Irving Wladawsky-Berger

On the Governance of Blockchain: Lessons from the Internet

A few weeks ago, the World Economic Forum (WEF) released Realizing the Potential of Blockchain, a report by Don Tapscott and Alex Tapscott, authors of Blockchain Revolution which was published in May, 2016, and founders of the recently launched Blockchain Research Institute.  “The last few decades brought us the internet of information.  We are now witnessing the rise of the internet of value,” wrote the authors in the report’s Executive Summary.  “Like the first generation of the internet, this second generation promises to disrupt business models and transform industries… pulling us into a new era of openness, decentralization and global inclusion.”

“However, this extraordinary technology may be stalled, sidetracked, captured or otherwise suboptimized depending on how all the stakeholders behave in stewarding this set of resources - i.e. how it is governed,” they add in a strong note of caution.  “How we govern the internet of information as a global resource serves as a model for how to govern this new resource: through a multi-stakeholder approach using what we call global governance networks.”

I totally agree.

The Internet and World Wide Web brought a badly needed culture of collaboration and standards to the IT industry.  In the 1980s, it was quite difficult to get different IT systems to talk to each other.  Just sending an e-mail across two different applications from two different vendors was quite a chore, as was sharing information across disparate systems.  Then in the 1990s, the open Internet protocol, - TCP/IP, - was widely embraced by the general IT marketplace, making it possible to interconnect systems and applications from any vendors.  Internet e-mail protocols, - SMTP, MIME, POP, IMAP, - enabled people to easily communicate with anyone on any system.  At the same time,  the Web’s open standards, - HTML, HTTP, URLs enabled any PC connected to the Internet to access information on any web server anywhere in the world.

A similar story played out with Unix.  In the 1980s, Unix became a popular operating system for technical workstations, supercomputers and other kinds of systems.  Every vendor had developed its own version of Unix, - IBM’s AIX, Sun’s Solaris, HP’s HP-UX, and several others, - and they were all somewhat different and incompatible, making it difficult to port applications across these different flavors of Unix.  Attempts to unify UNIX were not successful.  Finally, in the 1990s Linux emerged as a Unix-like operating system that over time was embraced by just about all vendors.

The Growing Value of a Dual-Track Education

A few weeks ago I read a very interesting article in The Chronicle of Higher Education, - Why Colleges Need to Embrace the Apprenticeship.  The article raised a number of important questions on the future of college education, in particular, the value of an education that combines formal schooling with real-world practical experience, often referred to as a dual-track educational system.

Lots has been written about the critical importance of a good education in our knowledge-based digital economy.  At the same time, lots of questions are been raised about college and careers.  Is a four-year college education necessary to attain a good job and to have a successful long-term career?  Is it sufficient?  Are colleges properly preparing students for the job market?  Is there a role for liberal arts colleges?  Is college still worth it, given their increasing costs and the student loan debt crisis?  Should we continue to encourage young people to get a college degree? 

The Chronicle article addresses a number of these questions.  It writes that “Apprenticeships - long embraced as a work-force-training method in other countries - may now have an opening to become a far more common pathway to education and employment in the United States.  The enthusiasm for apprenticeships represents a kind of refutation of college education - a recognition that something about the path from college to career is not working for many people.”  The article explains why vocational apprenticeships have not fared as well in the US as they have in other advanced economies, and why apprenticeships, and similar dual-track systems, are increasingly important for all careers, including white-collar and professional careers requiring a bachelor’s or higher professional degree.

Serious AI Challenges that Require Our Attention

Several weeks ago Vanity Fair published and article by NY Times columnist Maureen Dowd, - Elon Musk’s Billion-Dollar Crusade to Stop the AI Apocalypse.  “Elon Musk is famous for his futuristic gambles, but Silicon Valley’s latest rush to embrace artificial intelligence scares him,” noted Dowd.  “And he thinks you should be frightened too.”

Entrepreneur and inventor Elon Musk is one of a number of world-renowned technologists and scientists who have expressed serious concerns that AI might be an existential threat to humanity, a group that includes Stephen Hawking, Ray Kurzweil and Bill Gates.  But, the vast majority of AI experts do not share their fears.  A few months ago, Stanford University’s One Hundred Year Study of AI project published a report by a panel of experts assessing the current state of AI.  Their overriding finding was that:

“Contrary to the more fantastic predictions for AI in the popular press, the Study Panel found no cause for concern that AI is an imminent threat to humankind.  No machines with self-sustaining long-term goals and intent have been developed, nor are they likely to be developed in the near future.  Instead, increasingly useful applications of AI, with potentially profound positive impacts on our society and economy are likely to emerge between now and 2030, the period this report considers.  At the same time, many of these developments will spur disruptions in how human labor is augmented or replaced by AI, creating new challenges for the economy and society more broadly.”

Just because experts conclude that, - at least for the foreseeable future, - AI does not pose an imminent threat to humanity, doesn’t mean that such a powerful technology isn’t accompanied by serious challenges that require our attention.

Become a More Productive, Empathetic, Creative Person With the Help of AI-Based Tools

Despite dramatic advances in technology, most of the world’s economies have been stuck in a long period of slow growth and slow productivity.  This is one of the most serious challenges in our 21st century economy.  Opinions abound, but there’s little consensus on its causes, and, nobody seems to know what to do about it, or how long it will likely last, - years or decades. 

In a recent article in the MIT Sloan Management Review, MIT Research Fellow Michael Schrage proposed a provocative and counterintuitive approach for enhancing innovation and productivity through man-machine collaborations.  Schrage’s approach has been more influenced by behavioral economics than by technology or algorithmic advances.  Instead of just asking how can people create more valuable innovation?, why not also ask How can innovation create more valuable people?  Don’t just leverage advanced technologies, - e.g., bots, software agents, and digital assistants, - to automate away a large portion of the workforce, but also focus on enhancing innovation and productivity by leveraging technology to create higher-performance versions of employees.

“Designing and training smarter algorithms may be cheaper and easier than retraining smart people,” wrote Schrage.  “Advocates of autonomous systems and machine learning typically innovate to minimize or marginalize human involvement in business processes.  For them, people are part of the problem, not the solution.  Organizations that take productivity seriously, however, understand that false dichotomies make poor investments: Smarter machines can - and should - be keys to unlocking greater returns from human capital.”

Mobile Payments - a Long, Relentless War of Attrition

Apple Pay was launched in September of 2014.  It was positioned as a relatively easy, secure way to pay for purchases in physical stores as well as online using a variety of supported Apple devices including iPhones, iPads, Macs and Apple Watch. The general reaction to Apple’s announcement was quite positive:  “[F]or now, at least, analysts believe if there is any company to persuade consumers of the mobile wallet’s value, it is Apple.” 

The payments community welcomed Apple with open arms, hoping that Apple could play a major role in bringing together the different players in the fragmented payments ecosystem, much as it had previously done with iTunes for music and the App Store for smartphone apps.  Apple Pay embraced a number of industry standards, including NFC (near-field communications) for contact-less payments; secure element, a dedicated device chip; and network-based tokenization to protect sensitive financial data.  In addition, Apple collaborated with the credit card networks, several banks and a number of merchants in the development and deployment of Apple Pay, as well as publishing the APIs so developers could embed Apple Pay services in their own apps.  

“Say hello to Apple Pay. It’s the new kid on the payments block and, depending on how things unfold, it could be the new Gorilla in the mobile payments ecosystem,” wrote Karen Webster, CEO of Market Platform Dynamics and an expert in digital payments.  But, she also added a prescient note of caution: “As great as this sounds, there are two limitations of Apple Pay right now for consumers and merchants.  And it’s that old chicken and egg issue that gets in the way of every new payments system.”  The chicken and egg issue is that there aren’t enough consumer devices supporting Apple Pay, and there aren’t enough merchants that accept it.  Both, consumers and merchants, have to be convinced to move away from payment systems they know well and feel comfortable with.

Global Trends and Business Strategy

McKinsey recently published an article on the long-term trends that are reshaping the business environment.  The article reminds us that the trend is your friend is an old adage that applies to business strategy as well as to investing.  The ability to anticipate where your industry is moving and to begin to reposition your company ahead of competitors is one of the most important elements of business strategy.  Companies that correctly identify and ride the tailwinds of technology and market trends will generally perform significantly better than companies for whom these same trends become tough headwinds.

But, the full version of the phrase is “The trend is your friend, until the end when it bends.”  Identifying long term trends is easier said than done.   Major trends involve competing complex forces interacting with each other, making it even more difficult to ascertain where things are heading.  And, they will eventually change direction.  It can be just as painful to miss an important trend as to stay with the trend once it starts to bend.

The article discusses nine major global forces organized into three distinct mega-trends: global growth shifts, accelerating industry disruption, and a new societal deal.  Let’s take a closer look at each of them.

The Emerging Data Economy

The Economist’s May 6 issue referred to data in its cover as the world’s most valuable resource.  Its lead article, - Data is giving rise to a new economy, - called it the fuel of the future.  “Data are to this century what oil was to the last one: a driver of growth and change.”  Both oil refineries and data centers fulfill similar roles: “producing crucial feedstocks for the world economy.”  Much of modern life would not exist without the cars, plastics and drugs made possible by oil refineries.  Similarly, data centers “power all kinds of online services and, increasingly, the real world as devices become more and more connected.”

Data has been closely intertwined with our digital technology revolution since the early days of the IT industry.  Data processing was the term then used to describe the applications of IT to automate highly structured business processes, e.g., financial transactions, inventory management, airline reservations.  Over time, increasingly sophisticated applications were developed to better manage key business operations along with their associated data, including enterprise resource planning, customer relationship management and human resources.  Beyond their use in operations, the information generated by these various applications was collected in data warehouses, and a variety of business intelligence tools were used to analyze the data and generate management reports.

These commercial applications dealt mostly with structured information in those early years of computing.  But at the same time, the scientific community was developing tools for managing, analyzing and visualizing the high volumes of much more unstructured data generated by their  experiments and observations.  Physicists, astronomers, biologists, and other scientists and engineers were developing methodologies and architectures for dealing with very large volumes of unstructured data, as well as analytical techniques, like data mining, for discovering patterns and extracting insights from all that data.

Then came the explosive growth of the Internet in the mid-1990s.  Ever since, digital technologies have been permeating just about every nook and cranny of the economy, society and our personal lives.  Data is now being generated by just about everything and everybody around us, including the growing volume of online and offline transactions, web searches, social media interactions, billions of smart mobile devices and 10s of billions of smart IoT sensors.

Peering into a Confusing, Paradoxical Future

Every four years since 1997, the US National Intelligence Council has been publishing a Global Trends report on the key trends that will shape the world over the following twenty years.  This unclassified strategic report is intended to provide the incoming administration and other senior leaders with a framework for long-range policy assessment.

Global Trends 2030: Alternative Worlds, released four years ago, identified four overarching megatrends that are expected to shape and transform the world by 2030: the empowerment of individuals - which will accelerate the reduction of poverty and raise the standard of living around the world; the diffusion of power among states, - which will shift power to networks and coalitions in a multipolar world; changing demographic patterns especially rapid aging, urbanization, and increased migration; and growing demands on resources such as food, water and energy, - which might lead to scarcities.

The latest Global Trends report, Paradox of Progress, was released earlier this year.  It begins by explaining its title. “We are living a paradox: The achievements of the industrial and information ages are shaping a world to come that is both more dangerous and richer with opportunity than ever before… The progress of the past decades is historic - connecting people, empowering individuals, groups, and states, and lifting a billion people out of poverty in the process.  But this same progress also spawned shocks like the Arab Spring, the 2008 Global Financial Crisis, and the global rise of populist, anti-establishment politics.  These shocks reveal how fragile the achievements have been, underscoring deep shifts in the global landscape that portend a dark and difficult near future.”

Globalization at a Crossroads

Earlier this year I wrote about the future of global firms, based on two recent articles on the subject, - The retreat of the global company in The Economist, and The Global Enterprise: Where to Now? in Foreign Affairs by IBM’s former CEO Sam Palmisano.  As both articles noted, global firms boomed over the past few decades, driven by IT advances that made it much easier to do business around the world and by the fierce global competition that forced companies to become more efficient and lower costs.

But now, “The biggest business idea of the past three decades is in deep trouble,” said The Economist.  Palmisano pointed out that the world stands at a major crossroads.  “A rising chorus of nationalism echoes across developed countries; it calls for tighter borders and restrictions on immigration.  Global trade negotiations have essentially ceased, and regional trade deals face strong headwinds of opposition.”

How should business address the very important issues now surrounding globalization?  This question was explored in two recent Harvard Business Review articles, - People Are Angry About Globalization. Here’s What to Do About It, by NYU and IESE professor Pankaj Ghemawat, and An Agenda for the Future of Global Business by BCG strategists Martin Reeves and Johann Harnoss.

Not Your Grandfather’s Manufacturing

The February 23 issue of the NY Times Magazine was devoted to the future of work, and in particular, to what it called the new working class.  The Oxford Dictionary defines working class as “The social group consisting of people who are employed for wages, especially in manual or industrial work.”  The working class includes many traditional blue-collar occupations, - factory workers, truck drivers, electricians, plumbers, - but it also now includes an increasing number of white-collar and service jobs.

While the new working class comprises a variety of jobs, most discussions on the topic are generally centered on the deindustrialization of America over the past few decades, as well as on the ensuing decline in both the number and the wages of manufacturing jobs.  “Now when politicians invoke the working class, they are likely to gesture, anachronistically, to an abandoned factory,” notes the issue’s introductory article.

The ongoing transformation of manufacturing jobs was the subject of Learning to Love Our Robot Co-Workers by Kim Tingley.  Her article nicely explained the major changes taking place in US manufacturing, especially the appearance of a new generation of flexible, programmable, moderately priced robots that are designed to safely collaborate with humans, - each doing what they do best.

Robotics is an exciting, fast moving discipline, which is playing an increasingly important role in the future of manufacturing.  All computers are defined by what their brains, - that is, their hardware and software, - are capable of computing and controlling.  Robots are computers that have both a brain and a body.  A robot’s capabilities are defined by what its brains and body can jointly do.

The Simple, Economic Value of Artificial Intelligence

I recently attended a very interesting talk , - Exploring the Impact of Artificial Intelligence: Prediction versus Judgment, - by University of Toronto professor Avi Goldfarb.  The talk was based on recent research conducted with his UoT colleagues Ajay Agrawal  and Joshua Gans.  In addition to an in-depth paper aimed at a research audience, they’ve explained their work in two more general interest articles, one in the Harvard Business Review and the second in the MIT Sloan Management Review.

In their opinion, “the best way to assess the impact of radical technological change is to ask a fundamental question: How does the technology reduce costs?  Only then can we really figure out how things might change.”  For example, the semiconductor revolution can be viewed as being all about the dramatic reductions in the cost of arithmetic calculations.  Before the advent of computers, arithmetic was done by humans with the aid of various kinds of devices, from the abacus to mechanical and electronic calculators.

Then came digital computers, which are essentially powerful calculators whose cost of arithmetic operations has precipitously decreased over the past several decades thanks to Moore’s Law.  Over the years, we’ve learned to define all kinds of tasks in terms of such digital operations, e.g., inventory management, financial transactions, word processing, photography.  Similarly, the economic value of the Internet revolution can be described as reducing the cost of communications and of search, thus enabling us to easily find and access all kinds of information, - including documents, pictures, music and videos.

How does this framing now apply to our emerging AI revolution?  After decades of promise and hype, AI seems to have finally arrived, - driven by the explosive growth of big data,  inexpensive computing power and storage, and advanced algorithms like machine learning that enable us to analyze and extract insights from all that data.  Agrawal, Fans and Goldfarb provide an elegant answer to this question in their HBR article.  “Machine intelligence is, in its essence, a prediction technology, so the economic shift will center around a drop in the cost of prediction.”

What’s the Value of Blockchain?

A few weeks ago I attended the IBM Blockchain Summit 2017 in New York.  The Summit included a number of talks and panels, and - most important, - presentations of concrete blockchain use cases IBM has been working on in a number of areas, including finance, supply chains and healthcare.  Such real-world use cases are particularly important when introducing a new, complex set of technologies in the marketplace.  They’re the best way of getting on the learning curve for the new technologies as well as of explaining the kinds of problems they help us address.

Blockchain has the potential to transform our economic and social systems, but such a transformation is still many years away.  Like the Internet, blockchain is a foundational technology, whose adoption process is gradual, incremental and steady, unlike the hockey stick adoption we typically associate with disruptive technologies as defined by Clayton Christensen 20 years ago.  Foundational transformations must overcome many barriers, - technological, organizational, governance, political, - which is why they take a long time to play out.

Lest we forget,  TCP/IP, - the communications protocol that defines the Internet to this day, - was first adopted in the mid-1980s.  So were the protocols used in e-mail, - the first widely used Internet application which enabled its user base in government, universities and research institutions to easily communicate with each other.  It wasn’t until the late 1980s that the Internet was first opened up to public, commercial users.  General Internet adoption took off a few years later with the advent of the World Wide Web and the Web browser, and its transformational power wasn’t fully evident until the late 2000s, with the explosive growth of smartphones and the mobile Internet.

The concrete uses cases presented by IBM as it defines its blockchain strategy brought to mind the approach we took in the early days of formulating IBM’s Internet strategy, which I was closely involved with.

Technology, Capitalism and “The American Way of Life”

Much has been written about our digital technology revolution and its impact on economies, societies and individuals.  But few have brought the kind of historical perspective to the subject that helps us better understand our turbulent times like scholar and consultant Carlota Perez in her 2002 book Technological Revolutions and Financial Capital:  The Dynamics of Bubbles and Golden Ages and related publications.

According to Perez, over the past few centuries, we’ve had a technology revolution every 40 to 60 years, starting with the Industrial Revolution in 1771, which was characterized by the emergence of machines, factories and canals.  This was followed by the age of steam, coal, iron and railways starting in 1829; steel, electricity and heavy engineering in 1875; and oil, autos and mass production in 1908.  Our present age of information and communication technologies (ICT), whose starting point she pegs at 1971, is the fifth such major revolution.

Technology revolutions have two distinct periods, each lasting 20 to 30 years.  The installation period is the time of creative destruction, when new technologies emerge from the lab into the marketplace, entrepreneurs start many new businesses based on these new technologies, VCs encourage experimentation with new business models, and the new ventures attract considerable investments and financial speculation.  Inevitably, this all leads to bubbles and crashes like the recent dot-com and subprime mortgage bubbles.

After the crash, comes the deployment period, a time of institutional recomposition.  The now well accepted technologies become the norm.  New paradigms emerge for guiding innovation and for determining winners and losers in the marketplace.  Over time, these new paradigms significantly transform the economy and everything around it, as well as re-shaping social behavior and the institutions of society.

Last year Perez published Capitalism, Technology and a Green Global Golden Age: The Role of History in Helping to Shape the Future.  In this recent article, she argued that we’re going through a crucial moment in history similar to the 1930s, which requires the kind of creative thinking and bold measures for which we justifiably celebrate statesmen like Franklin Delano Roosevelt and John Maynard Keynes.  Let me summarize her argument.

The State of American Jobs

Last year, the Pew Research Center, - in association with the Markle Foundation, - conducted a survey about the state of American jobs to shed light on how people think about work and about the skills and training needed to get ahead in our fast changing digital economy.  The survey was based on landline and mobile telephone interviews with a national sample of over 5000 adults.  Their analysis and conclusions were published last October in a highly detailed 94 page report, - The State of American Jobs.

“Tectonic changes are reshaping U.S. workplaces as the economy moves deeper into the knowledge-focused age,” said the report in its opening paragraph.  “These changes are affecting the very nature of jobs by rewarding social, communications and analytical skills.  They are prodding many workers to think about lifetime commitments to retraining and upgrading their skills.  And they may be prompting a society-wide reckoning about where those constantly evolving skills should be learned - and what the role of colleges should be.”

Let me summarize some of the report’s key findings.

Automation and Employment in the 21st Century

Ever since the advent of industrialization over 200 years ago, there’ve been periodic fears about the impact of technology-based automation on jobs.  In the 1810s, for example, the so-called Luddites smashed the new machines that were threatening their textile jobs.  But each time those fears arose in the past, technology advances ended up creating more jobs than they destroyed.

Automation anxieties have understandably accelerated in recent years, as AI-related innovations, including robots and smart machines of all kinds, are now being applied to activities requiring intelligence and cognitive capabilities that not long ago were viewed as the exclusive domain of humans.  The concerns surrounding AI’s long term impact on jobs may well be in a class by themselves.

There’s a broad consensus that AI will have a major impact on jobs and the very nature of work, but it’s much less clear what that impact will be.  Will AI play out like past technology innovations, - highly disruptive in the near term, but ultimately leading to the creation of new jobs, whole new industries, and a rising standard of living?  Or will this time be different, as AI-based innovations end up replacing a large portion of the workforce, - leading to mass unemployment, economic dislocations and social unrest?

The Fourth Industrial Revolution - Risks and Benefits

The Fourth Industrial Revolution (4IR) was the central theme of the 2016 World Economic Forum (WEF) that took place a year ago in Davos, Switzerland.  It continued to play a prominent role in the recently concluded 2017 annual meeting.   Coming to grips with the impact of the fourth industrial revolution was among the top leadership priorities discussed at this year’s meeting.

Over the past year, Klaus Schwab, - WEF founder and executive chairman, - has described his vision for the fourth industrial revolution in a number of articles as well as a book on the subject.  Dr. Schwab positions the 4IR within the historical context of three previous industrial revolutions.  The First, - starting in the last third of the 18th century, - introduced new tools and manufacturing processes based on steam and water power.  The Second, - a century later, - saw the advent of steel, oil, electricity, mass production and associated inventions including the telephone, light bulbs phonographs and cars.  The Third, - starting in the middle of the last century, - has brought us digital technologies, computers, the IT industry, and the automation of processes in just about all industries.

The 4IR builds on our ongoing digital revolution.  It “entails nothing less than a transformation of humankind,” wrote Dr. Schwab in his book’s introduction  “We are at the beginning of a revolution that is fundamentally changing the way we live, work, and relate to one another.  In its scale, scope and complexity, what I consider to be the fourth industrial revolution is unlike anything humankind has experienced before…”

“Consider the unlimited possibilities of having billions of people connected by mobile devices, giving rise to unprecedented processing power, storage capabilities and knowledge access.  Or think about the staggering confluence of emerging technology breakthroughs, covering wide-ranging fields such as artificial intelligence (AI), robotics, the internet of things (IoT), autonomous vehicles, 3D printing, nanotechnology, biotechnology, materials science, energy storage and quantum computing, to name a few.  Many of these innovations are in their infancy, but they are already reaching an inflection point in their development as they build on and amplify each other in a fusion of technologies across the physical, digital and biological worlds.”

The Future of the Globally Integrated Enterprise

“In Retreat: Global companies in the era of protectionism,” reads the cover of the January 28 issue of The Economist.  In The retreat of the  global company, The Economist defines global firms as those where over 30% of their sales come from outside their home region.  For the past three decades, global firms have been the “apex predators of the global economy,” directing the global flow of goods, services and capital, shaping ecosystems, orchestrating supply chains and owning most of the world’s intellectual capital.  But now, “The biggest business idea of the past three decades is in deep trouble.”

Global firms boomed as China was opening up, Europe was integrating, the Soviet bloc was collapsing, and barriers to global trade and investment were coming down.  IT advances made it much easier to do business around the world.  Global competition forced companies to become more agile and efficient by unbundling functions and re-engineering processes. 

The world was waking up to the growing economic power of emerging markets.  “Governments in the rich world dreamed of their national champions becoming world-beaters.  Governments in the emerging world welcomed the jobs, exports and technology that global firms brought.  It was a golden age.”

The Economist referenced The Globally Integrated Enterprise, a 2006 Foreign Affairs article by IBM’s then CEO Sam Palmisano.  Palmisano’s article started out by looking at the evolution in the way companies have conducted business around the world.

The Emerging, Unpredictable Age of AI

In a 1930 essay, Economic Possibilities for our Grandchildren, English economist John Maynard Keynes wrote about the onset of “a new disease” which he called technological unemployment, that is “unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.”

“But this is only a temporary phase of maladjustment,” he added.  “I would predict that the standard of life in progressive countries one hundred years hence will be between four and eight times as high as it is.”  Keynes believed that technological progress would lead us to a brighter future.  By 2030, people would likely work no more than 15 hours a week, and their biggest problem would be how to use their leisure and freedom from economic cares.

I was reminded of Keynes’ predictions while reading a number of recent articles on our emerging age of AI.  After decades of unfulfilled promises and hype, AI seems to be reaching a tipping point.  The necessary ingredients are finally coming together: lots and lots of data, with the volume of data pouring in expected to double every three years or so; advanced machine learning algorithms that extract insights and learn from all that data; drastically lowered technology costs for collecting, storing and analyzing these oceans of information; and access to an increasing variety of data-driven, cloud-based AI applications.

A small, but prominent group of technologists and scientists have warned that at some future time, a superintelligent AI might pose an existential threat to humanity.  But while dismissing such dire concerns, most experts worry that the real threat is that AI advances could lead to widespread economic dislocation and social unrest.  “Contrary to the more fantastic predictions for AI in the popular press, the Study Panel found no cause for concern that AI is an imminent threat to humankind…” was the conclusion of a recent study by AI experts.  “At the same time, many of these developments will spur disruptions in how human labor is augmented or replaced by AI, creating new challenges for the economy and society more broadly.”

AI and Public Policy

Two years ago, Stanford University launched the One Hundred Year Study of AI (AI100), “to study and anticipate how the effects of artificial intelligence will ripple through every aspect of how people work, live and play.”  One of its key missions is to convene a Study Panel of experts every five years to assess the then current state of the field, as well as to explore both the technical advances and societal challenges over the next 10 to 15 years. 

The first such Study Panel recently published Artificial Intelligence and Life in 2030, a report that examined the likely impact of AI on a typical North American city by the year 2030.  The report is organized into three main sections: Section I described the key research trends influencing AI’s future; Section II examined the key economic sectors that are most likely to be impacted by AI;  and Section III looked into issues surrounding AI and public policy.  Over the past several weeks I’ve discussed the first and second sections.  I now would like to turn my attention to Section III: Prospects and Recommendations for AI Public Policy.

“Throughout history, humans have both shaped and adapted to new technologies.  This report anticipates that advances in AI technologies will be developed and fielded gradually - not in sudden, unexpected jumps in the techniques themselves - and will build on what exists today, making this adaptation easier… The measure of success for AI applications is the value they create for human lives.  Going forward, the ease with which people use and adapt to AI applications will likewise largely determine their success.”

The report then adds some very important warnings.  “Conversely, since AI applications are susceptible to errors and failures, a mark of their success will be how users perceive and tolerate their shortcomings.  As AI becomes increasingly embedded in daily lives and used for more critical tasks, system mistakes may lead to backlash from users and negatively affect their trust.”

The Internet, Blockchain, and the Evolution of Foundational Innovations

Last year, a panel of global experts convened by the World Economic Forum selected blockchain as one of the Top Ten Emerging Technologies for 2016, based on its potential to fundamentally change the way economies work.  But, how transformative will blockchain turn out to be?  How long is the transformation likely to take?  And how will it compare with the Internet-based transformation of the past few decades?

These questions were nicely addressed in The Truth about Blockchain, a recent Harvard Business Review article by Harvard professors Marco Iansiti and Karim Lakhani.  Their article starts off with one of the best descriptions I’ve seen of the long-term promise of blockchain.

“Contracts, transactions, and the records of them are among the defining structures in our economic, legal, and political systems.  They protect assets and set organizational boundaries.  They establish and verify identities and chronicle events.  They govern interactions among nations, organizations, communities, and individuals.  They guide managerial and social action.  And yet these critical tools and the bureaucracies formed to manage them have not kept up with the economy’s digital transformation.  They’re like a rush-hour gridlock trapping a Formula 1 race car.  In a digital world, the way we regulate and maintain administrative control has to change…”

“With blockchain, we can imagine a world in which contracts are embedded in digital code and stored in transparent, shared databases, where they are protected from deletion, tampering, and revision.  In this world every agreement, every process, every task, and every payment would have a digital record and signature that could be identified, validated, stored, and shared.  Intermediaries like lawyers, brokers, and bankers might no longer be necessary.  Individuals, organizations, machines, and algorithms would freely transact and interact with one another with little friction.”

AI, Automation and the US Economy

On December 20, the White House released Artificial Intelligence, Automation, and the Economy, a new report that investigates how AI will likely transform job markets over time, and recommends policy responses to address AI’s impact on the US economy.  This report is further evidence that AI is now reaching the kind of market impact that requires well thought out strategies by both business and government.

AI research has been around since the early days of IT, - having gone through ups and downs over the past several decades.  But it’s recent advances based on machine learning and related data-driven technologies are still relatively new, making it hard to predict where AI will be heading over time.

Harder still is predicting AI’s longer term economic and societal impact.  Think of anticipating the impact of the emerging Internet revolution back in the mid 1990s, before the advent of e-commerce and social media, let alone smartphones, IoT and cloud computing in the 2000s.  That’s roughly where we are with AI today.

But, there’s one big difference.  The Internet generated a fair degree of hype, especially in the dot-com era of the late 1990s, but the overriding feelings were ones of hope and excitement.  Not so with AI.  Along with admiration for its considerable accomplishments, - from assisting in the treatment of rare forms of cancer to self-driving cars, - there are serious fears that AI advances will lead to massive job losses, economic dislocations and social unrest.

Securing the Foundations of our Digital Economy

In February of 2016, the President issued an Executive Order establishing the Commission on Enhancing National Cybersecurity within the Department of Commerce.  The Commission was charged with “recommending bold, actionable steps that the government, private sector, and the nation as a whole can take to bolster cybersecurity in today’s digital world, and reporting back by the beginning of December.”

On December 1 the Commission issued its final Report on Securing and Growing the Digital Economy.  The Commission urged the incoming administration to strengthen cybersecurity efforts within its first 100 days.  The report includes 16 major recommendations and related actions that can hopefully serve as a useful framework for significantly enhancing the Nation’s cybersecurity.

The widespread success of the Internet in the 1990s has 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 significantly accelerated over the past decade with the advent of billions of smartphones, tens of billions of IoT devices and huge amounts of data, all now connected via Internet-based broadband networks.

At the same time, Internet threats have been growing.  Large-scale fraud, data breaches, and identity thefts are becoming more common.  Companies are finding that cyber-attacks are costly to prevent and recover from.  As we move from a world of physical interactions and paper documents, to a world primarily governed by digital data and transactions, our existing methods for protecting identities and data are proving inadequate.

The 2016 MIT Inclusive Innovation Awards

Several months ago, MIT’s Initiative on the Digital Economy launched its first annual Inclusive Innovation Competition (IIC).  MIT is one of the world’s top research universities, renowned as well for its entrepreneurial culture.  But the objectives of the IIC are quite different and unique.  Instead of competing on creating the most advanced technologies or compelling startups, the IIC is focused on innovations aimed at improving the economic opportunities of middle- and low-income earners around the world.

Applicants competed for $1 million in prizes to be awarded in four main categories: Skills, - how employees were re-skilled for new types of jobs; Matching, - how qualified people were connected to new types of jobs; Humans + Machines, - how technology is used to augment human labor; and New Models, - how new business models revolutionize labor markets and job opportunities.  In each of these categories, the grand prize winner was awarded $125,000, while each of the four runner-ups received $25,000.  In addition, four additional $25,000 Judges Choice Awards were given to organizations deemed by the judges to be uniquely inventive.

I’m a Fellow of the Initiative on the Digital Economy, and served as one of the judges in the competition.  243 applications were received from around the world, from which we selected 24 finalists.  I personally reviewed around 20 applications, and was really impressed not only by their innovative ideas, but also by their courage and determination as they addresed some of society’s toughest problems.

Becoming a Data-Driven Business: Challenges and Opportunities

A few weeks ago, McKinsey published The age of analytics: Competing in a data-driven world, a comprehensive report on the state of big data, and in particular, on the challenges and opportunities a company faces as it strives to become a data-driven business.

Big data,- including analytics, data science, artificial intelligence and related information-based technologies - are now everywhere.  “Is big data all hype?,” asks McKinsey in the report’s introduction.  “To the contrary: earlier research may have given only a partial view of the ultimate impact… the range of applications and opportunities has grown and will continue to expand.  Given rapid technological advances, the question for companies now is how to integrate new capabilities into their operations and strategies - and position themselves in a world where analytics can upend entire industries.”

It’s very hard to anticipate the consequences of disruptive innovations.  Even harder is predicting when the impact will be felt across the economy and society.  It’s often been said that truly transformative innovations are overhyped in the short term but under-hyped in the long term.  Think of electricity and automobiles, the Internet more recently and now big data.

The Transformative Power of Cloud Computing

I was recently involved in two different meetings, each convened by an IT research organization focused on providing strategic advice to CIOs.  My participation in each of the CIO  meetings was in the form of a fireside chat with a senior analyst of the organization.  Given that I’ve closely followed cloud computing over the years, the state of cloud was one of the main topics we discussed.

For a while now I’ve thought of cloud as a new model of computing in the IT world.  For the IT industry, a new computing model is a very big deal.  In the sixty years or so since there’s been an IT industry, this would be only the third such model, centralized and client-server computing being the two previous ones.  Mainframes and PCs were the defining technologies of the centralized model and client-server models respectively.

The Internet is the defining technology of the cloud computing model.  There are clearly other major technologies around us, - e.g., smartphones, IoT, analytics, AI, - but when you think about it, all of them rely on their connections to cloud-based data, applications, and services for much of their functionality.

Cloud computing has gone through three major stages over the past decade: IT-as-a-service in its initial years, then application innovation in it’s next stage, and it’s now just entering the business transformation stage.  Let me say a few words about the first two before turning to business transformation.

How Will AI Likely Impact How We Work, Live and Play?

A few weeks ago I discussed whether AI is finally reaching a tipping point, mostly based on a recently published report, - Artificial Intelligence and Life in 2030.  The report was developed by a study panel of AI experts convened by the One Hundred Year Study of AI (AI100), an initiative launched at Stanford University in December, 2014 “to study and anticipate how the effects of artificial intelligence will ripple through every aspect of how people work, live and play.”  To better understand the future impact of AI on everyday lives, the panel focused the study on the likely influence of AI on a typical North American city by the year 2030.

The report is organized into three main sections.  Section I, - What is Artificial Intelligence?, - describes how researchers and practitioners define AI, as well as the key research trends that will likely influence AI’s future.  Section II looks into AI’s overall impact on various sectors of the economy, while the third Section, examines AI issues related to public policy.

My previous discussion was primarily focused on Section I.  I’d now like to turn my attention to Section II, - AI by Domain.  To help analyze where AI might be heading, the study panel narrowed its explorations to the eight domains most likely to be impacted by AI:

The Evolution of the Firm

A few weeks ago I discussed The Rise of the Global Superstar Company based on a recent special report on the subject by The Economist.  The report noted that the decade-long trend toward increasingly concentrated global firms is somewhat surprising. 

“The rise of the giants is a reversal of recent history…  In the 1980s and 1990s management gurus pointed to the demise of size as big companies seemed to be giving way to a much more entrepreneurial economy.  Giants such as AT&T were broken up and state-owned firms were privatised.  High-tech companies emerged from nowhere.  Peter Drucker, a veteran management thinker, announced that ‘the Fortune 500 [list of the biggest American companies] is over.’ That chimed with the ideas of Ronald Coase, an academic who had argued in ‘The Nature of the Firm’ (1937) that companies make sense only when they can provide the services concerned more cheaply than the market can.”

Professor Coase’s views on the firm changed quite a bit over the years.  In 1937 he published The Nature of the Firm, a seminal article which along with other major contributions earned him the 1991 Nobel Prize in economics.  In the article, Professor Coase provided a simple answer to the question: Why do firms exist?  He explained that, in principle, a firm should be able to find the cheapest, most productive goods and services by contracting them out in an efficient, open marketplace.  However, markets are not perfectly fluid.  Transaction costs are incurred in obtaining goods and services outside the firm, such as searching for the right people, negotiating a contract, coordinating the work, managing intellectual property and so on.  Thus, firms came into being to make it easier and less costly to get work done.

Towards a Trusted Framework for Identity and Data Sharing

I recently participated in a Treasury Identity Forum organized by the US Treasury Department in Washington, DC.  The Forum focused “on the critical role of legal identity for financial inclusion, economic development, and anti-money laundering/counter financing of terrorism (AML/CFT) safeguards, and the development of new technology identification/authentication solutions to help achieve these goals.”  It brought together stakeholders from governments, financial service companies, FinTech startups and technologists to better understand how emerging technologies and legal frameworks can help us develop the required digital identity systems.

I was a member of a panel on how government, business and research communities can collaborate in developing workable identity solutions.  Let me summarize the points I made in my introductory remarks.

From time immemorial, our identity systems have been based on face-to-face interactions and on physical documents and processes.  But, the transition to a digital economy requires radically different identity systems.  As the economy and society move toward a world where interactions are primarily governed by digital data and transactions, our existing methods of managing identity and data security are proving inadequate.  Large-scale fraud, identity theft and data breaches are becoming common, and a large fraction of the world’s population lacks the credentials needed to be part of the digital economy.

The Rise of the Global Superstar Company

The September 17 issue of The Economist included a special report on the rise of so called superstar companies.  “Disruption may be the buzzword in boardrooms, but the most striking feature of business today is not the overturning of the established order,” notes The Economist.  “It is the entrenchment of a group of superstar companies at the heart of the global economy.”

This trend toward consolidation and growing size is evidenced by a few worldwide statistics: 10% of public companies generate 80% of all profits; firms with over $1 billion in annual revenues are responsible for 60% of total global revenues; and the rate of mergers and acquisitions is more than twice what it was in the 1990s.  The trend is particularly prominent in the US: in the 20 years from 1994 to 2013, the share of GDP generated by the 100 biggest companies rose from 33% to 46%; the five largest banks now account for 45% of all banking assets, up from 25% in 2000; and new firm formation has been going down since the late 1970s, leading to an overall decline in young- and medium-aged companies over the years.

The current rise of large companies is somewhat unexpected.  Following the Great Depression and WW2, the country welcomed the stability promised by corporate capitalism.  Big, multinational companies dominated most industries, - from GM, Ford and Chrysler in cars to Esso/Exxon, Mobil and Texaco in oil and gas.  It was an era characterized by bureaucratic corporate cultures, focused on organizational power and orderly prosperity.

This all started to change a few decades later with the advent of a more innovative, fast moving entrepreneurial economy.  The 1980s saw the rise of young, high-tech companies, - e.g., Microsoft, Apple, Oracle, Sun Microsystems; telecommunications was deregulated; ATT was broken up; and Silicon Valley became the global hub for innovation, emulated by regions around the world.

Is Design Thinking the “New Liberal Arts”?

Design thinking has become an increasingly popular topic of discussion over the past decade.  It was featured in the September, 2015 issue of the Harvard Business Review with several articles on the subject.  Design is no longer just for physical objects, e.g. cars, bridges, shoes, jewelry, smartphones.  Design thinking is now being applied to abstract entities, - e.g. systems, services, information and organizations, - as well as to devise strategies, manage change and solve complex problems.

The application of design thinking beyond products isn’t new.  Nobel laureate Herbert Simon discussed the concept in his 1969 classic The Sciences of the Artificial.  IDEO, a firm best known for pioneering this expanded view of design, traces its roots back to 1978.  The School of Design in London’s Royal College of Art has long been expanding the boundaries of industrial design.  Stanford’s Institute of Design, - better known as the d.school, - was launched in 2004 as a graduate program that integrates business, the social sciences, the humanities and other disciplines into more traditional engineering and product design.

The d.school’s website nicely explains its design-thinking point of view:  “Students and faculty in engineering, medicine, business, law, the humanities, sciences, and education find their way here to take on the world’s messy problems together.  Human values are at the heart of our collaborative approach… Along the way, our students develop a process for producing creative solutions to even the most complex challenges they tackle…  Our deliberate mash-up of industry, academia and the big world beyond campus is a key to our continuing evolution.”

Reflections on the Development of Implementable, Winning Strategies

I recently read an article by strategy consultant and writer Ken Favaro which nicely explained how to best think about strategy in today’s business environment.  “Many business leaders subscribe to the classic definition of strategy as a set of actions designed to achieve an overall aim,” wrote Favaro in The Trouble with Putting Goals Ahead of Strategy, published in strategy+business in 2015.  “In other words, they believe strategy starts with a goal.  But for companies that have implemented winning strategies, that’s not how it typically happens.”

Goals and strategies serve very different purposes.  Goals, visions and missions are important to paint an exciting picture of the future around which everyone can rally, as well as to help set the general direction of a company.  But being too high level, goals by themselves don’t give you much guidance on how to get things done and what key decisions must be made and prioritized.  “[G]oals tell you very little about the fundamental choices you should make around creating customer and company value.  Such choices are the very essence of your strategy.”

Most winning strategies start with an idea for an innovative new product, service or business model, followed by a plan to bring the idea to market.  Only then should come a big, bold goal, as a way “to crystalize an ambition, motivate the troops, and excite investors.  Unfortunately, strategic planning in most companies gets this sequence exactly reversed  - and when that happens, bad strategies result.”

I totally agree with Favaro, based on my personal experiences leading emerging technology initiatives at IBM, including parallel supercomputing, the Internet, and Linux.  Let me share some of what I learned when working on IBM’s Internet strategy.

Blockchains: the Promise of More Frictionless, Trusted Economies

Why do firms exist?  Ronald Coase, - the eminent British economist and University of Chicago professor, - addressed this question in The Nature of the Firm, - a seminal paper published in 1937 which along with other major achievements earned him the 1991 Nobel Prize in economics.

Professor Coase explained that, in principle, a firm should be able to find the cheapest, most productive, highest quality goods and services by contracting them out in an efficient, open marketplace.  However, markets are not perfectly fluid.  Transaction costs are a kind of friction incurred in obtaining goods and services outside the firm, such as searching for the right supply chain partners, establishing a trusted relationship, negotiating a contract, coordinating the work, managing intellectual property and so on.  Firms came into being to make it easier and less costly to get work done.

A recent IBM report, - Fast forward: Rethinking enterprises, ecosystems and economies with blockchains, - harks back to Coase’s paper to analyze the potential value of blockchains.  The report notes that while transaction costs are lower within firms, “in recent years as enterprises have scaled, the added complexity of operations has grown exponentially while revenue growth has remained linear.  The result?  At a certain point, organizations are faced with diminishing returns.  Blockchains have the potential to eradicate the cost of complexity and ultimately redefine the traditional boundaries of an organization.”

Competing Against “Digital Invaders”

Last year, IBM’s Institute for Business Value conducted a C-suite study aimed at identifying the key disruptive trends that will likely impact companies around the world over the next three to five years, as well as what their senior executives are doing to better prepare their organizations for the expected disruptions.  The study surveyed over 5,200 CEOs, CFOs, CIOs, CMOs and other C-suite executives across 21 industries in over 70 countries, - most of them in face-to-face interviews.  After analyzing the survey data,  - including the use of Watson Analytics to extract inferences from open-ended responses, - IBM published its findings in Redefining Boundaries: Insights from the Global C-suite Study.

To better understand the traits of the most successful enterprises, the IBM study also asked CxOs to rank their companies based on their innovation reputation and their financial performance over the previous three years.  After analyzing their responses, it identified 5% of companies as Torchbearers, the name given to those companies enjoying both a strong innovation reputation and an excellent financial track record.  At the other end of the spectrum, 34% of enterprises were identified as Market Followers or laggards in both innovation and financial performance.

The report organized its findings and recommendations into three main areas:  Preparing for digital invaders; Creating a panoramic perspective; and Be first, be best or be nowhere.  Let me briefly discuss each.

Why Are We Stuck in a World of Slow Economic Growth? Nobody Seems to Know for Sure

Over the past few centuries, the natural sciences, - e.g. physics, chemistry, biology, - have developed a variety of principles and models.  These have enabled them to analyze and predict the behavior of our highly complex physical systems under widely different conditions.  But the situation is quite different in the social sciences, - e.g., economics, sociology, political science.  It’s much more difficult to make accurate predictions in social systems, - whose key components are people, organizations and their intricate interactions, - because of their highly fluctuating behaviors.

I was reminded of this major distinction between physical and social systems by a recent issue of Foreign Affairs, which focused on How to Survive Slow  Growth.  “[G]rowth has ground to a halt almost everywhere, and economists, investors, and ordinary citizens are starting to confront a grim new reality: the world is stuck in the slow lane and nobody seems to know what to do about it,” notes its introductory article.  Several prominent authors wrote about various aspects of the economic slowdown.  But in the end, they didn’t arrive at consensus reasons for the slow growth or how long it will likely last, - years or decades.

In the lead article, - The Age of Secular Stagnation: What It Is and What to Do About It, - Harvard economics professor Larry Summers wrote:  “As surprising as the recent financial crisis and recession were, the behavior of the world’s industrialized economies and financial markets during the recovery has been even more so.”  Back in 2009, almost no one would have predicted that we would still be in a period of slow economic growth, that inflation would be around one percent and interest rates would hover around zero.  But, “nearly seven years into the U.S. recovery, markets are not expecting normal conditions to return anytime soon.”

Blockchain Can Reshape Financial Services… But it Will Take Significant Time and Investment

In early August, the World Economic Forum (WEF) published two excellent reports: A Blueprint for Digital Identity, - which I wrote about a few weeks ago, - and The future of financial infrastructure: An ambitious look at how blockchain can reshape financial services, - which I’d now like to discuss.

“Distributed ledger technology (DLT), more commonly called blockchain, has captured the imaginations, and wallets, of the financial services ecosystem,” notes the report, citing a few statistics as evidence: over 90 central banks are engaged in DLT discussions around the world; more than 24 countries have already launched blockchain-based initiatives; 80% of banks predict that they’ll launch blockchain projects by 2017; over 90 financial and technology companies have already joined blockchain consortia; over the past 3 years; more than 2,500 patents have been filed; and $1.4 billion has been invested in blockchain-based startups over the same time span.

In addition, a panel of global experts convened by the WEF selected blockchain as one of the Top Ten Emerging Technologies for 2016 because of its potential to fundamentally change the way markets and governments work, - further evidence that blockchain is reaching a tipping point of market acceptance.

But, significant hurdles must be overcome before the advent of large-scale blockchain infrastructures.  The WEF correctly warns that this will take time.  Not only are there major technology and standards issues to be worked out, but the industry will have to collaborate with governments around the world to develop the appropriate legal frameworks and regulatory environments.

Automation Technologies and the Future of Work

Last year, McKinsey launched a multi-year study to explore the potential impact of automation technologies on jobs, organizations and the future of work.  “Can we look forward to vast improvements in productivity, freedom from boring work, and improved quality of life?,” its initial article on the study asked, or “Should we fear threats to jobs, disruptions to organizations, and strains on the social fabric?”

Most jobs involve a number of different tasks or activities.  Some of these activities are more amenable to automation than others.  But just because some of the activities have been automated, does not imply that the whole job has disappeared.  To the contrary, automating parts of a job will often increase the productivity and quality of workers by complementing their skills with machines and computers, as well as by enabling them to focus on those aspect of the job that most need their attention.

Given that few jobs or occupations will be entirely automated in the near-mid future, the study focused instead on the kinds of activities within jobs that are more likely to be automated, as well as how those jobs and business processes will then be redefined.  It did so by analyzing the extensive data in O*NET, a web-based application sponsored by the US Department of Labor which includes the most comprehensive information on US occupations.

The study analyzed around 2,000 work activities across 800 different occupations, and grouped them into 18 different capabilities, - 3 of them social in nature; 10 cognitive; and 5 physical, - and then assessed the automation potential of each.  It found that 45% of work activities could be automated using existing, state-of-the-art technologies.

Digital Identity - the Key to Privacy and Security in the Digital World

From time immemorial, our identity systems have been based on face-to-face interactions and on physical documents and processes.  But, the transition to a digital economy requires radically different identity systems.  In a world that’s increasingly governed by digital transactions and data, our existing methods for managing security and privacy are no longer adequate.  Data breaches, identity theft and large-scale fraud are becoming more common.  In addition, a significant portion of the world’s population lacks the necessary digital credentials to fully participate in the digital economy.

Last month, the World Economic Forum (WEF) published an excellent report, A Blueprint for Digital Identity.  The report lays out a framework for the creation of digital identity systems, discusses the benefits that these systems would bring to its various stakeholders, and argues that financial institutions should lead their development.  It also includes a primer on identity, which clearly explains what identity is all about.

Identity plays a major role in everyday life.  Think about going to an office, getting on a plane, logging to a website or making an online purchase.  While all around us, we generally don’t pay much attention to our identity credentials unless something goes wrong.  But, it’s a highly complex and interesting subject, which the report helped me better understand.  Let me summarize some of what I learned.

“Why is identity important?,” the primer starts out by asking.  “In an increasingly borderless and digital world, privacy and security cannot be ensured through the construction of walls around sensitive information.  Identity is the new frontier of privacy and security, where the very nature of entities is what allows them to complete some transactions but be denied from completing others.  To understand the importance of identity and the criticality of strong identity protocols that protect against cyber-risk and suit the needs of transacting parties, it is essential to understand what identity is, and its role in enabling transactions.”

Blockchain - Once Again, the Technological Genie Has Been Unleashed from its Bottle

Skeptics needing further reassurance that the Blockchain is truly reaching a tipping point can rest easier with the recent publication of Don Tapscott’s Blockchain Revolution, co-written with his son Alex.  Don, whom I’ve long known, has a knack for identifying what The Next Big Thing will likely be, and shortly thereafter writing a book to explain it to everybody else.  The Digital Economy, written in the mid 1990s, anticipated the unbundling of vertically integrated companies into business webs, giving rise to the open networked enterprise.  His 2006 Wikinomics predicted the rise of mass collaboration in what became known a few years later as the On Demand Economy.  Blockchain Revolution, his 16th book, now explains “How The Blockchain Will Transform Everything From Banking To Government To Our Identities.”

The book is organized into three main sections.  The first explains the blockchain from two complementary points of view: as a major next step in the evolution of the Internet; and as the architecture underpinning bitcoin, the best known and most widely held digital currency.  The second and longest section describes how blockchain could potentially transform financial services, companies, government, the Internet of Things, and other key areas.  The last section summarizes the major challenges that must be overcome as well as the governance required to fulfill the promise of blockchain.

“It appears that once again, the technological genie has been unleashed from its bottle,” write the authors in their opening paragraph.  “Summoned by an unknown person or persons with unclear motives, at an uncertain time in history, the genie is now at our service for another kick of the can - to transform the economic power grid and the old order of human affairs for the better.  If we will it.”

Is There a STEM Crisis or a STEM Surplus?

Is the US facing a critical shortage of STEM skills?  Do we have enough STEM workers to meet the demands of the labor market?  Are enough young people choosing STEM careers so we can meet future demands?

Such serious concerns have been expressed in a number of national studies over the past two decades.  In 2005, for example, the National Innovation Initiative listed “Build the Base of Scientists and Engineers” as one of its top recommendations, noting that “unless the United States takes swift action, the demand for S&E talent will far outstrip supply.  The number of jobs requiring technical training is growing at five times the rate of other occupations.”

Two years later, a major National Academies study, Rising Above the Gathering Storm, called for increasing America’s STEM talent pool by providing 25,000 new 4-year competitive undergraduate scholarships to US citizens enrolled in the physical sciences, the life sciences, engineering and math; and by funding 5,000 new graduate fellowships each year for US citizens pursuing graduate studies in areas of national need.

And in 2012, a report by the President’s Council of Advisors on Science and Technology wrote: “Economic projections point to a need for approximately 1 million more STEM professionals than the U.S. will produce at the current rate over the next decade if the country is to retain its historical preeminence in science and technology.  To meet this goal, the United States will need to increase the number of students who receive undergraduate STEM degrees by about 34% annually over current rates.”

Is the Blockchain Now Reaching a Tipping Point?

A few weeks ago, the World Economic Forum (WEF) published its annual list of the Top Ten Emerging Technologies for 2016.  The technologies on the list have been worked on for years.  But their inclusion in the Top Ten List indicates that each has now reached a market acceptance tipping point where its impact can be meaningfully felt.  The Blockchain is one of the technologies in this  year’s list, selected by the WEF panel of global experts because of its emerging potential to fundamentally change the way markets and governments work. 

What does it mean for an infrastructure technology like the blockchain to have reached such a tipping point?  The WEF report compared the blockchain to the Internet, noting that “Like the Internet, the blockchain is an open, global infrastructure upon which other technologies and applications can be built.  And like the Internet, it allows people to bypass traditional intermediaries in their dealings with each other, thereby lowering or even eliminating transaction costs.”

I agree with this comparison and find it useful to help us understand how blockchains might evolve over the years. So, I’d like to compare the state of the blockchain in 2016 to the state of the Internet 25 years ago or so.

The Smart London Plan

Urbanization is one of the major forces shaping the 21st century - right up there with the digital technology revolution and globalization.  Over half of the world’s population lives in urban areas, and as the 2014 UN World Urbanization Prospect noted: “The continuing urbanization and overall growth of the world’s population is projected to add 2.5 billion people to the urban population by 2050,” with the proportion of the population living in urban areas increasing to 66 percent by 2050.

Just about every study that’s benchmarked the competitiveness of major urban areas ranks London, - along with New York, - as the world’s two top cities.  But despite, - or perhaps because of, - their leadership positions, both cities face major challenges as they deal with economic growth and a growing population.

London has been much in the news lately.  First came the election of Sadik Khan last May, - the first Muslim mayor not only of London but of a major Western capital, followed by the recent Brexit referendum, where London voted to Remain in the EU by an overwhelming 60% of its vote while the UK as a whole voted 52% to Leave.

At this point, it’s very hard to predict where Brexit is heading over the next few months, let alone what it’s long term consequences might be.  But, given its many strengths I have little doubt that London will remain among the world’s very top cities.  So, let me put Brexit aside for the moment and discuss instead what London has been doing to address its major population and economic challenges.

Virtual Work Interactions, Context, and Related Subjects

I just read Tripping Down a Virtual Reality Rabbit Hole,- a very interesting NY Times column by technology journalist Farhad Manjoo.  Manjoo recently spent a few weeks testing the Occulus Rift and the HTC Vive, two of the most powerful VR devices on the market. 

“The whole point of virtual reality is to create a fantasy divorced from the physical world,” he wrote.  “You’re escaping the dreary mortal coil for a completely simulated experience: There you are, climbing the side of a mountain, exploring a faraway museum, flying through space or getting in bed with someone way out of your league…  There are some great games on these systems… There are also several useful experiences, like designing your Ikea kitchen in V.R.”

“But if you’re not a gamer and you’re not looking for a new kitchen, V.R. is, at this point, just too immersive for most media.  A few minutes after donning my goggles, I came to regard my virtual surroundings as a kind of prison… I suspect that V.R. will be used by the masses one day, but not anytime soon.  I’m not sure we’re ready to fit virtual reality into our lives, no matter how excited Silicon Valley is about it.”

Manjoo’s reaction brought to mind the work of Karen Sobel-Lojeski, who’s long been studying technology-mediated interactions.  She’s in the faculty at Stony Brook University as well as the founder of the workplace consulting firm Virtual Distance International.  To be effective, she argues, our technology-based interactions must take place within the proper context, defined as “everything around us that helps us to understand who we are, where we are, and what our role is.”  The way VR works, - at least for now, - is by cutting off all real-world context to better immerse us in its simulations, - an experience that as Farhad Manjoo discovered, can be very unsettling.

FinTech and Financial Inclusion

In early June I spent a few days in Mexico City.  The main purpose of the trip was to participate and give a keynote at the 2016 Cumbre de Directores (Director’s Summit), a conference sponsored by Endeavor Mexico in collaboration with the IPADE Business School.  Endeavor is a global not-for-profit organization dedicated to long-term economic growth by supporting high-impact entrepreneurship in over 25 cities around the world, including Mexico.  The Director’s Summit is Endeavor Mexico’s major annual meeting, bringing together over 400 entrepreneurs and senior executives.

My talk was focused on the changing nature of innovation in the digital economy.  A major part of the talk included a discussion of innovations in the digital payments and financial services ecosystem.  My keynote was followed by two separate FinTech panels, where different entrepreneurs discussed the importance of FinTech in Mexico as well as their individual companies’ efforts in the area.  That same evening I attended and spoke at a reception sponsored by Angel Ventures Mexico, an early stage VC firm where I also heard quite a bit about FinTech startups.  My overall impression is that there’s considerable FinTech activity in Mexico, a large portion of which is aimed at financial inclusion.

Every year, the World Bank publishes the Global Findex database, a measure of financial inclusion around the world, including how individuals save, borrow, make payments and manage risks in over 140 countries.  According to their latest report, - Global Findex 2014, - 62 percent of adults worldwide have an account at a bank, at another type of financial institution, or with a mobile money provider, - up from 51 percent in 2011.  The 2014 report also noted that 2 billion adults remain without an account around the world, a 20 percent decrease from the 2.5 billion unbanked adults in 2011. Technology advances, particularly the rapid growth in mobile devices and digital financial services, are the major reasons for these dramatic improvements.

The Global Findex database includes data for each individual country.  Their 2014 data for Mexico showed that about 39 percent of adults had accounts with financial institutions, - a significant improvement over the 27.4 percent of adults with accounts in 2011.  But, Mexico still lags many of its peers in Latin America.  Over half of all adults have financial accounts in Latin America as a whole, significantly above Mexico’s figure.

Platforms and the New Rules of Strategy

Last week I wrote about one of the talks at the annual conference of the MIT Initiative on the Digital Economy, - Only Humans Need Apply by Tom Davenport, based on his recently published book of the same title.  I would now like to discuss another excellent talk at the same conference, - How Platforms Change Strategy by Boston University professor Marshall Van Alstyne, also based on a recently published book, Platform Revolution: How Networked Markets are Transforming the Economy and How to Make Them Work for You, co-authored with Geoffrey Parker and Sanjeet Choudary.  The three also published a related article in the April issue of the Harvard Business Review.

Van Alstyne started out his presentation by noting that back in 2007, seven firms controlled 99% of handset profits: Nokia, Samsung, Ericsson, Motorola, LG, RIM and HTC.  That same year, Apple’s iPhone was born and began gobbling up market share.  By 2015, only one of the former incumbents had any profit at all, while Apple now generated 92% of the industry’s global profits.

What happened? “Is it likely all 7 incumbents had failed strategies, run by clueless management, lacking execution capabilities?,” he asked.  “Or was something more fundamental happening?…  Nokia and the others had classic strategic advantages that should have protected them: strong product differentiation, trusted brands, leading operating systems, excellent logistics, protective regulation, huge R&D budgets, and massive scale.  For the most part, those firms looked stable, profitable, and well entrenched.”  How can we explain their rapid free fall?

We all know the answer to Van Alstyne’s rhetorical questions. “Apple (along with Google’s competing Android system) overran the incumbents by exploiting the power of platforms and leveraging the new rules of strategy they give rise to.  Platform businesses bring together producers and consumers in high-value exchanges. Their chief assets are information and interactions, which together are also the source of value they create and their competitive advantage.”

Learning to Work with Our Increasingly Smart Machines

A few weeks ago I attended the annual conference of MIT’s Initiative on the Digital Economy.  The day-long conference featured a number of interesting talks on the impact of digital technologies on business, the economy and society.  Tom Davenport, - Babson College professor and IDE Fellow, - gave one such talk on technology and jobs, based on his recently published book Only Humans Need Apply: Winners and Losers in the Age of Smart Machines, co-authored with HBR editor Julia Kirby.

Davenport started his talk by noting that over the past two centuries we’ve seen three distinct stages of automation, based on the kinds of jobs that were replaced by machines.  The machines of the first automation era “relieved humans of work that was manually exhausting,” making up for our physical limitations, - steam engines and electric motors enhanced our physical power while railroads, cars and airplanes helped us go faster and farther.

Next came the automation of jobs involving routine tasks that could be well described by a set of rules and were thus prime candidates for IT substitution.  “Era Two automation doesn’t only affect office workers.  It washes across the entire services-based economy that arose after massive productivity gains wiped out jobs in agriculture, then manufacturing.”  It threatened many transactional service jobs that “are so routinized that they are simple to translate into code,” from bank tellers to airline reservations clerks.

We’ve now entered the third era of automation.  Our increasingly smart machines are “now breathing down our necks…  This time the potential victims are not tellers and tollbooth collectors, much less farmers and factory workers, but rather all those knowledge workers who assumed they were immune from job displacement by machines,…” including, - as Davenport and Kirby poignantly remind us, - “People like the writers and readers of this book.”

The President’s Commission on Enhancing National Cybersecurity

Last February, President Obama issued an Executive Order establishing the Commission on Enhancing National Cybersecurity within the Department of Commerce.  The Commission is charged with “recommending bold, actionable steps that the government, private sector, and the nation as a whole can take to bolster cybersecurity in today’s digital world, and reporting back by the beginning of December.”

The Commission is composed of twelve individuals from the world of business, technology and academia. Former national security advisor Tom Donilon and former IBM CEO Sam Palmisano serve as chair and vice-chair respectively.

To gather the necessary information for its short- and long-term recommendations, the Commission is holding public meetings around the country, each focused on a different sector of the economy.  On May 16, it met in New York City to discuss the challenges and opportunities facing the financial sector.  The meeting included three panels, one on finance, one on insurance, and the third on research and development.

I was a member of the R&D panel, along with MIT professor Sandy Pentland, IBM Fellow Jerry Cuomo, and Greg Baxter, head of digital strategy at Citigroup.  During our 90 minute panel, we each made introductory remarks based on our previously submitted briefing statements and then answered the commissioners’ questions.

Can AI Help Translate Technological Advances into Strategic Advantage?

After many years of promise and hype, artificial intelligence is now being applied to activities that not long ago were viewed as the exclusive domain of humans.  It wasn’t all that long ago that we were wowed by Watson, Siri, and self-driving cars.  But it’s getting harder for our smart machines to truly impress us.  Earlier this year Google’s AlphaGo won a match against one of the world’s top Go players.  Go is a very complex game, for which there are more possible board positions than there are particles in the universe.  Yet, we seem to be taking AlphaGo’s impressive achievement in stride.

“Any sufficiently advanced technology is indistinguishable from magic,” is one of the most memorable quotes of science fiction writer Arthur C. Clarke.  But, as we better understand its promise and limitations, technology becomes just another tool we rely on in our work and daily life.  With familiarity, the romance begins to fade, - as was the case with electricity, cars, airplanes and TV in the early decades of the 20th century, and as has been the case more recently with computers, the Internet, and, - increasingly now, - with AI.

Over time, our feelings turn from wonderment and admiration for the seemingly magical achievements of the technology in its childhood years, to the far more practical questions of what the technology can actually achieve when it grows up.  This has been a particular issue with information technologies in general, including the Internet and AI.

The IT industry has long been associated from what’s been called the Solow productivity paradox, in reference to Robert Solow's 1987 quip: “You can see the computer age everywhere but in the productivity statistics.  We all thought that the Solow paradox was finally behind us when IT-driven productivity surged between 1996 and 2003.  But despite the continuing advances in technology, productivity is now back to its slow pre-1995 levels, for reasons that are still not well understood.

Digital technologies are all around us.  But, are they a major source of competitive differentiation?  Are they a strategic value to business?  Can they help increase innovation and productivity and drive long term growth?  These questions have no easy answers, as we have learned over the years.

The Public Face of Science

Last month, the American Academy of Arts and Sciences launched a three year initiative to address the complex relationship between scientists and the public.  The Public Face of Science project will explore the interactions of the general public with science, technology, medicine and related areas.

Throughout the 20th century, polls have consistently indicated strong public support for science and technology, especially during the Cold War decades following World War 2.  But recent polling data, - and in particular, a recent study conducted by the Pew Research Center, -  reveals a more complex relationship between the public and science.  While scientific achievements are still recognized and valued, there is a large opinion gap between the general public and scientists on a number of scientific issues.

The Pew findings were released in a January, 2015 report based on two surveys of science-related issues conducted in collaboration with the American Association for the Advancement of Science (AAAS).  The first survey is based on a representative sample of 2,002 general public adults and was conducted by landline and mobile phones.  The second survey was conducted online, and is based on a representative sample of 3,748 US-based scientists who are members of AAAS.

The Analog Foundations of the Digital Revolution

This past January, the World Bank issued the Digital Dividends report, a comprehensive study of the state of digital developments around the world.  All in all, it’s a mixed picture.  Digital technologies have been rapidly spreading in just about all nations, but their expected digital dividends, - i.e., their broad development benefits, - have lagged behind and are unevenly distributed.

“We find ourselves in the midst of the greatest information and communications revolution in human history,” notes the report in its Foreword.  “More than 40 percent of the world’s population has access to the internet, with new users coming online every day.  Among the poorest 20 percent of households, nearly 7 out of 10 have a mobile phone…”  But, while this is great progress, much remains to be done.  Many are still left behind due to their limited connectivity, and are thus unable to fully benefit from the global digital revolution.

While universal connectivity is necessary, it’s far from sufficient, the report adds.  “[T]raditional development challenges are preventing the digital revolution from fulfilling its transformative potential…  the full benefits of the information and communications transformation will not be realized unless countries continue to improve their business climate, invest in people’s education and health, and promote good governance.”

Let me attempt to summarize the salient findings and recommendations of this comprehensive (over 300 pages) report.

Why Some Work Groups Thrive While Others Falter

I recently read an interesting article published earlier this year in the NY Times Magazine by reporter Charles Duhigg, - What Google Learned From its Quest to Build the Perfect Team.  The article is focused on Project Aristotle, an initiative Google embarked on in 2012 that examined hundreds of Google teams in their quest to learn why some work groups thrive while others falter. 

“[M]any of today’s most valuable firms have come to realize that analyzing and improving individual workers - a practice known as employee performance optimization -  isn’t enough,” writes Duhigg.   “As commerce becomes increasingly global and complex, the bulk of modern work is more and more team-based… at many companies, more than three-quarters of an employee’s day is spent communicating with colleagues.”

“In Silicon Valley, software engineers are encouraged to work together, in part because studies show that groups tend to innovate faster, see mistakes more quickly and find better solutions to problems,” he later adds.  “Studies also show that people working in teams tend to achieve better results and report higher job satisfaction.  In a 2015 study, executives said that profitability increases when workers are persuaded to collaborate more.  Within companies and conglomerates, as well as in government agencies and schools, teams are now the fundamental unit of organization.  If a company wants to outstrip its competitors, it needs to influence not only how people work but also how they work together.”

The article devotes several paragraphs to the pioneering research on group performance by MIT professor Tom Malone, CMU professor Anita Woolley and their various collaborators over the past 8 years.  Their work addressed a very intriguing set of questions: Do groups exhibit characteristic levels of intelligence which can be measured and used to predict the group’s performance across a wide variety of cognitive tasks?  If so, can you devise tests to measure the group’s intelligence using methodologies and statistical techniques similar to those that have been applied to measure the IQs of individuals over the past hundred years?