencies or big insurance companies to throw up barriers.
Companies that make medical devices and their accompanying smartphone apps could establish themselves almost overnight. Then, once they have built a large, profitable base of users, they could consider jumping through the legal and regulatory hoops to bring the technology to developed countries.

For the full commentary, see:
Michael S. Malone. “Silicon Valley Trails in Medical Tech; With smartphones everywhere and little regulation, India and Africa are set to lead..” The Wall Street Journal (Mon., July 24, 2017): A15.
(Note: the online version of the commentary has the date July 23, 2017.)

Regulations, Not Robots, Cause Slower Job Growth

(p. A19) Some anxious forecasters project that robotics, automation and artificial intelligence will soon devastate the job market. Yet others predict a productivity fizzle. The Congressional Budget Office, for instance, expects labor productivity to grow at the snail’s pace of 1.3% a year over the next decade, well below the historical average.
There’s reason to reject both of these dystopian scenarios. Innovation isn’t a zero-sum game. The problem for most workers isn’t too much technology but too little. What America needs is more computers, mobile broadband, cloud services, software tools, sensor networks, 3-D printing, augmented reality, artificial intelligence and, yes, robots.
For the sake of explanation, let’s separate the economy into two categories. In digital industries–technology, communications, media, software, finance and professional services–productivity grew 2.7% annually over the past 15 years, according to the findings of our report, “The Coming Productivity Boom,” released in March. The slowdown is concentrated in physical industries–health care, transportation, education, manufacturing, retail–where productivity grew a mere 0.7% annually over the same period.
Digital industries have also experienced stronger job growth. Since the peak of the last business cycle in December 2007, hours worked in the digital category rose 9.6%, compared with 5.6% on the physical side. If health care is excluded, hours worked in physical jobs rose only 3%.
What is holding the physical industries back? It is no coincidence that they are heavily regulated, making them expensive to operate in and resistant to experimentation. The digital economy, on the other hand, has enjoyed a relatively free hand to invest and innovate, delivering spectacular and inexpensive products and services all over the world.
But more important, partially due to regulation, physical industries have not deployed information technology to the same extent that digital industries have.

For the full commentary, see:

Bret Swanson and Michael Mandel. “Robots Will Save the Economy; The problem today is too little technology. Physical industries haven’t kept up.” The Wall Street Journal (Mon., May 15, 2017): A19.
(Note: the online version of the commentary has the date May 14, 2017.)