Irving Wladawsky-Berger

How Has Working from Home Worked Out So Far?

“COVID-19 triggered a mass social experiment in working from home (WFH),” said economists Jose Maria Barrero, Nicholas Bloom, and Stephen J. Davis in Why Working from Home Will Stick, a paper published in April of 2021 by the National Bureau of Economics Research (NBER). “Americans, for example, supplied roughly half of paid workhours from home between April and December 2020, as compared to five percent before the pandemic. This seismic shift in working arrangements has attracted no shortage of opinions about whether WFH will stick.”

Working from home (WFH) has been around for decades, modestly growing in the 1990s with the rise of the Internet. The share of WFH three or more days per week was under 1% in 1980, 2.4% in 2010, and 4.0% in 2018. Then came Covid-19, forcing tens of millions around the world to work from home and triggering a mass workplace experiment that broke through the technological and cultural barriers that had prevented its adoption in the past.

To investigate whether WFH will stick, the authors of the NBER paper devised a survey that asked questions about working arrangements and personal experiences with WFH during the pandemic, as well as worker preferences and employer plans after the pandemic ends. The survey was conducted monthly between May 2020 and March 2021, by which time it had collected 28,597 valid responses from 20-64 years old US workers, of which 43.8% were female. The typical respondent was 40 to 50 years old, with one to three years of college, who earned $40 to $50 thousand in 2019.

Let me discuss a few of the survey’s questions and findings.

Which Colleges and College Programs Give Students the Best Bang for their Buck?

“The decision not to attend college for fear that it’s a bad deal is among the most economically irrational decisions anybody could make in 2014,” wrote NY Times journalist David Leonhardt in Is College Worth It? in May of 2014. “Over the long run, college is cheaper than free,” he added, citing an article by MIT economist David Autor which pointed out that a college-educated worker can expect an additional lifetime earning of over $500,000 compared to one whose highest degree is a high school diploma. Experts and journalists questioning the value of a college education are most likely obsessing to get their toddlers into an elite nursery school, so they are on-track for the right schools over the ensuing 20 years, added Leonhardt.

In May, 2019 seminar I attended, Autor noted that over the last four decades, the US and other industrial economies have seen a remarkable rise in wage inequality by educational attainment, with the earnings of the most-educated increasing, and the earnings of the least-educated falling in real terms. Since the 1980s, the earnings of those with a four year college degree have risen by 40% to 60%, while the earnings of those with a high school education or less have fallen among men and barely changed among women.

Every year, the US Bureau of Labor Statistics publishes a set of earning projections by educational attainment. Their 2020 projections showed that the median weekly earnings for all workers is $1,029; for those with less than a high school degree it is $619; high school diploma - $781; some college, no degree - $877; associate’s degree - $938; bachelor’s degree - $1,305; master’s degree - $1,545; doctoral degree - $1,885; and professional degree - $1,893.

Beyond these aggregate numbers, which institutions of higher education give students the best economic returns, that is, the best bang for their buck. In April of 2020, Third Way, a public policy think tank, published a report that introduced a new approach for estimating the economic return of an education, - that is, the Price-to-Earnings Premium (PEP), - based on the amount of time it generally takes a student to recoup the cost of obtaining a credential at a particular school.

Impact of Covid-19 on Job Automation

“Why are there still so many jobs?,” asked MIT economist David Autor in a 2015 article on the history of workplace automation. Given that technologies have been automating human work for the past couple of centuries,“should we not be somewhat surprised that technological change hasn’t already wiped out employment for the vast majority of workers?”

As Autor explained in the article, the answer is based on an economic reality that’s frequently overlooked. “Automation does indeed substitute for labor - as it is typically intended to do. However, automation also complements labor, raises output in ways that lead to higher demand for labor, and interacts with adjustments in labor supply. … journalists and even expert commentators tend to overstate the extent of machine substitution for human labor and ignore the strong complementarities between automation and labor that increase productivity, raise earnings, and augment demand for labor.”

Professor Autor was co-chair of MIT’s Work of the Future Task Force, which was launched in the spring of 2018 to better understand the impact AI and automation on jobs. The Task Force released an interim report in September of 2019. Its overriding conclusion was that the likelihood that AI and automation would wipe out major workforce sectors in the near future was exaggerated.

However, it raised important reasons for concern, especially the rising polarization of employment and wage distribution over the past few decades, which has disproportionately benefited high-skilled professionals while reducing opportunities for mid- and low-skilled workers. The report emphasized that “at a time of historic income inequality, a critical challenge is not necessarily a lack of jobs, but the low quality of many jobs and the resulting lack of viable careers for many people, particularly workers without college degrees.”

The Covid-19 pandemic came a few months later, pretty much turning our world upside down.

The Complex Interplay Between Cybersecurity and Regulatory Compliance

Cybersecurity threats have significantly increased since March of 2020 when much of the economy was forced online to help us cope with the Covid crisis, including a number of high profile attacks by international criminal groups and adversarial governments. This past June, FBI Director Christopher Wray compared the danger of ransomware attacks on US firms by Russian criminal groups to the 9/11 terrorist attacks. When Biden and Putin met in Geneva a few weeks later, cyberweapons control was at the top of the agenda, a spot previously occupied by the control of nuclear weapons.

It’s been clear for a while that in a world increasingly governed by digital data and transactions, our existing cybersecurity methods have been far from adequate. To learn more about this very important area, earlier this year I joined  CAMS, MIT’s interdisciplinary cybersecurity initiative, and started attending its research seminars.

At a recent seminar, I heard a very interesting presentation on Compliance and Cybersecurity by CAMS research affiliate Angelica Marotta. Her seminar was based on Convergence and divergence of regulatory compliance and cybersecurity, a recent paper she co-authored with MIT professor Stuart Madnick.

Marotta’s opening slide included succinct definitions of cybersecurity and compliance that highlight their different objectives:

• Cybersecurity is responsible for the “internal procedures established by a company to improve the security of its operations.”
• Compliance is responsible for the “external regulations established by governments or industries groups that must be met.”

Today, in order to be successful, every organization needs to be both compliant and cyber secure. But, the extent to which compliance helps or hinder security for an organization continues to be a very important research question.

The Supply Chain Economy - A New Categorization of the US Economy

A few weeks ago I attended The Supply Chain Economy: Understanding Innovation in Services, a virtual seminar sponsored by the Council on Foreign Relations with economists Mercedes Delgado and Karen Mills discussing their recent paper A New Categorization of the U.S. Economy.

The debate about the drivers of innovation and job creation has long been centered on manufacturing versus services. The predominant view has been that manufacturing drives good wages, economic growth, and innovation as measured by its large share of patents, while services provide lower-wage jobs, less innovation and significantly fewer patents.

But Delgado and Mills argue that categorizing the economy in terms of manufacturing versus services is no longer meaningful. Instead, they’ve proposed an alternative framework for understanding the drivers of innovation and economic performance that’s focused on the suppliers of both goods and services: the supply chain economy.

“A long academic and policy debate has focused on the role of the manufacturing capacity of a country in its economic and innovative performance,” wrote the authors. “This question has become even more relevant as the U.S. economy has shown a large decline in manufacturing employment in recent decades, in part due to increased import competition. In this debate, the predominant view is that a country's manufacturing capacity drives innovation because of externalities associated with the production of intermediate goods (e.g., machine tools, automation equipment, and semiconductors) that improve the efficiency of the innovation process. Most prior work on innovation focused on a narrow view of suppliers as producers of intermediate goods. However, in today's economy suppliers increasingly produce services (e.g., enterprise software).”

A Pandemic Is Fundamentally an Information Problem

A few weeks ago I attended a very interesting online seminar, Economics in the Age of Covid-19, by University of Toronto professor Joshua Gans. Over the past 18 months, professor Gans has been conducting research and writing extensively on the impact of Covid-19, including a number of articles, a newsletter, and two books. His key thesis is that a pandemic is fundamentally an information problem. If you know that someone you interact with is potentially infectious, you can take actions to limit the interactions. However, if you have to guess whether a person is infectious, you’re taking a risk. Not only can you become infected, but you might also pass that infection on to others.

“The difference between perfect knowledge and no knowledge is what causes an infectious disease to have an impact on social and economic interactions,” wrote Gans in The Pandemics Information Gap, first published in April of 2020, followed by an expanded second edition in November of 2020. “With perfect knowledge, some people get sick, they are isolated, and life is (for most of us) essentially unchanged. … perfect knowledge allows you to avoid all infected people. No knowledge makes it near certain that you will encounter at least one infected person.” Furthermore, when we don’t know who is infected, we have to act as if everyone is infected, which then leads to major economic and social disruptions, including near-empty offices and city centers, decreased travel and leisure activities, and learning from home instead of in school.

In his seminar, Gans cited the 2002 SARS outbreak in China, Hong Kong, and Taiwan and the 2015 MERS outbreak in South Korea as examples of pandemics that were quickly contained. With SARS and MERS, people only became infectious when they developed a fever, cough, and other easily identifiable flu-like symptoms. Anyone suspected of being infected could thus be quickly isolated before infecting many others. This made it possible to contain the SARS and MERS viruses within a few short months, and to suppress them completely a few months later.

The 2020 COVID-19 outbreak was different. About a third of the people infected with the virus were asymptomatic carriers who didn’t develop noticeable symptoms but were still capable of infecting others. Of the people who showed symptoms, around 80% were only mild to moderate. And, there was generally a delay of several days between the time a person first became infected and the appearance of the first symptoms. In other words, the information problem was relatively straightforward with SARS and MERS, which made them easier to manage and contain, whereas managing the information problem with COVID-19 has been much, much harder.

Why Our Judgements Are Often Flawed and What to Do About It

A few weeks ago I listened to a very interesting Freakonomics podcast hosted by University of Chicago economist Steven Levitt. In the podcast, Why Our Judgment is Flawed — and What to Do About It, Levitt interviewed Daniel Kahneman about his recent book, Noise: A Flow in Human Judgement, co-authored with Olivier Sibony and Cass Sunstein. Kahneman is Professor of Psychology and Public Affairs Emeritus at Princeton University. In 2002, he was awarded the Nobel Prize in Economics “for having integrated insights from psychological research into economic science, especially concerning human judgment and decision-making under uncertainty.”

Thinking, Fast and Slow, Kahneman’s 2011 bestseller, was about the major discoveries by psychologists and cognitive scientists that have led to our current understanding of judgement and decision-making over the past several decades. Up to the 1970s, the prevailing view among social scientists was that people are generally rational and in control of the way they think and make decisions. It was thought that people only departed from rational behaviors because powerful emotions like fear, hatred or love distorted their judgement.

These assumptions were challenged by the pioneering research of Kahneman and his long time collaborator Amos Tversky, who died in 1996. In a series of experiments, they demonstrated that human behavior often deviated from the predictions of the previous rational models, and that these deviations were due to the machinery of cognition, that is, to the biases and mental shortcuts or heuristics that we use for making everyday decisions, rather than to our emotional state.

Kahneman has been studying biases and how they lead to errors in judgement for most of his career. But a few years ago, he encountered another type of error, noise, that he hadn’t thought about earlier. Noise is “the sort of ignored stepsister of bias… the complement of bias. And in terms of the standard way of measuring accuracy and measuring error, bias and noise are completely independent of each other. … bias is really the average error. And noise is the variability of error, the standard deviation of errors.

Why Do We Work So Damn Much?

A few weeks ago, I listened to a very interesting podcast, Why Do We Work So Damn Much?, where podcast host, NY Times columnist Ezra Klein, interviewed anthropologist James Suzman. Suzman has devoted almost thirty years to studying and writing about the Ju’hoansi and other bushmen from the Kalahari Basin, who are among the world’s few remaining hunter-gatherer societies. He recently published Work: A Deep History from the Stone Age to the Age of Robots, a book about his research.

Modern humans emerged in Africa between 200,000 and 300,000 years ago. Our homo sapiens ancestors were hunter-gatherers for most of those years, collecting wild plants and hunting wild animals. Starting around 12,000 years ago, the agricultural revolution introduced the domestication of plants and animals, leading many hunter-gatherer groups to establish agricultural communities and villages.

The vast majority of hunter-gatherers disappeared a long time ago, but a few groups remain in isolated sections of Africa, Australia, the Amazon rainforest and the Arctic. Anthropologists have been studying these remaining hunter-gatherers to learn how they’ve been able to survive so much longer than other human groups, as well as to understand the behaviors and cultures that modern humans may have inherited from our closest ancestors.

Revitalizing US Manufacturing

“The COVID-19 pandemic has underscored manufacturing’s role in providing products that are critical to health, safety, national security, and the continuity of multiple industries,” said McKinsey in a recent discussion paper, Building a More Competitive US Manufacturing Sector. “It has also revealed the extent to which global supply chains are exposed to shocks and disruptions. All of this has occurred at a moment when new technologies, process innovations, and demand growth are reshaping the sector worldwide. The United States can seize on these developments to make its own manufacturing sector more competitive.”

Manufacturing jobs helped build the US middle class after WWII. In the 1950s, it accounted for roughly 30% of employment and close to 30% of GDP. But manufacturing has significantly declined in the intervening decades, now comprising only 8% of the workforce and 11% of GDP. Manufacturing growth has particularly slowed down over the past 30 years, from 4.9% in the 1990s to 1.4% in each of the past two decades.

Despite its dramatic decline, manufacturing continues to have a disproportionate impact on the US economy, accounting for 35% of productivity growth, 55% of patents, 70% of R&D spending, and 60% of exports. According to McKinsey, these outsize economic contributions uniquely position manufacturing to strengthen the US recovery over the long term.

Understanding the Impact of Cybersecurity on International Trade

The explosive success of the Internet in the 1990s led to a historical transition from the industrial age of the past two centuries to an economy and society increasingly based on global, digital interactions.  This transition has continued to advance over the past two decade with the advent of billions of smartphones, hundreds of billions of IoT devices, a wide variety of online applications and mobile apps, and huge amounts of data, all connected via Internet-based broadband networks.

Then came Covid-19. A recent McKinsey survey found that the pandemic has accelerated the overall adoption of digital technologies and applications by three to seven years in just a few months.

At the same time, cybersecurity threats have been growing. Large-scale fraud, data breaches, and identity thefts have become far more common. As we moved from a world of physical interactions and paper documents, to a world primarily governed by digital data and transactions, our existing cybersecurity methods have been far from adequate.

More recently, international cyberthreats have escalated, with a growing number of high profile attacks by criminal groups and adversarial governments. Cybersecurity is now invoked by governments as a major aspect of national security, as they focus on protecting their critical infrastructures and the overall wellbeing of their nations. In early June, for example, FBI Director Christopher Wray compared the danger of ransomware attacks on US firms by Russian criminal groups to the September 11 terrorist attacks. And, in a recent editorial, the NY times editorial board argued that ransomware attacks have emerged as “a formidable potential threat to national security,” given “their ability to seriously disrupt economies and to breach strategically critical enterprises or agencies,” urging governments that “It is a war that needs to be fought, and won.”

The New Joint Cyber Defense Collaborative

Following World War II and the onset of the Cold War with the Soviet Union, the US undertook a series of measures to strengthen the resilience of the nation. These included a significant expansion of government support for scientific research in universities and R&D labs, leading to product innovations from the private sector and better weapons from the defense industry which contributed to making the US the most prosperous and secure nation in the world.

In the 1950s the government enacted the National Interstate and Defense Highways Act, which led to the construction of the Interstate Highway System. The Act had a dual purpose: facilitating the economic growth of the country as well as supporting the country’s defense during a conventional or nuclear war should it be necessary.

And, last but far from least, in the late 1960s the Department of Defense launched ARPANET, the digital infrastructure that eventually became the Internet. ARPANET was designed as a flexible digital network that would enable computers to continue to communicate with individuals and with each other following a military attack.

Fortunately, we never had to test the Internet’s ability to keep the US going following an attack or invasion. But, who would have thought that 50 years after the launch of ARPANET, it would be a global pandemic that’s been testing the Internet’s ability to fulfill its original objective of keeping nations and economies going during arguably the biggest shock the world has experienced since WWII.

The Coming Era of Productivity Growth

“The last 15 years have been tough times for many Americans, but there are now encouraging signs of a turnaround,” wrote economists Erik Brynjolfsson and Georgios Petropoulos in The Coming Productivity Boom, a recent opinion article in the MIT Technology Review. “Productivity growth, a key driver for higher living standards, averaged only 1.3% since 2006, less than half the rate of the previous decade. But on June 3, the US Bureau of Labor Statistics reported that US labour productivity increased by 5.4% in the first quarter of 2021. What’s better, there’s reason to believe that this is not just a blip, but rather a harbinger of better times ahead: a productivity surge that will match or surpass the boom times of the 1990s.”

After growing at an average annual rate of around 2.8% between 1947 and 1973, US productivity has significantly slowed down, except for the Internet-driven productivity boost between 1996 and 2004. Despite the relentless advances of digital technologies over the past 15 years, - from smartphones and broadband wireless to cloud computing and machine learning, - productivity has only grown at an anemic 1.3%, between 2006 and 2019. Most OECD countries have seen similar slowdowns.

What accounts for this puzzling so-called productivity paradox and when might it finally end? Over the past several years, Brynjolfsson and his various collaborators have explored this question, first at MIT where he was faculty director of the Initiative on the Digital Economy, and since 2020 at Stanford, where he’s Director of the Stanford Digital Economy Lab. Brynjolfsson discussed alternative explanations for the paradox at a recent MIT conference.

The Post-Pandemic Future of Work: An Optimistic Outlook

“The COVID-19 pandemic-induced lockdowns and related global recession of 2020 have created a highly uncertain outlook for the labour market … millions of workers have experienced changes which have profoundly transformed their lives within and beyond work, their well-being and their productivity,” said the World Economic Forum (WEF) in The Future of Jobs Report 2020, published in October, 2020. “Comparing the impact of the Global Financial Crisis of 2008 on individuals with lower education levels to the impact of the COVID-19 crisis, the impact today is far more significant and more likely to deepen existing inequalities.”

The Economist  was considerably more optimistic in a special report on The Future of Work in its April 10 issue, which included several articles on the subject. “A jobs rebound, shifting politics and technological change could bring a golden age for labour in rich countries,” said the overview article. “It might seem premature to predict a wonderful world of work only a year on from a labour-market catastrophe. But America is showing how rapidly jobs can come back as the virus recedes. In the spring of 2020 the country’s unemployment rate was nearly 15%. Now it is already just 6% after a year containing five of the ten best months for hiring in history.”

The key reason for The Economist’s optimistic outlook is that as labor markets recovers, two deeper shifts are unfolding: a political environment which is becoming friendlier to workers than it’s been in decades; and an accelerated digital economy which promises to bring about faster productivity growth. Let me briefly summarize each of these two shifts.

The Three Types of AI: Artificial, Authentic, and Augmented Intelligence

“The history of work - particularly since the Industrial Revolution - is the history of people outsourcing their labor to machines,” notes a recent article in the Harvard Business Review, - AI Should Augment Human Intelligence, Not Replace It, - by National University of Singapore professor David De Cremer and chess grandmaster Garry Kasparov. “While that began with rote, repetitive physical tasks like weaving, machines have evolved to the point where they can now do what we might think of as complex cognitive work, such as math equations, recognizing language and speech, and writing. Machines thus seem ready to replicate the work of our minds, and not just our bodies.”

Throughout the Industrial Revolution there were periodic panics about the impact of automation on jobs, going back to the so-called Luddites, - textile workers who in the 1810s smashed the new machines that were threatening their jobs. Automation does indeed substitute for labor. However, automation also complements labor, raising economic outputs in ways that often lead to more long-run employment, not less.

Most jobs involve a number of tasks or processes. Some of these tasks are more routine in nature, while others require judgement, social skills and other human capabilities. The more routine, rules-based the task, the more amenable it is to automation. But just because some of the tasks have been automated, does not imply that the whole job has disappeared. To the contrary, automating the more routine parts of a job will often increase the productivity and quality of workers by complementing their skills with machines and computers, as well as enabling them to focus on those aspect of the job that most need their attention.

What Might the World Be Like in 2040?

The mission of the National Intelligence Council (NIC) is to lead intelligence integration and long-term strategic thinking across a wide variety of sources, including the US Intelligence Community, policy makers, and experts in academia and the private sector. Every four years, the NIC develops a Global Trends report that examines the key trends and uncertainties that will shape the global environment during the next two decades. This is done to provide the incoming administration with a framework for long-range strategic policy assessment. Global Trends 2040 - A More Contested World (GT2040), the latest NIC report, was published in March, 2021, a few weeks after President Joe Biden’s inauguration. Let me briefly discuss.

Key Recurring Themes

“During the past year, the COVID-19 pandemic has reminded the world of its fragility and demonstrated the inherent risks of high levels of interdependence,” notes the report in its introduction.  Not surprisingly, given that we’ve been living through the most significant global disruption since WW2, GT2040 paints a rather dark picture of what lies ahead.

“In coming years and decades, the world will face more intense and cascading global challenges ranging from disease to climate change to the disruptions from new technologies and financial crises. These challenges will repeatedly test the resilience and adaptability of communities, states, and the international system, often exceeding the capacity of existing systems and models. This looming disequilibrium between existing and future challenges and the ability of institutions and systems to respond is likely to grow and produce greater contestation at every level.” As a NY Times editorial observed, “Experts in Washington who have read these reports said they do not recall a gloomier one.”

Leveraging Cloud Computing to Enhance the Nation’s Cybersecurity

There’s clearly an urgent need to significantly improve the security and resilience of IT systems and applications in light of the growing threat of cyberattacks, which FBI director Christopher Wray recently compared to addressing the challenge of global terrorism following the 9/11 attack. Earlier this week, the NY Times published this front page article - Once, Superpower Summits Were About Nukes. Now, It’s Cyberweapons, that said: “The rising tempo and sophistication of recent attacks on American infrastructure - from gasoline pipelines running up the East Coast, to plants providing a quarter of America’s beef, to the operations of hospitals and the internet itself - has revealed a set of vulnerabilities no president can ignore.” On May 12, President Biden issued an Executive Order to Improve the Nation’s Cybersecurity, a welcome and very important step.

Cloud-based technologies and Cloud Service Provides (CSPs) can play a major role in improving the nation’s cybersecurity. Over the years, CSPs have invested billions in cloud security, hired thousands of top cyber experts, and developed an array of new tools and methods. CIOs generally agree that the security on cloud platforms is superior to that of in-house data centers, a major reason why the top IDC prediction for the post-pandemic new normal was that “By the end of 2021, based on lessons learned, 80% of enterprises will put a mechanism in place to shift to cloud-centric infrastructure and applications twice as fast as before the pandemic.”

“Cloud computing drives innovation and productivity across the economy, just as the electric grid did a century ago - yet it is more capable and dynamic.” This is the overriding message of Secrets From Cloud Computing’s First Stage: An Action Agenda for Government and Industry, a report by Bill Whyman that was recently published by the Information Technology & Innovation Foundation (ITIF). As someone who’s long been following and writing about cloud computing, I found the report quite instructive. It includes a very good introduction to cloud computing, its economic impact and market dynamics, and the areas where cloud particularly excels. But, it also addresses the key challenges that cloud must overcome to fully achieve its benefits, as well as the need for a policy agenda for cloud computing, - a very important area that hasn’t received as much focus.

The Emergence of Central Bank Digital Currencies

Bitcoin was created in October of 2008 with the release of Bitcoin: A Peer-to-Peer Electronic Cash System, the original design paper which also introduced the blockchain architecture. A decade later, The Economist published a detailed evaluation of Bitcoin which succinctly concluded that “Bitcoin and other cryptocurrencies are useless.”

“Bitcoin, the first and still the most popular cryptocurrency, began life as a techno-anarchist project to create an online version of cash, a way for people to transact without the possibility of interference from malicious governments or banks,” it further argued. “A decade on, it is barely used for its intended purpose. Users must wrestle with complicated software and give up all the consumer protections they are used to. Few vendors accept it. Security is poor. Other cryptocurrencies are used even less.”

But last month, the May 8 issue of The Economist reached a very different conclusion in its assessment of central bank digital currencies (CBDCs), - i.e., e-dollars, e-yuans, or e-euros, - which it called “The digital currencies that matter.”

“Bitcoin has gone from being an obsession of anarchists to a $1trn asset class that many fund managers insist belongs in any balanced portfolio. … Yet, as our special report explains, the least noticed disruption on the frontier between technology and finance may end up as the most revolutionary: the creation of government digital currencies, which typically aim to let people deposit funds directly with a central bank, bypassing conventional lenders. These govcoins are a new incarnation of money. They promise to make finance work better but also to shift power from individuals to the state, alter geopolitics and change how capital is allocated. They are to be treated with optimism, and humility.”

Can We Look Forward to a New Decade of Innovation?

Can we  look forward to a new decade of innovation, asked The Economist in its January 16 issue. “The 2010s were marked by pessimism about innovation,” notes the issue’s overview article. “Productivity growth was lackluster and the most popular new inventions, the smartphone and social media, did not seem to help much… Promising technologies stalled, including self-driving cars, making Silicon Valley’s evangelists look naive.”

“Today a dawn of technological optimism is breaking,” adds the article. Some giddily predict a new decade of progress, - a kind-of 21st century roaring Twenties. While some of this optimism may be overblown, “there is a realistic possibility of a new era of innovation that could lift living standards, especially if governments help new technologies to flourish.”

There are historical precedents for such optimism. The Roaring Twenties was a decade of economic growth and widespread prosperity, as the country recovered from the dual devastations of World World I and the Spanish flu pandemic. Technological advances like electrification, consumer appliances, the mass production of cars, and the advent of commercial aviation transformed the US into the richest country in the world.

Then following World War II and the onset of the Cold War, the federal government significantly expanded its support of R&D in the private and public sectors, making the US the undisputed leader in science, engineering, medicine and other disciplines. The blueprint for R&D in post-war America was laid out by presidential science advisor Vannevar Bush in his 1945 report, Science The Endless Frontier: “New knowledge can be obtained only through basic scientific research” conducted in universities and research labs, which is then applied to develop new products by the private sector and new and improved weapons by the defense sector.

The Urgent Need for Wide-Scale Upskilling

Few topics are as important as the future of work in our 21st century digital economy. In the spring of 2018 MIT President Rafael Reif commissioned a task force on the Work of the Future to address whether our rapidly advancing technologies will not only raise economic output and the wealth of nations, but enable people to attain higher living standards and better working conditions. After working across MIT for over two and a half years, the task force released its final report in November, 2020.

“Amidst a technological ecosystem delivering rising productivity, and an economy generating plenty of jobs (at least until the COVID-19 crisis), we found a labor market in which the fruits are so unequally distributed, so skewed towards the top, that the majority of workers have tasted only a tiny morsel of a vast harvest,” was the overriding conclusion of the task fore. But, it further argued that with better policies in place, more people could enjoy good careers even as new technologies transform the very nature of work.

Similar conclusions were reached by Upskilling for Share Prosperity, a report published in January, 2021 by the World Economic Forum (WEF) in collaboration with PwC. “Millions of people are already being left behind because of volatile market conditions, the effects of COVID-19, or because they work in industries that are being replaced by new sectors,” said the report… There is an enormous opportunity to reconfigure the world of work at this critical juncture and embark on an upskilling revolution that will give people across the world the ability to participate fully in the future of work, whatever that might be.”

A New Contract with the Middle Class

“The U.S. is a middle-class nation,” says the opening sentence of A New Contract with the Middle Class, an essay by Richard Reeves and Isabel Sawhill that was recently published by the Brookings Institution. “Since our nation’s founding, the American Dream has always been based on an implicit understanding - a contract if you will - between individuals willing to work and contribute, and a society willing to support those in need and to break down the barriers in front of them.” The essay is part of the Future of the Middle Class initiative launched by Brookings in November, 2018.

Why focus on the middle class? The reason, notes the essay, is that this is how the majority of Americans define themselves. “An aristocratic leisure class and a welfare-dependent underclass are equally unappealing to most Americans.” It’s why paid work is seen as so important. Americans want a society where everybody has the chance to “make something of themselves.” Joining the middle class is the very core of the American Dream, - the promise that anyone can get ahead and achieve success and prosperity through talent and hard work.

Who is in the middle class? While there are multiple definitions, most are based on income, partly because data on income are widely available, and it’s easier to come up with concrete, quantifiable definitions. But also because income tends be highly correlated with other attributes of social class, such as educational level, job status, consumer preferences, behaviors, aspirations, and cultural tastes.

The essay defines middle class as those in the middle 60% of household income distribution. “To be middle class, a household of three would have an income between $40,000 and $154,000,” - neither poor nor prosperous. “The middle class, by our definition, is diverse: 59 percent white, 12 percent Black, 18 percent Hispanic, and 6 percent Asian. Within a few decades, whites will make up the minority of middle-class families.”

The Post-Pandemic Outlook for Technology, Jobs, and Skills

“The COVID-19 pandemic-induced lockdowns and related global recession of 2020 have created a highly uncertain outlook for the labour market,” said the World Economic Forum (WEF) in The Future of Jobs Report 2020. The pandemic has caused labor markets to change significantly faster than previously expected. What used to be considered the future of work has already arrived. As McKinsey noted in a May, 2020 article: “we have vaulted five years forward in consumer and business digital adoption in a matter of around eight weeks.”

The WEF report aims to shed light on the post-pandemic outlook for technology adoption, jobs and skills over the next five years, including detailed quantitative profiles on 15 industry sectors and 26 advanced and emerging countries. The report is based on a survey of senior executives from nearly 300 global companies which collectively employ 8 million workers. The survey asked 49 questions on the outlook for their companies’ workforce through 2025, including major trends affecting the labor market, the technologies their companies are adopting, the expected evolution of jobs and skills, their training and reskilling programs, and the near-term impact of the pandemic on their workforce.

“The global shift to a future of work is defined by an ever-expanding cohort of new technologies, by new sectors and markets, by global economic systems that are more interconnected than in any other point in history, and by information that travels fast and spreads wide. … As a new global recession brought on by the COVID-19 health pandemic impacts economies and labour markets, millions of workers have experienced changes which have profoundly transformed their lives within and beyond work, their well-being and their productivity. One of the defining features of these changes is their asymmetric nature - impacting already disadvantaged populations with greater ferocity and velocity.”

The Intriguing Nature of Non-Fungible Tokens

The blockchain first came to light in 2008 as the digital ledger for bitcoin transactions. The blockchain creator’s original vision was limited to enabling peer-to-peer bitcoin transactions with no need for a bank or government agency to certify the validity of the transactions. But, like the Internet, electricity and other transformative technologies, blockchain soon transcended its original objectives.

Over the years, blockchain technologies have evolved along two major lines. One continues to focus on blockchain as the underlying platform for bitcoin, as well as a wide variety of cryptoassets, such as digital tokens and cryptocurrencies. The other focuses on the use of blockchain in the business world, - a kind of Internet 2.0. The cryptocurrency camp is based mostly on public permissionless blockchains, which anyone can join and require some kind of proof-of-work or proof-of-stake systems. The business camp, - best characterized by Hyperledger, - is based on private or public permissioned blockchain networks to support transactions among institutions that need not know nor trust each other.

Given my professional history with the Internet and e-business, I’ve been almost exclusively focused on the business camp for two major reasons. First, blockchain technologies can help us enhance the security of Internet transactions and data, by developing a layer with the required standard services and their open source implementations for secure communication, storage and data access. And second, blockchain technologies can significantly improve the efficiency, resilience, and management of supply chains, financial services, and other complex global applications involving multiple institutions across multiple countries.

I have not paid much attention to bitcoin or other cryptoassets. But recently, I’ve become quite intrigued by non-fungible tokens (NFTs). To me, NFTs are further evidence that, as with the Internet of Things (IoT), we’re increasingly living in a hybrid physical-digital world. Let me explain.

The Changing Nature of the Liberal Arts in the Digital Economy

What is meant by the liberal arts? Here is a succinct dictionary definition: “The academic course of instruction intended to provide general knowledge and usually comprising the arts, humanities, natural sciences, and social sciences, as opposed to professional or technical subjects.” And, here is a more thorough explanation: “A liberal arts education is by nature broad and diverse, rather than narrow and specialized…  [it] is not intended to train you for a specific job, though it does prepare you for the world of work by providing you with an invaluable set of employability skills, including the ability to think for yourself, the skills to communicate effectively, and the capacity for lifelong learning.”

Over the past few decades, business, engineering, and other professions not previously associated with the liberal arts have embraced a number of its attributes. A few years ago, for example, I came across an article about the efforts of Roger Martin to transform business education. At the time, Martin was the Dean of the Rotman School of Management at the University of Toronto. He had long been advocating “that students needed to learn how to think critically and creatively every bit as much as they needed to learn finance or accounting. More specifically, they needed to learn how to approach problems from many perspectives and to combine various approaches to find innovative solutions.” Such a transformation would require business schools to move into territory more traditionally associated with the liberal arts.

Similarly, in a 2006 report, the National Academy of Engineering called for reforming engineering education. “New graduates were technically well prepared but lacked the professional skills for success in a competitive, innovative, global marketplace. Employers complained that new hires had poor communication and teamwork skills and did not appreciate the social and nontechnical influences on engineering solutions and quality processes.”

A few years ago, USC’s Annenberg School of Communications and Journalism conducted a study to better understand the key competencies companies were looking for. Future leaders, the study found, must be strong in quantitative, technical and business skills. But to advance in their careers, they also need to be good strategic thinkers and must have strong social and communications skills. Companies were looking for so called T-shaped professionals who combine deep quantitative, technical, problem solving hard skills with broad multidisciplinary, communications, and social soft skills that enable them to collaborate with experts in other fields.

New Directions for Government in the Digital Age

Over the past few decades, economies and societies around the world have been going through historical transformations as they transition from the industrial age of the past two centuries to a 21st century digital age. Companies - especially large, global corporations - have leveraged digital innovations to improve their productivity and competitiveness and adapt better to these powerful technology and market changes.

In 2010, the Technology CEO Council released a report recommending that governments embrace the information technologies (IT) and organizational best practices that the private sector was successfully applying: “By harnessing major technological shifts and adopting best business practices, we can not only make our government far more productive, but also foster greater innovation in areas ranging from healthcare to education and energy - innovation that will generate economic growth and job creation.”

But governments have continued to lag the private sector, and risk falling further behind as the pandemic accelerated the digital transformations that are helping companies cope with the crisis. “We’ve seen two years’  worth of digital transformation in two months,” as companies adapt to stay open for business “in a world of remote everything,” said Microsoft CEO Satya Nadella in April 2020. A month later, McKinsey & Company added, “We have vaulted five years forward in consumer and business digital adoption in a matter of around eight weeks.”

The authors of a recently published report, “New Directions for Government in the Second Era of the Digital Age,” argue that governments should exploit this fast-moving era of technology in their own operations, for the overall benefit of their nations. The 120-page report was authored by Don Tapscott, Kirsten Sandberg, and Anthony Williams from the Blockchain Research Institute (BRI), in collaboration with the Chamber of Digital Commerce and experts from several countries. The BRI is a global think tank dedicated to the strategic implications of blockchain and related technologies to business, government and society. I am a research contributor at the BRI.

The report aims to assist government leaders around the world, but is particularly focused on the opportunities and challenges facing the new US administration.

Is Work-from-Anywhere Here to Stay?

Remote work has been around for a few decades, but took off in the mid-late 1990s with the explosive growth of the Internet.  There were predictions that the Internet would lead to the decline of cities, because technology was making location less relevant to our work and personal lives.  Why would anyone choose to live in an expensive, stressful metropolitan area and endure a long daily commute?  However, instead of declining, superstar cities continued to attract talented, ambitious knowledge workers, and to generate the greatest levels of economy activity and innovation.

But, even before the pandemic, “a movement was brewing within knowledge-work organizations,” wrote Harvard professor Prithwiray (Raj) Choudhury in a recent Harvard Business Review article, Our Work-from-Anywhere Future.  “Personal technology and digital connectivity had advanced so far and so fast that people had begun to ask, ‘Do we really need to be together, in an office, to do our work?’”

“We got our answer during the pandemic lockdowns.  We learned that a great many of us don’t in fact need to be colocated with colleagues on-site to do our jobs.  Individuals, teams, entire workforces, can perform well while being entirely distributed - and they have.  So now we face new questions: Are all-remote or majority-remote organizations the future of knowledge work?  Is work from anywhere (WFA) here to stay?”

Trends That Will Likely Shape a Highly Uncertain Year

A few weeks ago The Economist published The World in 2021, it’s 35th annual look at the economic, political, social and cultural trends that will likely shape the coming year.  Overall, 2021 will be a year of unusual uncertainty given the still ongoing pandemic, the uneven economic recovery, and the turbulent political environment in the US, Britain, and a number of other countries.  “The great prize on offer is the chance of bringing the coronavirus pandemic under control,” wrote the issue’s editor Tom Sandage.  “But in the meantime risks abound, to health, economic vitality and social stability.”

The World in 2021 highlights ten specific trends.  Let me focus my discussion on three of them.

The Evolution of American Capitalism - Tweaks, Reforms, or Wholesale Change?

“American capitalism has evolved time and again, and we may be poised for another such shift,” said a recent McKinsey article, Rethinking the future of American capitalism, by James Manyika, Gary Pinkus, and Monique Tuin.  “Capitalism has contributed to significant gains in economic growth and prosperity throughout its history.  But at a time of growing public discontent about rising inequality, heightened competition from economies with different models, and existential threats including from climate change, capitalism in its current form - and American capitalism in particular - may face its most serious test.”

Adam Smith, the 18th century Scottish philosopher and economist, is generally considered the father of free-market, free-trade capitalism.  Smith is most famous for The Wealth of Nations, published in 1776 and generally regarded as the first work of modern economics.  He’s also well known for his famous metaphor of the invisible hand - “the free market, while appearing chaotic and unrestrained, is actually guided to produce the right results by this so-called invisible hand.”

Smith believed in a balanced approach to capitalism.  On one side is the fierce competition and self-interest inherent in open, free markets.  On the other, - as he wrote in The Theory of Moral Sentiments, - is the sympathy and community support that’s required to achieve beneficial results in well functioning, stable societies.

How Covid Is Reordering the Global Economy

The October 10 issue of The Economist includes a special report on the impact of covid-19 on the global economy, with eight article on the subject.  “The pandemic has caused the world’s economies to diverge,” notes the issue’s overview article.  “But its long-term impact will be even more far-reaching… huge gaps between the performance of countries are opening up - which could yet recast the world’s economic order.”

According to the OECD, whereas China’s economy is expected to be 10% larger by the end of 2021 than it was in pre-pandemic 2019, the US economy will be essentially the same size, while the economies of the Euro area, the UK, Japan and South Korea will see a decline by the end of 2021 compared to their pre-pandemic levels.

“The covid-19 pandemic will accelerate change in the world economy,” says The Economist.  It’s becoming increasingly clear that “the pandemic will lead to immense structural changes in the global economy: less globalized, more digitized, and less equal.”  Supply chains will bring production closer to home to cut risks.  Office workers will continue to work from their homes for at least part of the week.  Lower paid urban service workers will face unemployment and need to find new jobs.  The gulf between Wall Street and Main Street will widen.  “The challenge for democratic governments will be to adapt to all these changes while maintaining popular consent for their policies and for free markets.”

Let me discuss the three key areas where The Economist expects long-lasting changes: globalization, digitization and inequality.

What Is Objective Reality?

I learned about The Constitution of Knowledge, - a 2018 National Affairs essay by author and journalist Jonathan Rauch, - from a recent OpEd by NY Times columnist David Brooks.  In his “remarkable essay,” wrote Brooks, “Rauch pointed out that every society has an epistemic regime, a marketplace of ideas where people collectively hammer out what’s real.  In democratic, nontheocratic societies, this regime is a decentralized ecosystem of academics, clergy members, teachers, journalists and others who disagree about a lot but agree on a shared system of rules for weighing evidence and building knowledge.”

Rauch’s essay asks a very important and timely question: what is objective reality?  “In everyday vernacular, reality often refers to the world out there: things as they really are, independent of human perception and error,” he wrote.  “Reality also often describes those things that we feel certain about, things that we believe no amount of wishful thinking could change.  But, of course, humans have no direct access to an objective world independent of our minds and senses, and subjective certainty is in no way a guarantee of truth.”

The distinction between subjective opinion and objective facts is nicely captured in this widely used quote: People Are Entitled To Their Own Opinions But Not To Their Own Facts.  It’s the essence of any discussion about objective reality.  However, the distinction between opinion and facts has long been rather porous in totalitarian regimes, as well as in highly polarized periods, - like our own.

On top of which, we now have the impact of social media.  “Over the last decade, we’ve doused our kindling fire of human interaction with high-­octane gasoline,” wrote MIT professor Sinan Aral in his recently published book The Hype Machine.  “We’ve constructed an expansive, multifaceted machine that spans the globe and conducts the flow of information, opinions, and behaviors through society.”  We now have a global social media ecosystems that’s been designed to stimulate and manipulate the human psyche, and to persuade us that there’s no such thing as objective facts and objective reality.

How to Emerge Stronger in the Post-Pandemic New Normal

“What now?,” asked a recent McKinsey article on the implications of Covid for business.  “Over the past six months, they have reorganized supply chains, set up remote operations, and made tough financial decisions.  But without a COVID-19 vaccine yet available, not much feels different, and the summer pause hasn’t done much to relieve fatigue.”

“One priority, then, is to reenergize the organization - to act rather than react.  Even as the COVID-19 crisis continues to create a world of uncertainty, the goal must be to rebuild for the longer term.  Companies that are strong and resilient will be better placed to survive and prosper.  Those are qualities that can’t be taken for granted; they need to be cultivated.” 

But, how can a company, - regardless of size or industry, - formulate a rebuilding strategy for the longer term in such an uncertain environment?  As former president Dwight Eisenhower famously said when he was the overall Commander of Allied Forces in WWII: “In preparing for battle I have always found that plans are useless but planning is indispensable.”  In other words, rather than doing so on-the-fly, planning during highly uncertain times requires that companies thoroughly map out their rebuilding strategy, and quickly and flexibly react to the continuing changing circumstances.

Are There Limits to the Predictability of Elections?

The elegant mathematical models of classical mechanics depict a world in which objects exhibit deterministic behaviors. These models make perfect predictions within the accuracy of their human-scale measurements.

But, once you start dealing with atoms, molecules and exotic subatomic particles, you find yourself in a very different  world, one with somewhat counter-intuitive behaviors governed by the laws of quantum mechanics.  The orderly, predictable models of classical physics have now given way to wave functions, uncertainty principles, quantum tunneling and wave-particle dualities.

But, the world of the very small is not the only one with non-deterministic behaviors.  So are highly complex systems, especially those systems whose components and interrelationships are themselves quite complex.  This is the case with social systems, which are based on individuals, groups, and institutions.  It’s quite a challenge to make accurate predictions in such systems due to the the dynamic nature of human behaviors.  Terms, like emergence, long tails, and butterfly effects - every bit as fanciful as quarks, charm and strangeness, - are part of the social systems lexicon.

Which brings us to the 2020 US election. “The polls were wrong again, and much of America wants to know why,” wrote NY Times journalist David Leonhardt in a recent article. “This is a disaster for the polling industry and for media outlets and analysts that package and interpret the polls for public consumption, such as FiveThirtyEight, The New York Times’ Upshot, and The Economist’s election unit,” said David Graham  in The Atlantic.

Building Better Jobs in an Age of Intelligent Machines

On November 18, the MIT Task Force on the Work of the Future released its final report, The Work of the Future: Building Better Jobs in an Age of Intelligent Machines.  The Task Force was commissioned in the spring of 2018 by MIT President Rafael Reif to address what may well be the most critical question of the digital economy: as emerging technologies raise aggregate economic output and the wealth of nations, will they also enable people to attain higher living standards, better working conditions, greater economic security, and improved health and longevity?  An interim report was released in September, 2019.

“Amidst a technological ecosystem delivering rising productivity, and an economy generating plenty of jobs (at least until the COVID-19 crisis), we found a labor market in which the fruits are so unequally distributed, so skewed towards the top, that the majority of workers have tasted only a tiny morsel of a vast harvest,” is the Task Force overriding conclusion.  Yet, it argues that with better policies in place, more people could enjoy good careers even as new technologies transform the very nature of work.

What Is the Social Responsibility of Business?

On September 13, 1970, the NY Times Magazine published an essay by University of Chicago economist and 1976 Nobel Prize recipient Milton Friedman - “The Social Responsibility of Business is to Increase its Profits.”  Friedman’s essay turned out to be one of the most influential ever published in the world of business.  To mark its 50th anniversary, the NY Times reached out to 22 business leaders and top economists and asked their opinion on what Friedman got right and wrong in his essay.

“Friedman, who died in 2006 at the age of 94, was no mere economist; he was a kind of celebrity,” noted Andrew Ross Sorkin, NY Times financial columnist and editor.  “He became a regular on the talk-show circuit.  PBS even gave him a 10-part series. His economic theories, among the most consequential of the 20th century, still hold sway over large parts of corporate America, maybe none more so than this 1970 manifesto on corporate governance.”

“In a free-enterprise, private-property system, a corporate executive is an employee of the owners of the business,” wrote Friedman in his 1970 essay.  “He has direct responsibility to his employers.  That responsibility is to conduct the business in accordance with their desires, which generally will be to make as much money as possible while conforming to the basic rules of the society, both those embodied in law and those embodied in ethical custom.”  Business concerns beyond making profit, - such as “promoting desirable social ends,” or “providing employment, eliminating discrimination, avoiding pollution and whatever else,” - amounted to “preaching pure and unadulterated socialism.”

To better appreciate the importance of Friedman’s essay, let’s take a brief look at the historical context around the time it was published.

The Public Face of Science - Implications of the Covid Crisis

The Public Face of Science was launched four years ago by the American Academy of Arts and Sciences to better understand the complex relationship between scientists and the American public.  The initiative has now published three reports.

The first, Perceptions of Science in America, was published in 2018.  It found that a majority of Americans have expressed a great deal of confidence in the scientific community, a confidence which has remained stable over the past thirty years.  But, it also found that confidence in science varied based on demographics, including age, race, educational attainment, regional location, political affiliation and other characteristics.  The report recommended additional research to better understand why certain topics were particularly controversial, especially climate change, vaccine safety, and genetically modified foods.

It was followed by Encountering Science in America, which was published in 2019.  This second report explored the diverse and expanding range of opportunities for people to learn about science outside the classroom, including visits to science centers and museums, general news sources, online information, social media, and entertainment.  It concluded that such a complex landscape calls for a multifaceted approach to the public face of science, and recommended additional research to better understand how effective communications and engagements shape the public’s interest in their understanding and support of science.

Priorities for the Future, the third and final report, was published in August of 2020.  While the report doesn’t directly address the implications of Covid-19 to the Public Face of Science initiative, it does so in an accompanying document which highlights the critical role played by science in ensuring the well-being of individuals and society during the pandemic.  “[T]he experience with COVID-19 reinforces the need for continuing thoughtful work to address public access to reliable scientific content and to enhance the public’s capacity to identify and reject misinformation and disinformation (intentionally false information).”

AI Technologies Are Fundamentally Changing How Work Gets Done

After decades of promise and hype, artificial intelligence is finally becoming one of the most important technologies of our era.  AI technologies, like machine learning, are clearly having a major impact on the very nature of work.  But, how can we best quantify their impact on the actual evolution of jobs?

The best approach for exploring the relationship between technology and jobs is to look at the individual tasks that comprise a job.  Most jobs involve a number of tasks.  Some of these tasks are relatively routine and based on well-understood rules, while others require judgement, social skills and other human capabilities.  The more routine and rules-based the task, the more amenable it is to automation. 

However just because some of its component tasks have been automated, does not imply that the whole job has disappeared.  To the contrary, automating the more routine parts of a job will often increase the productivity and quality of workers by complementing their skills with technologies and tools, thus enabling them to focus on those aspect of the job that most need their attention.  While automation  substitutes for labor, automation also complements labor, increasing productivity and other economic outputs in ways that often raise the demand for and earnings of workers.

“The emergence of artificial intelligence (AI) and machine learning (ML) poses a new set of opportunities - and challenges - for work and workers,” said The Future of Work: How New Technologies Are Transforming Tasks, a research report released last Fall by the MIT-IBM Watson AI Lab.  “The tasks that can be done by machine learning are much broader in scope than previous generations of technology have made possible.  The expanded scope will change the value employers place on tasks, and the types of skills most in demand.”

America’s Obsession with Economic Efficiency

The belief that efficiency is fundamental to competitive advantage has turned management into a science, whose objective is the elimination of waste, - whether of time, materials, or capital, - wrote Roger Martin in “The High Price of Efficiency,” a January 2019 article in the Harvard Business Review.  Martin is professor and former dean of the Rotman School of Management at the University of Toronto, as well as a prolific writer.

“Why would we not want managers to strive for an ever-more-efficient use of resources?,” asked Martin.  Of course we do.  But, an excessive focus on efficiency can produce startlingly negative effects.  To counterbalance such potential negative effects, companies should pay just as much attention to a less appreciated source of competitive advantage: resilience,  - “the ability to recover from difficulties - to spring back into shape after a shock,” he presciently added a year before the advent of Covid-19.

In his recently published book, When More Is Not Better: Overcoming America's Obsession with Economic Efficiency, Martin expanded on his HBR article, arguing that an excessive focus on efficiency is not only detrimental to business but constitutes a serious threat to America’s democratic capitalism.  “Throughout the first nearly two and a half centuries of America’s existence as a sovereign state, most citizens experienced an advance in their economic status in the overwhelming majority of those years.  Based on that trend, Americans have, unsurprisingly, used their votes throughout the years to support and perpetuate capitalism as America’s economic system.  But that consistent economic advance has stalled, and has been for a longer period than ever before in American history.”

The book is based on a six-year project on the future of America’s democratic capitalism by the Martin Prosperity Institute.  The project conducted in-depth interviews with a wide variety of Americans to understand what they thought about the directions of the country.  It excluded people in the top 10% of the income distributions, focusing instead on the vast majority of the populations, which includes people with household incomes ranging from $25,000 to $110,000 with a median of $75,000.

After Years of Promise and Hype, Is AI Once More Failing to Deliver?

The June 13 issue of The Economist included an in-depth look at the limits of AI, with seven articles on the subject.  “There is no question that AI - or, to be precise, machine learning, one of its sub-fields - has made much progress,” notes The Economist in the issue’s overview article.  “Computers have become dramatically better at many things they previously struggled with…  Yet lately doubts have been creeping in about whether today’s AI technology is really as world-changing as it seems.  It is running up against limits of one kind or another, and has failed to deliver on some of its proponents’ more grandiose promises.”

Transformative technologies, - remember the dot-com bubble, - are prone to hype cycles, when all the excitement and publicity accompanying their early achievements often lead to inflated expectations, followed by disillusionment if the technology fails to deliver.  But AI is in a class by itself, as the notion of machines achieving or surpassing human levels of intelligence has led to feelings of both wonder and fear over the past several decades.

The article reminds us that AI has gone through two such major hype cycles since the field began in the mid-1950s.  Early achievements, - like beating humans at checkers and proving logic theorems, - led researchers to conclude that machines would achieve human-level intelligence within a couple of decades.  This early optimism collapsed leading to the first so-called AI winter from 1974-1980.  The field was revived in the 1980s with the advent of commercial expert systems and Japan’s Fifth Generation project, but it didn’t last long, leading to the second AI winter from 1987-1993.

May the Network Force Be With You

May the Force Be With You has become part of popular culture since the words were first uttered in the 1977 Star Wars film.  As we know, The Force is a source of power for those who, like the Jedi, feel its flow.  “The network force is similar,” wrote Silicon Valley network expert and entrepreneur James Currier in Your Life is Driven by Network Effects.  “You don’t always see it, but it is exerting itself on you.  It wants something from you. Your network force proactively guides you down a path.”

“When you start to see that dialogue between you and your network, the push-pull, you see it everywhere.  The chaos of the world diminishes a bit and becomes more understandable and predictable. And you understand more why things are the way they are and why they stay that way.  Hopefully, it will also give you insights as to where you can push to change things that should be changed, not just about you, but about your company, your city, and your world.”

Over the past few decades, network forces have been influencing many aspects of business, the economy, and our social interactions.  The Internet’s universal reach and connectivity have led to increasingly powerful network effects, such as, for example, platform economies.

The Social Network Is the Computer

“Human beings have always been a social species,” writes MIT professor Sinan Aral in the opening paragraph of The Hype Machine, his recently published book.  “We’ve been communicating, cooperating, and coordinating with one another since we were hunting and gathering.”  Our increasingly complex social interactions have been the critical factor in the exponential increase of human cranial capacity over the past few million years.  “But today something is different.  Over the last decade, we’ve doused our kindling fire of human interaction with high-­octane gasoline.  We’ve constructed an expansive, multifaceted machine that spans the globe and conducts the flow of information, opinions, and behaviors through society.”

Professor Aral has been studying social media since its beginning in the early 2000s, when it was driven by the idealistic vision of connecting the world and providing free access to information.  The Hype Machine is what he now calls our global social media ecosystem.  This ecosystem has been designed to stimulate and manipulate the human psyche, “to draw us in and persuade us to change how we shop, vote, and exercise, and even who we love.”  His book nicely explains how the social media industrial complex works, how it affects us, and what we can do to help achieve its original vision while avoiding its later perils.  Let me discuss a few of its key points.

User-Based Free Innovation

In his 2016 book of the same title, MIT professor Eric von Hippel defines free innovation “as a functionally novel product, service, or process that (1) was developed by consumers at private cost during their unpaid discretionary time (that is, no one paid them to do it) and (2) is not protected by its developers, and so is potentially acquirable by anyone without payment - for free.” The book is available as a free download here.

Free innovation is a tightly constrained subset of commons-based peer production, - also known as open, collaborative innovation.  Participants in a commons-based peer production project can do so for monetary gains, either as individual users or as employees of a collaborating company, as has been the case with firms involved in the continuous development of Linux.  In contrast, while free innovation has potentially important economic impacts, it’s fundamentally not about money.

Free innovation is part of the household sector of national economies, carried out by the members of a household for their own consumption, using their own capital and unpaid labor.  “In just six countries surveyed to date, tens of millions of individuals in the household sector have been found to collectively spend tens of billions of dollars in time and materials per year developing products for their own use,” writes von Hippel.

How Will the Pandemic Reshape Labor Markets?

“The COVID crisis appears poised to reshape labor markets along at least four axes: telepresence, urban de-densification, employment concentration in large firms, and general automation forcing,” wrote MIT’s David Autor and Elisabeth Reynolds in a July essay on The Nature of Work After the COVID Crisis.   “Although these changes will have long-run efficiency benefits, they will exacerbate economic pain in the short and medium terms for the least economically secure workers in our economy, particularly those in the rapidly growing but never-highly-paid personal services sector.”

Autor and Reynolds are cochairs of the ongoing MIT Work of the Future task force, whose interim report was published in the (pre-Covid) Fall of 2019.  The report’s overriding conclusion was that the likelihood that AI and automation will wipe out major workforce sectors in the near future was exaggerated.  However, there were very important reasons for concern, in particular, the rising polarization of employment and wage distribution over the past few decades which has disproportionately benefited high-skilled professionals. Our most critical challenge, said the report, isn’t necessarily a lack of jobs, but the low quality of jobs and viable careers available to many workers, particularly those without college degrees.

“Despite our concerns about the distributional consequences of advancing technologies, until the COVID crisis began, we were sanguine about the prospects for ongoing employment growth, even in the face of lackluster wage growth,” said the authors in their July essay.  “In the fall of 2019 we wrote, ‘We anticipate that in the next two decades industrialized countries will have more job openings than workers to fill them, and that robotics and automation will play an increasingly crucial role in closing these gaps’. The COVID crisis has upended our confidence in that prediction - not merely because COVID has generated mass unemployment in the short term, which it has, but also because the postcrisis trajectory now worries us.”

The AI Factory: A New Kind of Digital Operating Model

“Whether you’re leading a digital start-up or working to revamp a traditional enterprise, it’s essential to understand the revolutionary impact AI has on operations, strategy, and competition,” wrote Harvard professors Marco Iansiti and Karim Lakhani in “Competing in the Age of AI”, a recently published article in the Harvard Business Review (HBR).  Earlier this year, they also published a book of the same title, which expands on the ideas in the article and illustrates them with a number of concrete use cases.

The age of AI is being ushered by the emergence of a new kind of digital firm.  Rather than just relying on traditional business processes operated by its workers, these firms are leveraging software and data-driven algorithms to eliminate traditional constraints and transform the rules of competition.  Managers and engineers are responsible for the design of the new AI-based operational systems, but the system then runs the operations pretty much on its own.

“At the core of the new firm is a decision factory - what we call the AI factory,” note the authors.  “[T]he AI factory treats decision-making as a science.  Analytics systematically convert internal and external data into predictions, insights, and choices, which in turn guide and automate operational workflows…  As digital networks and algorithms are woven into the fabric of firms, industries begin to function differently and the lines between them blur.”

The Industrial Revolution transformed the economy by developing a scalable, repeatable approach to manufacturing.  The AI factory is now driving another fundamental transformation by industrializing the data gathering, decision making, and overall digital operations of 21st century firms.

Reconnecting Society and Reopening the Economy

A few months ago, MIT Connection Science held it’s annual Sponsors’ Meeting online.  The virtual meeting included a number of very interesting presentations.  Given its continuing importance, I want to focus my discussion on “Reconnecting Society After a Pandemic,” a talk given by visiting professor Esteban Moro. 

Moro started his presentation by showing a slide from this article.  The slide illustrates that if we had done nothing, or just relied on soft mitigation and herd immunity to contain the spread of the Covid-19 virus, the number of cases and deaths would have gone up very rapidly, - overwhelming healthcare systems around the world.  Instead, many national and state governments adopted two distinct sets of actions, the hammer and the dance.

The hammer is the somewhat draconian social distancing policies aimed at containing the spread of the virus, especially in regions like the New York metro area where the number of cases were escalating at a very rapid pace.  The dance starts once the spread of the virus has been brought under reasonable control, - albeit at the price of large economic costs and societal disruption.  The dance is the longer term effort to keep the virus contained until there’s an effective vaccine while reopening the economy and bringing life as close to normal as possible.

Are We Becoming a Decadent, Stagnating Society?

Earlier this year I read a very interesting essay, “The Age of Decadence”, by NY Times columnist Ross Douthat.  The essay is adapted from his recently published book The Decadent Society - How We Became the Victims of Our Own Success.  This long essay covers a lot of ground, from technology and innovation to politics and religion.  The essay was published in early February, before Covid-19 spread across the US.  I’ll discuss the original essay, but I do wonder how it would have been modified to reflect the impact of the pandemic.

“The real story of the West in the 21st century is one of stalemate and stagnation,” wrote Douthat.  “Everyone knows that we live in a time of constant acceleration, of vertiginous change, of transformation or looming disaster everywhere you look.  Partisans are girding for civil war, robots are coming for our jobs, and the news feels like a multicar pileup every time you fire up Twitter.  Our pessimists see crises everywhere; our optimists insist that we’re just anxious because the world is changing faster than our primitive ape-brains can process.” 

“But what if the feeling of acceleration is an illusion, conjured by our expectations of perpetual progress and exaggerated by the distorting filter of the internet?,” he asked.  What if we really inhabit an era in which repetition is more the norm than invention; in which new developments in science and technology consistently undercover; in which we’re comfortably aging, “no longer optimistic about the future… [while] growing old unhappily together.”  What if  “Our civilization has entered into decadence.”

Could AI Reshape the Global Balance of Power?

The National Security Commission on Artificial Intelligence (NSCAI) was established by the US Congress in Fiscal Year 2019 to “advance the development of artificial intelligence, machine learning, and associated technologies by the United States to comprehensively address the national security and defense needs of the United States.”  A few months ago, the 15 member Commission, - led by former Google CEO Eric Schmidt  and former deputy secretary of defense Robert Work, - released its interim report. The final report is due to be released in March, 2021.  It remains to be seen how the Covid-19 pandemic will impact the final report’s recommendations and release date.

“The convergence of the artificial intelligence revolution and the reemergence of great power competition… threaten the United States’ role as the world’s engine of innovation and American military superiority,” said the interim report in its opening statements.  “How the United States adopts AI will have profound ramifications for our immediate security, economic well-being, and position in the world…  We are concerned that America’s role as the world’s leading innovator is threatened… We know strategic competitors are investing in research and application.  It is only reasonable to conclude that AI-enabled capabilities could be used to threaten our critical infrastructure, amplify disinformation campaigns, and wage war.”

Like the Internet, - let’s remember that ARPANET was started in the late 1960s by the US Department of Defense, - AI is usable for military and civilian purposes.  But, - also like the Internet, - AI is a general purpose technology that can be used for a wide variety of applications, many of them beneficial, but others potentially threatening.

Scenario Planning - Formulating Strategy in the Face of High Uncertainty

“How can we formulate strategy in the face of uncertainty?,” asks Learning from the Future, a recent Harvard Business Review article by Peter Scoblic, in its opening sentence.  Answering this question has never felt more urgent as leaders prepare for the future.  “Even before the Covid-19 crisis, rapid technological change, growing economic interdependence, and mounting political instability had conspired to make the future increasingly murky.”  Uncertainty was already all-encompassing.

“And then the pandemic hit.”

When the present resembles the past, we can calculate the probability of future outcomes by analyzing past historical data.  That’s how insurance companies accurately predict the life expectancy of different people based on age, gender, general health, behavioral traits like smoking and drinking, etc.  But the situation is very different when the present doesn’t resemble the past.  “Uncertainty stems from our inability to compare the present to anything we’ve previously experienced.  When situations lack analogies to the past, we have trouble envisioning how they will play out in the future.”

Military strategists first developed scenario planning in the 1950s to help them envision the impact of a nuclear war between the US and the Soviet Union, - something that was clearly way beyond anyone’s experience.  The object of scenario planning is to assemble all known facts, trends, and other information and use them to create a number of alternative stories rich in detail, typically three or four, about plausible future outcomes along with the development paths and key events that led to such outcomes.  Altogether, the scenarios should span the scope of possible futures, although the actual future will likely include events from each scenario.

Remote Work is Surprisingly Productive, But For Many… Something Is Missing

What If Working From Home Goes on … Forever?, asks science and technology journalist Clive Thompson in the title of his June 9 NY Times Magazine article.  “The coronavirus crisis is forcing white-collar America to reconsider nearly every aspect of office life.  Some practices now seem to be wastes of time, happily discarded; others seem to be unexpectedly crucial, and impossible to replicate online.  For workers wondering right now if they’re ever going back to the office, the most honest answer is this: Even if they do, the office might never be the same.”

A recent survey found that of the 56% of respondents employed pre-Covid-19, half were working from home, - 35% having recently switched to working from home, while another 15% were already doing so pre-Covid; 37% continued to commute to work, and 10% had been recently laid-off or furloughed.  The survey was  based on two separate national samples of US data, - one which gathered 25,000 responses in early April, and the second another 25,000 responses in early May.

Thompson’s article cites the experience of Accenture, which has around 500,000 employees in more than 200 cities in 120 countries.  Before the pandemic, no more than 10% worked remotely on any given day.  But, by the middle of March, nearly all were asked to work from home.  Employees adapted quickly, said Accenture’s CTO.  The volume of video calls went up by a factor of six while those of audio calls tripled.  Despite having to switch from face-to-face to audio and video interactions, overall productivity actually went up as measured by several metrics.

It’s difficult to judge whether the surge in remote work will last.  “Home life in a lockdown is much harder than usual,” notes Thompson.  “Many workers who live alone are experiencing enforced isolation as an emotional grind… Nearly every parent I spoke to had their fingers crossed that schools and day care would reopen in the fall - at which point remote work might become an option they could choose, as opposed to one they were forced to endure.  Assuming that such a day does arrive, it’s possible that quite a few may elect to continue working outside the office.”

How Will Covid-19 Transform Urban Life?

In Why America’s Richest Cities Keep Getting Richer, a 2017 article in The Atlantic, urban studies professor and author Richard Florida wrote: “The most important and innovative industries and the most talented, most ambitious, and wealthiest people are converging as never before in a relative handful of leading superstar cities that are knowledge and tech hubs.  This small group of elite places forge ever forward, while most others struggle, stagnate, or fall behind…  They are not just the places where the most ambitious and most talented people want to be - they are where such people feel they need to be.”

Knowledge-intensive industries have long been centered in cities and surrounding metropolitan areas, where they’ve had the most access to a college educated, high skill workforce.  But, - from Milan to New York, - high density, globally connected urban areas have been ground zero for the spread of Covid-19.  Are cities now at risk of losing the superstar status they’ve enjoyed over the past several decades?

This is not the first time we’ve asked this question in the recent past.  In the mid-late 1990s, some predicted that the Internet would lead to the decline of cities, because it would enable people to work and shop from home, be in touch with their friends over e-mail, and get access to news and entertainment online.   But, instead of declining, megacities have continued to generate the greatest levels of innovation and good jobs, and thus attract a disproportionate share of the world’s talent.

Post-Pandemic, Is the World Likely to Become Significantly Less Flat?

“The golden age of globalisation, in 1990-2010, was something to behold,” wrote The Economist in a January, 2019 article.  “Commerce soared as the cost of shifting goods in ships and planes fell, phone calls got cheaper, tariffs were cut and the financial system liberalised.”

Thomas Friedman’s The World is Flat became an international best-seller in 2005 by nicely explaining what this new golden age of globalization was all about, including the key forces that contributed to flattening the world, - from the explosive growth of the Internet, open source software and related technologies; to the rise of outsourcing, offshoring and global supply chains.

In 2011 I attended a conference where Friedman was one of the speakers.  He said that we’ve transitioned from a connected to an increasingly hyperconnected global economy since he wrote The World is Flat in 2004.  Many of the companies and technologies that were part of every day conversations in 2011, - Facebook, Twitter, LinkedIn, smartphones, cloud computing, big data, broadband wireless Internet, - weren’t mentioned in his book because they had not yet been born or were still in their infancy.

The very nature of the global firm was transformed during these same decades.  In The Globally Integrated Enterprise, a 2006 Foreign Affairs article, then IBM CEO Sam Palmisano argued that the modern industrial corporation was now in its third stage of evolution in the way it conducted business around the world.

The Post-Pandemic Enterprise: What Will It Be Like?

In the near term, nations have been mostly focused on surviving the massive disruptions caused by Covid-19.  But, what about the longer term?  What will the post-pandemic new normal be like for societies and economies?  More specifically, how will the pandemic impact the world of business?  How can enterprises leverage the crisis to accelerate their journey toward what most everyone agrees will be an even faster changing future?  As Rahm Emanuel famously said in a 2008 WSJ interview: “You never want a serious crisis to go to waste.”

“The future is not what we thought it would be only a few short months ago,” said a recent McKinsey article, From thinking about the next normal to making it work.  “As businesses step into the post-coronavirus future, they need to find a balance between what worked before and what needs to happen to succeed in the next normal.”  The article offers 21 concrete recommendations for succeeding in the next normal, organized into seven major areas.  Let me summarize a few of these recommendations.