Irving Wladawsky-Berger

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.”

The Top Ten Emerging Technologies of 2016

For the past several years, the World Economic Forum (WEF) has published an annual list of the Top Ten Emerging Technologies that would likely have the greatest impact on the world in the years to come.  A few weeks ago, the WEF published its 2016 Top Ten list.  The list is compiled by the WEF Meta-Council on Emerging Technologies, a panel of global experts led by Dr. Bernard Meyerson, - IBM Fellow and Chief Innovation Officer.

“Horizon scanning for emerging technologies is crucial to staying abreast of developments that can radically transform our world, enabling timely expert analysis in preparation for these disruptors,” said Meyerson. “The global community needs to come together and agree on common principles if our society is to reap the benefits and hedge the risks of these technologies.”

The technologies on the list are not new.  They’ve been worked on for many years.  But their selection to the Top Ten List indicates that, in the opinion of the council members, each of these technologies has now reached a maturity and acceptance tipping point where its impact can be meaningfully felt.

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 Continuing Evolution of Service Science

Service Science emerged in the mid-2000s as an academic discipline aimed at applying technology and science to the service sector, - by far the largest sector of the US economy and of most economies around the world.  Since its inception, IBM has played a major role in the continuing evolution of service science, coining the term Service Science, Management and Engineering (SSME) to highlight the interdisciplinary nature of this emerging discipline.  I was personally involved in these efforts during my last few years at IBM.  Subsequently, it’s continued to be one of the main subjects I’ve talked about in seminars and written about in this blog.

A few weeks ago I had an interesting conversation on the the state of service science with analysts from an IT research organization who were preparing a report on the subject for their clients.  Our discussion led me to reflect on the evolution of service science over the past several years.  I think that we are hearing a bit less about it these days.  But is that because we’ve become tired of the subject and moved on, or because the application of science and technology to services is now so well accepted that it’s no longer a topic of debate?  I very much think it’s the latter.

Vehicle Automation - a Very Important Priority for AI Research

In September, 2014, I attended an MIT conference that explored the major progress that’s taken place in artificial intelligence, robotics and related technologies over the past several years. Autonomous vehicles was one of the main areas of discussion.  With most other topics, there was considerable consensus, but not so with self-driving cars.  While some thought that fully autonomous vehicles will be all around us within a decade or so, others were not quite so sure, myself included, due to the many highly complex technical, economic and societal issues that must be worked out.

I was reminded of this meeting a few weeks ago when I read that a Florida man had been killed while driving a Model S Tesla in autopilot mode.  The accident is still under investigation, but it appears that the Tesla struck a tractor-trailer truck that was making a left turn in front of its path.  Neither the driver or the Tesla’s autopilot noticed that a truck was suddenly crossing its lane of traffic, perhaps because the white truck was hard to spot against a bright sky.

This accident has led to a renewed discussion of the current state-of-the-art of vehicle automation, the approaches being pursued by different companies, and the prospects for the near- and long-term future.

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.

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 Prosperity Puzzle

The April 30 issue of The Economist includes a special briefing on The Prosperity Puzzle. The briefing highlights how tricky it is to compare living standards across countries, across economic classes within a country, and, - arguably hardest of all, - across time.

“Which would you prefer to be: a medieval monarch or a modern office-worker?,” it glibly asks.  “The king has armies of servants.  He wears the finest silks and eats the richest foods.  But he is also a martyr to toothache.  He is prone to fatal infections.  It takes him a week by carriage to travel between palaces.  And he is tired of listening to the same jesters.  Life as a 21st-century office drone looks more appealing once you think about modern dentistry, antibiotics, air travel, smartphones and YouTube.”

The point is further illustrated by referencing the research of Yale economist William Nordhaus.  In the mid 1990s, Nordhaus looked at the evolution of the price of light over the past two centuries in Do Real-Output and Real-Wage Measures Capture Reality? The History of Lighting Suggests Not.

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?

Could Blockchain Prove to Be “The Next Big Thing”?

Over the past several decades, information technologies (IT) have been fundamentally transforming companies, industries and the economy in general.  In its early years, - ’60s, ’70s, ’80s - companies deployed IT primarily to automate their existing processes, - leaving the underlying structure of the business in place.  It wasn’t until the 1990s, - with the pioneering work of Michael Hammer and others on business process reengineering, - that companies realized that just automating existing processes wasn’t enough.  Rather, to achieve the promise of IT, it was necessary to fundamentally redesign their operations, examine closely the flow of work across the organization, and eliminate legacy processes that no longer added value to the business.

Organizational transformation was then taken beyond the boundaries of the company with the explosive growth of the Internet.  The Internet made it significantly easier to obtain goods and services outside the firm, enabling companies to rely on business partners for many of the functions once done in-house.  To compete effectively in an increasingly interconnected global economy, companies now had to optimize not only the flow of work within their own organizations but across their supply chain ecosystems.  Over the past 20 years, such ecosystem-wide transformations have been disrupting the business models of industry after industry, - from retail and manufacturing to media and entertainment.

The banking industry has long been one of the major users of IT, - among the first to automate its back-end and front-office processes and to later embrace the Internet and smartphones.  However, banking has been relatively less disrupted by digital transformations than other industries.  In particular, change has come rather slowly to the world’s banking infrastructure.

Is FinTech Forcing Banking to a Tipping Point?

For the past few decades, digital technologies have been systematically transforming one industry after another.  The transformations have generally proceeded along three different stages.  First comes the use of IT to improve the productivity and quality of production-oriented, back-end processes.  Distribution comes next, leveraging the universal reach and connectivity of the Internet over the past 20 years.  The transformation then reaches a tipping point when technology radically changes the user experience, - as has happened with the rise of smartphones over the past decade, - leading to a fundamental disruption of the industry and its business models.

While this digital disruption journey is ultimately inevitable, the pace varies widely across industries.  The IT industry has been the most disrupted, - often by its own digital creations in a kind of sorcerer’s apprentice scenario.  Over my long career, I’ve seen many once powerful IT companies done in by technology and market changes, and either disappear altogether or become shadows of their former selves.

Beyond IT, few industries have felt the impact of digital forces like media.  Everything seems to be changing at once, from the way content is produced and delivered, to the sources of revenue and profits.  In less than two decades, the global recorded music industry has lost over half its revenues, while the drop in newspaper advertising revenue in the US has been even steeper.  Retail has also been undergoing major changes with the rise of e-commerce, as has telecommunications with the transition to mobile phones and wireless data.

How about the banking industry, which has long been a major user of information technologies, - including back- and front-office automation, ATM’s, Internet banking, data-driven risk management, fraud detection, and mobile financial apps?

Computing Beyond Moore’s Law

The March 12 issue of The Economist  includes a special report on the future of computing after the very impressive 50-years run of Moore’s Law.

In his now legendary 1965 paper, Intel co-founder Gordon Moore first made the empirical observation that the number of components in integrated circuits had doubled every year since their invention in 1958, and predicted that the trend would continue for at least ten years, a prediction he subsequently changed to a doubling every two years.  The semi-log graphs associated with Moore’s Law have since become a visual metaphor for the technology revolution unleashed by the exponential improvements of just about all digital components, from processing speeds and storage capacity to networking bandwidth and pixels.

The 4004, Intel’s first commercial microprocessor, was launched in November, 1971.  The 4-bit chip contained 2,300 transistors.  The Intel Skylake, launched in August, 2015, contains 1.75 billion transistors which collective deliver about 400,000 more computing power than the 4004.  Moore’s Law has had quite a run, but like all good things, especially those based on exponential improvements, it must eventually slow down and flatten out.

In its overview article, The Economist reminds us that Moore’s Law was never meant to be a physical law like Newton’s Laws of Motion, but rather “a self-fulfilling prophecy - a triumph of central planning by which the technology industry co-ordinated and synchronised its actions.”  It also reminds us that its demise has been long anticipated: for a while now, the number of people predicting the death of Moore’s Law has also been doubling every two years.

So what happens as the end is now in sight?  I’ve been thinking about this question for a while.  And, and as is often the case when it comes to highly complex systems, I find myself turning to biology as a source of inspiration, in particular, to evolutionary biology.

Anticipating the Future of the IT Industry

How can we best anticipate the future of a complex, fast changing industry like IT?  Which hot technology innovations, - e.g., artificial intelligence, the blockchain, cloud computing, - will end up having a big impact and which are destined to fizzle?  What can we learn from the IT industry’s 60-year history that might help us better prepare for whatever lies ahead?

A major way of anticipating the future of any economic or social entity, - be it a company, industry, university, government agency or city, - is to explore and learn from its history.  While there’s no guarantee that historical patterns will continue to apply going forward, they might well be our most important guides as we peer into an otherwise unpredictable future.

I’ve been involved with computers since the early 1960s, first as a student at the University of Chicago, then in my long career at IBM, and subsequently through my relationship with a number of companies and universities.  I’ve thus had a ringside seat from which to observe the journey the IT industry’s been on since those early days.

Let me share some of my personal impressions of this journey through the lens of three key areas, each of which has played a major role throughout IT’s history, and will continue to do so well into its future: data centers, transaction processing, and data analysis.

The MIT Inclusive Innovation Competition

About three years ago, MIT launched the Initiative on the Digital Economy (IDE), a major effort focused on the broad changes brought about by the relentless advances of digital technologies.  As its website explains:

“While digital technologies are rapidly transforming both business practices and societies and are integral to the innovation-driven economies of the future, they are also the core driver of the great economic paradox of our time.  On one hand, productivity, wealth, and profits are each at record highs; on the other hand, the median worker in America is poorer than in 1997, and fewer people have jobs.  Rapid advances in technology are creating unprecedented benefits and efficiencies, but there is no economic law that says everyone, or even a majority of people, will share in these gains.

The future of work and jobs is one of the major areas being addressed by IDE.  What will the workforce of the future look like?; Where will jobs come from in the coming years?; Will the nature of work be significantly different in the digital economy?; How can we accelerate the transformation of institutions, organizations, and human skills to keep up with the quickening pace of digital innovation?

To help come up with breakthrough answers to these very challenging questions, IDE just launched its first annual Inclusive Innovation Competition.  The competition aims to identify, celebrate and award prizes to “organizations that are inventing a more sustainable, productive, and inclusive future for all by focusing on improving economic opportunity for middle- and base-level income earners.” 

The Coming Robotics Revolution

Hi, Robot: Work and Life in the Age of Automation, reads the Hamlet-inspired cover of the July, 2105 issue of Foreign Affairs.  The clever cover highlights the issue’s main theme, artificial intelligence and robotics, - a set of technologies that some fear could one day threaten our very existence. 

As its introductory article reminds us “new technologies have been revolutionizing the world for centuries, transforming life and labor and enabling an extraordinary flourishing of human development.  Now some argue that advances in automation and artificial intelligence are causing us to take yet another world-historical leap into the unknown.” 

Speculations about a future radically transformed by technology are nothing new.  But, with AI and robots seemingly everywhere, the concerns surrounding their long term impact may well be in a class by themselves.  Like no other technologies, AI and robots force us to explore the boundaries between machines and humans.  Will they turn out like other major innovations, e.g., steam power, electricity, cars, - highly disruptive in the near term, but ultimately beneficial to society?  Or, will we see a more dystopian future, as smart machines increasingly encroach on activities requiring intelligence and cognitive capabilities that not long ago were the exclusive domain of humans?  Opinions abound, but in the end, we don’t really know.

What’s the Value of a Liberal Arts Education in Our 21st Century Digital Economy?

A few years ago, I came across a very interesting 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.”

“Learning how to think critically - how to imaginatively frame questions and consider multiple perspectives - has historically been associated with a liberal arts education, not a business school curriculum, so this change represents something of a tectonic shift for business school leaders.”  Achieving this goal would require business schools to move into territory “more traditionally associated with the liberal arts: multidisciplinary approaches, an understanding of global and historical context and perspectives, a greater focus on leadership and social responsibility and, yes, learning how to think critically.”

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.”

The Fourth Industrial Revolution

The Fourth Industrial Revolution: what it means, how to respond was the central theme of the 2016 World Economic Forum (WEF) that took place earlier this year in Davos, Switzerland.  The theme was nicely explained by Klaus Schwab, WEF founder and executive chairman, in the lead article of a recently published Foreign Affairs Anthology on the subject.

Dr. Schwab positions the Fourth Industrial Revolution within the historical context of three previous industrial revolutions.  The First, - in the last third of the 18th century, - introduced new tools and manufacturing processes based on steam and water power, ushering the transition from hand-made goods to mechanized, machine-based production.  The Second, - a century later, - revolved around steel, railroads, cars, chemicals, petroleum, electricity, the telephone and radio, leading to the age of mass production.  The Third, - starting in the 1960s, - saw the advent of digital technologies, computers, the IT industry, and the automation of process in just about all industries.

“Now a Fourth Industrial Revolution is building on the Third, the digital revolution that has been occurring since the middle of the last century,” he noted.  “It is characterized by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres.”

Shaping the Future of the Internet

The Winter 2016 issue of Dædalus, the Journal of the American Academy of Arts and Sciences, is devoted to the Internet.  Its 7 articles explore some of the major issues shaping the Internet’s future.  The issue was curated by Harvard professor Yochai Benkler and MIT research scientist David Clark, whose joint introduction and individual papers frame the overall discussion.

“The Internet was born in 1983,” write Benkler and Clark in the Introduction.  That year saw the adoption of TCP/IP, - the communications protocol that defines the Internet to this day.  Its technical directions and overall culture have been largely determined by the academic and research communities, who were also its early users.  With strong government support, they developed a system that “only a researcher could love: general, abstract, optimized for nothing, and open to exploration of more or less anything imaginable using connected computers.”

The Internet has since evolved “from a network that primarily delivered email among academics and government employees, to a network over which the World Wide Web arose, to the video and mobile platform it has become - and the control network for embedded computing that it is fast becoming.”  From its niche research beginnings, it’s become the universal platform for collaborative innovation, enabling startups, large institutions, and everyone in between to quickly develop and bring to market many new digital products and services.

What design choices have led to the Internet as we know it?  Could it still evolve into a fundamentally different platform than the one we use today?  What decisions could significantly shape its future?  These are among the very important questions explored in the Dædalus issue.  In their Introduction, Benkler and Clark summarized some of the key themes that emerged from the various papers, - a few of which I’d now like to discuss.

The Rise of the Platform Economy

What do we mean by platform?  I particularly like this definition by MIT Professor Michael Cusumano: “A platform or complement strategy differs from a product strategy in that it requires an external ecosystem to generate complementary product or service innovations and build positive feedback between the complements and the platform.  The effect is much greater potential for innovation and growth than a single product-oriented firm can generate alone.”

The importance of platforms is closely linked to the concept of network effects - the more products or services it offers, the more users it will attract.  Scale increases the platform’s value, helping it attract more complementary offerings which in turn brings in more users, which then makes the platform even more valuable… and on and on and on.

Platforms have long played a key role in the IT industry.  IBM’s System 360 family of mainframes, announced in 1964, featured a common hardware architecture and operating system, enabling customers to upgrade their systems with no need to rewrite their applications.  The ecosystem of add-on hardware, software and services that developed around System 360 helped it become the premier platform for commercial computing over the next 25 years.

In the 1980s, the explosive growth of personal computers was largely driven by the emergence of the Wintel platform based on Microsoft’s operating systems and Intel’s microprocessors, which attracted a large ecosystem of hardware and software developers. 

The 1990s saw the commercial success of the Internet and World Wide Web, driving platforms to a whole new level.  Internet-based platforms connected large numbers of PC users to a wide variety of web sites and online applications.  The power of platforms has grown even more dramatically over the past decade, with billions of users now connecting via smart mobile devices to all kinds of cloud-based applications and services.

What’s the current state and growth potential of platform companies?  How many large platforms are currently operating around the world?  What’s their impact on established enterprises?  These are among the questions addressed in in a recent report, The Rise of the Platform Enterprise: A Global Survey led by Peter Evans and Annabelle Gawer and sponsored by the Center for Global Enterprise.  The report is based on a comprehensive survey of the 176 platform companies around the world with an individual valuation exceeding $1 billion.  Their aggregate market value was over $4.3 trillion.

Leadership in a Changing World

What are the critical competencies needed to lead in our fast-changing business environment?  This question was the focus of a study jointly conducted by the professional services firm Heidrick & Struggles and the University of Oxford Said Business School.  The study was based on over 150 conversations with CEOs from a wide range of sectors around the world.  Its findings were recently published in The CEO Report: Embracing the Paradoxes of Leadership and the Power of Doubt.

“Declining tenure rates and levels of public trust suggest that CEO leadership has not kept pace with increased expectations,…” notes the report in its opening paragraphs.  “Indeed, the role of the CEO is becoming more complex as competing and increasingly vocal stakeholders permeate organizations.”  Leading in today’s world requires new thinking: “past experience is no longer a reliable guide for future action…  success as a CEO today hinges on continual growth in the role, even more than on the preparation beforehand.”

The key challenge confronting CEOs, - and senior executives in general, - is the relentless pace of change.  But, while speed is the major dimension of change, it’s not the only one.  Beyond speed, executives must also focus on scope and significance.  They must carefully consider a few fundamental questions about each:

Corporate Survival: Lessons from Biology

Having lived through IBM’s near-death experience in the early 1990s, respect for the forces of the marketplace is edged deep in my psyche.  It’s frankly sobering how many once powerful IT companies are no longer around or are shadows of their former selves.  The carnage might be more pronounced in the fast-changing IT industry, but no industry is immune.  It would seem as if darwinian principles apply in business almost as much as they do in biology. 

A few weeks ago I discussed a paper published last year, The Mortality of Companies, by physicist Geoffrey West and his collaborators at the Santa Fe Institute.  Based on their extensive analysis of data about publicly traded US companies, they were surprised to discover that a typical firm lasts about ten years before it gets merged, acquired or liquidated, and that a firm’s mortality rate is independent of its age, how well established it is or what it does.  While beyond the scope of their study, the authors speculated that biological ecosystems are likely to shed valuable insights into their findings.

Such similarities between business and biological ecosystems was the focus of The Biology of Corporate Survival, a paper recently published in the Harvard Business Review (HBR) by Martin Reeves, Simon Levin, and Daichi Ueda. 

“Some business thinkers have argued that companies are like biological species and have tried to extract business lessons from biology, with uneven success,” note the authors.  “We stress that companies are identical to biological species in an important respect: Both are what’s known as complex adaptive systems.  Therefore, the principles that confer robustness in these systems, whether natural or manmade, are directly applicable to business.”

The (Uneven) Digitization of the US Economy

Digital technologies are all around us, - increasingly ubiquitous and commoditized.  But, are they a major source of competitive differentiation?  Are they still a strategic value to business?  Can digital innovation drive long term economic growth?

Several weeks ago, the McKinsey’s Global Institute (MGI) published a report addressing these questions.  Digital America: A tale of the haves and have-mores aims to quantify the state of digitization of the US economy.  The report introduces the MGI Industry Digitization Index, a methodology for exploring the various ways US companies are going about their digital journey, - based on 27 indicators that measure how they’re building digital assets, expanding digital usage, and creating a digital workforce.

“Digital innovation, adoption, and usage are evolving at a supercharged pace across the US economy,” notes the report in its opening paragraph. “As successive waves of innovation expand the definition of what is possible, the most sophisticated users have pulled far ahead of everyone else in the race to keep up with technology and devise the most effective business uses for it.”

Let me discuss a few of the findings in this extensive report.

The Blockchain and Open Innovation

Transformational innovations don’t always play out as originally envisioned.  Once in the marketplace, they seem to acquire a life of their own.  Lest we forget, the Internet started out as a DARPA sponsored project aimed at developing a robust, fault-tolerant computer network.  ARPANET was launched in 1969, and by the mid-1980s, it had grown and evolved into NSFNET, a network widely used in the academic and research communities.  And, the World Wide Web was first developed by Tim Berners-Lee at CERN in the late 1980s to facilitate the sharing of information among researchers around the world.  They’ve both gone on to change the world, - to say the least.

The blockchain first came to light around 2008 as the architecture underpinning bitcoin, the best known and most widely held digital currency.  But, as with the Internet, the Web and other major technologies, the blockchain has now transcended its original objective.  It has the potential to revolutionize the finance industry and transform many aspects of the digital economy. 

Two press announcements released in mid-December are serious milestones in its evolution.  Let me explain.

Why People and Companies Die While Cities Keep Growing

The Winter issue of strategy+business includes a very interesting article on theoretical physicist Geoffrey West, - The Fortune 500 Teller.  Dr. West is Distinguished Professor and Past President of the Santa Fe Institute (SFI), a non-profit research institute dedicated to the study of complex systems.  Prior to joining the SFI in 2003, he was the leader and founder of the high energy physics group at Los Alamos National Lab.

About 20 years ago, West got interested in whether some of the techniques and principles from the world of physics could be applied to complex biological and social systems.  In particular, he wondered if we could apply empirical, quantifiable and predictive scientific methods to help us better understand complex biological organisms and social organizations like cities and companies.

In the 1990s, his attention first turned to biology.  There are enormous variations in the characteristics of living creatures, their live spans, pulse rates, metabolism, and so on.  How do these characteristics change with body size?  Why do human beings live roughly 80 to 100 years, while mice live only two to three years.  Are there some common principles that apply to all living creatures regardless of size?  Can we find empirical mathematical models that might allow scientists to ask big questions about life, aging and death?

Learning to Apply Data Science to Business Problems

This past semester I was involved in an interesting course at MIT’s Sloan School of Management, - Analytics Labs (A-Lab).  A-Lab’s objective is to teach students how to use data sets and analytics to address real-world business problems.  Companies submit project proposals prior to the start of the class, including the business problem to be addressed and the data on which the project will be based. Students are then matched with the project they’re most interested in and grouped into teams of 3-4 students.

A-Lab received over 20 project proposals from different companies, of which 13 were selected by the students.  Each project team was assigned a research mentor to provide guidance as appropriate.  I mentored a 3-student team that worked on a project sponsored by MasterCard.  The students explored the possibility of improving on predictions of the economic performance of emerging markets by coupling existing economic indicators data with consumer behavior based on MasterCard’s transaction data.  This is a particularly interesting project because economic data in emerging markets is often not as reliable as the data in more advanced markets.

But more important for the students, the various A-Lab projects served as a concrete learning experience on what data science is all about, - how to leverage messy, incomplete, real-world data to shed light on a complex and not-so-well-defined problem.

Trust and the On-Demand Economy

The intrinsic structure of companies has long been a subject of study, most famously by Ronald Coase, the eminent British economist and recipient of the 1991 Nobel Prize in economics.  In 1937, Coase published a seminal paper, The Nature of the Firm, in which 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.  Firms thus came into being to make it easier to get work done.  A well managed company tries to achieve a good balance between the work that gets done within and outside its boundaries.  

Over the past few decades, the firm has been going through dramatic changes, driven by both advances in information technologies and the heightened competitive pressures brought about by globalization.  Fundamental changes have taken place in the structure of firms and in the overall flow of goods and services in the economy.  As this 2005 IBM study noted:

“The nature of competition - increasingly intense, global and unpredictable - requires strength across the board.  So the objective is to decompose the enterprise into its component parts, understand with great precision what is truly differentiating - where the enterprise has strengths and weaknesses - and then make decisions about how to build, buy or partner for world-class capability.” 

“In this model, companies can focus their energies on their true point of differentiation, instead of trying to master many domains and ultimately squander competitive advantage by dispersing focus and investment.  Rather than existing as static and fixed organizations, more enterprises could essentially become an aggregation of specialized entities with complementary interests - expanding, contracting and reconfiguring themselves in a way that best adapts to or even anticipates market dynamics.”

The Rise of the T-Shaped Organization

The concept of T-shaped skills was first introduced over 20 years ago, but its importance, - to both individuals and organizations, - has continued to rise.  A growing number of articles have been extolling the value of T-shaped professionals, that is, individuals who combine deep cognitive, analytical, and/or technical skills in a specific discipline, with broad multidisciplinary, social skills.

As described by IDEO CEO Tim Brown:  “The vertical stroke of the T is a depth of skill that allows them to contribute to the creative process.  That can be from any number of different fields: an industrial designer, an architect, a social scientist, a business specialist or a mechanical engineer.  The horizontal stroke of the T is the disposition for collaboration across disciplines.”

T-shaped skills are increasingly valued in the marketplace.  For example, a recent paper by Harvard professor David Deming showed that labor markets have been rewarding individuals with strong social skills, that is, with interpersonal skills that facilitate interactions and communications with others.  Deming’s research showed that since 1980, social-skill intensive occupations have enjoyed most of the employment growth across the whole wage spectrum.  Employment and wage growth have been particularly strong in jobs requiring both high cognitive and high social skills.  But since 2000, they have fallen in occupations with high cognitive but low social skill requirements, - “suggesting that cognitive skills are increasingly a necessary but not sufficient condition for obtaining a high-paying job.”

Disruptive Innovation Revisited

Disruptive innovation was first introduced by Harvard Business School professor Clayton Christensen in a 1995 Harvard Business Review (HBR) paper co-written with Joseph Bower.  The concept was further elaborated and popularized in Christensen’s 1997 bestseller The Innovator's Dilemma, and in the articles and books he’s written or co-authored since then.  Few business concepts have been as long and widely used.

But as often happens with serious ideas once they become popular, disruptive innovation has joined the pantheon of trendy, overused business buzzwords, - stretched and applied way beyond its intended meaning.  It’s even led to a rather strong backlash in a 2014 New Yorker article by Harvard history professor Jill Lepore.

20 years after its introduction, Christensen has revisited his original concept in What is Disruptive Innovation?, co-written with Michael Raynor and Rory McDonald, and just published in HBR’s December issue.  The authors aim to define what disruptive innovation is and what it isn’t, as well as to update the theory based on the experiences of the past two decades.

“The theory of disruptive innovation… has proved to be a powerful way of thinking about innovation-driven growth…,” they write.  “Unfortunately, disruption theory is in danger of becoming a victim of its own success.  Despite broad dissemination, the theory’s core concepts have been widely misunderstood and its basic tenets frequently misapplied.  Furthermore, essential refinements in the theory over the past 20 years appear to have been overshadowed by the popularity of the initial formulation.  As a result, the theory is sometimes criticized for shortcomings that have already been addressed.”

The Continuing Evolution of Cloud Computing

I’ve been closely following cloud computing for a number of years, having posted my first cloud blog in March of 2008.  A few months later I gave a presentation at a  cloud-based conference.  The overall sense at that conference was that something big and profound was emerging in the IT industry.  Cloud computing could well be The Next Big Thing - one of those massive changes that the IT industry goes through from time to time that really shake things up, - like the advent of personal computers in the 1980s and the Internet in the 1990s. 

Cloud has fulfilled those early expectations, having made much progress in a relatively short time.  As I look back at its evolution over the past few years, I think of cloud as having gone through three main, overlapping phases.

Early adopters viewed cloud as computing-on-demand.  Next, cloud introduced a much more disciplined approach to the architecture and management of large IT infrastructures.  And by now, cloud has become accepted as a major transformational force in IT, in business, and in the economy in general.

Let me discuss each of these phases. 

The Growing Value of Social Skills

I recently read a very interesting paper, The Growing Importance of Social Skills in the Labor Market, by Harvard professor David Deming.  Deming’s paper shows that over the past several decades, labor markets have been increasingly rewarding social skills, that is, interpersonal skills that facilitate interactions and communications with others.  He presents evidence that since 1980, social-skill intensive occupations have enjoyed most of the employment growth across the whole wage spectrum, and that employment and wage growth have been particularly strong in jobs that require both high cognitive and high social skills. 

Deming’s paper builds on the work of MIT economist David Autor, a leading authority on the impact of technological change on the US labor market.  A few weeks ago I wrote about a paper he published this past summer on the history and future of workplace automation.  In that paper, Autor summarized the sharp polarization of job opportunities that’s taken place in the US over the past two decades, noting that job opportunities have significantly expanded in both high-skill and low-skill occupations, while they have significantly contracted for mid-skill jobs. 

The reason for this polarization is that automation has been most successful when applied to mid-skill routine tasks, that is, tasks or processes that follow precise, well understood procedures that can be well described by a set of rules.  The occupations most susceptible to automation have included blue-collar physical activities such as manufacturing and other forms of production, as well as white-collar, information-based activities like accounting, record keeping, and many kinds of administrative tasks.  As a result, these occupations have experienced the biggest declines in employment opportunities and earnings. 

On the other hand, non-routine tasks are much harder to describe by a set of rules that a machine can follow.  These include manual jobs in fast-food restaurants, janitorial services and health-care aides that require relatively low skills and education, as well as high-skill jobs that involve expert problem solving and complex communications requiring strong cognitive skills and a college education.

Why Blockchains Could Transform How the Economy Works

The October 31 issue of The Economist featured the blockchain in its cover: “The Trust Machine: How the technology behind Bitcoin could change the world.”  Its two articles on the subject explain what blockchains are about, as well as why we should care about an exotic technology that involves concepts from cryptography, game theory and distributed computing. 

Right up front, the Economist distinguishes between three different notions that are often muddled up when discussing blockchains: 

• Bitcoin, the best known and most widely held digital currency, whose users can transact directly with each other with no need for a central authority, - be it a bank or government agency, - to certify the validity of the transactions.
  

• The blockchain architecture underpinning bitcoin, whose protocols were specifically designed to control the creation and transfer of bitcoins. 

• The general concept of blockchain, a distributed database architecture with the ability to handle trust-less transactions where no parties need to know nor trust each other for transactions to complete. 

Bitcoin has had a mixed reputation, due to its wild fluctuations in value and past links to illicit activities.  And, bitcoin-specific blockchain concepts like mining might well be perceived as too wasteful of computing power and energy by all but the most libertarian of bitcoin supporters.  But the advanced technologies and architectures underlying blockchains are being increasingly accepted as having important implications far beyond bitcoin and other cryptocurrencies.

The blockchain holds the promise to revolutionize the finance industry by bringing one of its most important and oldest concepts, the ledger, to the Internet age.  Beyond finance, the blockchain “offers a way for people who do not know or trust each other to create a record of who owns what that will compel the assent of everyone concerned.  It is a way of making and preserving truths.”

Two-Speed IT Architectures

I recently read an interesting McKinsey article, Organizing for digital acceleration: Making a two-speed IT operating model work.  The article argues that born digital  Internet companies, - e.g., Amazon, Google, Facebook, - are setting the standards in the quest to understand and optimize the customer experience, challenging traditional companies to keep up.  These older companies have to both leverage the back-end systems, processes and overall capabilities that have served them well over the years, while adopting innovative consumer-facing technologies to enhance their customers’ experiences.

The article starts out by summarizing the best practices of born digital companies:

• Provide the appropriate information and platforms so customers can find what they need quickly and reliably. 
• Align technology and production systems with business goals. 
• Limit the size of application-development teams. 
• Focus on agile product development to enhance customer engagements. 
• Encourage product managers to think about digital experiences rather than discrete applications or components. 
• Collect and learn from consumer data.
• Engage in frequent testing and experimentation.
• Don’t be afraid to fail.
  

Technological Unemployment and the Future of Work

Few topics are as important, - and as challenging to anticipate, - than the future of work given our justifiable fears of rising technological unemployment.  How are job markets likely to evolve in our 21st century digital economy?  This question has been widely discussed for years, but, - at the end of the day, - we don’t really have good answers.

One such discussion took place this past September at the The World Summit on Technological Unemployment in New York.  Its agenda featured top experts on the subject, including Larry Summers, Robert Reich and Joseph Stiglitz.  I moderated a panel on Technology and the Future of Work, where MIT economist David Autor and NY Times reporter John Markoff talked about their most recent work.  The Summit explored many good ideas, but there were no definitive answers.

Autor’s most recent paper on the subject, Why Are There Still So Many Jobs? The History and Future of Workplace Automation, frames the topic through a number of important questions, including:

• Why hasn’t automation already wiped out a majority of jobs?;
• Will mid-skill, mid-pay jobs continue to decline?; and
• What’s the impact of AI, robotics and other advanced technologies?

Design Thinking and the Workplace Experience

Design has long played a major role in product innovation.  But in the last few years, a shift has been underway bringing design to the very core of the business.  “The Evolution of Design Thinking: It’s no longer just for products. Executives are using this approach to devise strategy and manage change,” read the cover of the Harvard Business Review’s September issue, which featured several articles on the subject. 

Leading-edge companies are leveraging design thinking to translate technological advances into compelling customer experiences in order to seize market share from more traditional competitors.  As noted in one of the HBR articles, design-centric organizations are adamantly focused on their customer’ needs, rather than on their internal operational efficiencies.

A second HBR article explored a different kind of application.  To help overcome the stiff resistance often encountered by disruptive innovations, - both within one’s own organization and in the marketplace, - the article proposed that design thinking should be applied to their actual introduction, - a process it calls intervention design.

I would now like to turn to another recent article, Management by Design, by professors Mark Gruber, Nick de Leon, Gerry George and Paul Thomson.  As the authors argue, design principles should be applied within the management domain itself, to help rethink business processes, workflows and the overall structure of the organization and thus create what it calls a New Workplace Experience (NWX).

Bridging the World’s Knowledge Divide: Technology + Competition, Skills and Institutions

A few months ago I attended the 12th annual Brookings Blum Roundtable on Global Poverty, a meeting that brought together around 50-60 policy and technical experts from government, academia, business, investors and NGOs.  This year’s event was focused on the impact of digital technologies on economic development in emerging and developing countries.  It was organized around six different sessions, each of which explored the links between technology and development through a different lens. 

Prior to the event, the Brookings Institution commissioned a policy brief for each session to help set the stage for the ensuing discussions.  I wrote one of the briefs, - Will the Digital Revolution Deliver for the World’s Poor.  I would now like to discuss another brief which I found quite interesting, - Will the Spread of Digital Technologies Spell the End of the Knowledge Divide?, by Deepak Mishra, lead economist at the World Bank.  Dr. Mishra is also co-director of the World Development Report 2016: Internet for Development, which will shortly be released by the World Bank.

The Future of Jobs: Lessons from History

How will the job market evolve in our 21st century digital economy?  What can we learn from history that might help us make such predictions?  While there’s no guarantee that historical patterns will continue to apply going forward, they might well be our most important guides as we peer into an otherwise unpredictable future.

Fears that machines will put humans out of work are not new.  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 anxieties continued to resurface in the 20th century, right along with advances in technology.  In a 1930 essay, English economist John Maynard Keynes wrote about the onset of “a new disease” which he named 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.”

Automation fears have understandably accelerated  in recent years, as our increasingly smart machines are now being applied to activities requiring intelligence and cognitive capabilities that not long ago were viewed as the exclusive domain of humans.  “Previous technological innovation has always delivered more long-run employment, not less.  But things can change,” said an Economist article from January, 2014.  “Nowadays, the majority of economists confidently wave such worries away…  Yet some now fear that a new era of automation enabled by ever more powerful and capable computers could work out differently.”

Automation angst, past and present, was the subject of three papers in the Summer issue of the Journal of Economic Perspectives.   I’d like to focus my discussion on one of the papers, - The History of Technological Anxiety and the Future of Economic Growth: Is This Time Different? - by economic professors Joel Mokyr, Chris Vickers, and Nicolas L. Ziebarth.  Their paper looked at both the history and the future of jobs from multiple points of view.

The Importance of Empathy in Our Services-Centric, People-Oriented Economy

A few days ago I read an excellent article in the Harvard Business Review, - Empathy Is Still Lacking in the Leaders Who Need It Most, - by Ernest Wilson, Dean of the Annenberg School of Communications and Journalism  at the University of Southern California (USC).  The article is based on the Third Space, a research project to better understand the key competencies companies are looking for, and whether these talent requirements are being adequately addressed by universities.

The study conducted face-to-face, in-depth conversations with dozens of senior executives across companies in a broad range of industries and consulted with a number of other academic institutions.  It gathered additional data through online surveys and partnered with Korn Ferry, - the world’s largest executive search firm, - which gave them access to data on almost 1,900 executives with a broad range of professional backgrounds. 

Their initial findings were published in a working paper, The one-trillion dollar global talent gap: What it is and what we can do about it.  Their research discovered that talent is the greatest competitive challenge companies face.  More specifically, beyond the traditional skills typically provided by engineering and business schools, companies need a new kind of talent that is currently undersupplied in the workforce.

Future leaders must be strong in quantitative, technical and business skills.  But these must be complemented with a unique set of attitudes, perspectives, experiences and other so called softer skills.  Good leaders need to be good strategic thinkers and must have strong social and communications skills.  Finding and retaining talented individuals with these capabilities is a challenge regardless of geography or industry.

Intervention Design: Overcoming Stiff Resistance to a New, Disruptive Innovation

The September issue of the Harvard Business Review features a spotlight on The Evolution of Design Thinking.  With four articles on the subject, HBR’s overriding message is that design is no longer just for physical products, being increasingly applied to customer experiences, innovation, business strategy, and complex problem solving. 

Last week I discussed this expanded view of design thinking based on one of the articles, - Design Thinking Comes of Age.  I now want to turn my attention to a second article in the HBR issue, Design for Action, which applies design thinking not to the actual artifact being designed, - whether product, service, business strategy, or complex system, - but to a very different kind of problem: the introduction of the designed artifact into the world.

When first introduced, disruptive innovations are likely to encounter stiff resistance, both within one’s own organization and in the marketplace, - otherwise we wouldn’t call them disruptive.  The article argues that we should apply design thinking to the launch of the disruptive innovation itself - a process they call intervention design. 

Design for Action was co-written by Tim Brown and Roger Martin.  Tim Brown is the CEO of IDEO, - the firm most associated with this more general view of design.  Roger Martin is in the faculty of the Rotman School of Management at the University of Toronto, where he served as Dean from 1998 to 2013.  He’s a strategic advisor to CEOs around the world and the author of a number of books.

The Evolution of Design Thinking

Design Thinking is the featured topic in the September issue of the Harvard Business Review with four articles on the subject.  “It’s no longer just for products.  Executives are using this approach to devise strategy and manage change,” reads the tagline in its cover.

The application of design thinking beyond products, - in innovation, problem solving and business strategy, - 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 pushing the boundaries of industrial design.  Stanford’s Institute of Design, aka the d.school, was founded a dozen years ago.  “But many companies still aren’t sure how it can improve their business,” notes Adi Ignatius, HBR’s editor-in-chief.

It’s not surprising that many companies don’t understand what is meant by design thinking, let alone its potential value to their business.  It’s much easier to appreciate the role of design when it comes to physical objects: cars, bridges, buildings, dresses, shoes, jewelry, smartphones, laptops, and so on.  But, it’s considerably harder to appreciate its importance when it comes to more abstract entities like systems, services, information and organizations.  Their very nature is vague.  You can’t touch them.  Yet, they account for the bulk of the growing complexity in our daily lives.

Capitalism and Social Issues in the 21st Century

A recent NY Times article, The Sunny Side of Greed by Op-Ed columnist Frank Bruni, argues that corporations may well now be among the strongest socially progressive forces in the country.  In issue after issue, - e.g., marriage equality, the confederate flag,  immigration reform,  - the business community has supported what we generally think of as the more socially progressive position. 

“Are these companies acting in their own interests?,” asks Bruni. “Absolutely.  They’re trying to make sure that laws and local customs don’t prevent them from attracting and retaining the best work force.  They’re burnishing their brands in a manner that they hope will endear them to customers.  But those efforts, coupled with whatever genuine altruism and civic obligation some corporate leaders feel, have produced compelling recent examples of companies showing greater sensitivity to diversity, social justice and the changing tides of public sentiment than lawmakers often manage to.” 

While our politicians are paralyzed by ideological arguments and partisan bickering, corporations seem to have little trouble embracing the more pragmatic positions that seem to better reflect the overall mood of the country on social issues like immigration and same-sex marriage.  The reason isn’t all that difficult to understand.  Many politicians must respond to the wishes of a few big donors and of small, single-issue interest groups in their districts.  But companies, especially those with national and global brands, must be responsive to a much larger, diverse constituency, namely their customers.

Realizing the Potential of the Digital Economy

A few weeks ago I attended the 12th annual Brookings Blum Roundtable on Global Poverty.  Organized by the Brookings Institution, the Blum Roundtable brings together policy and technical experts from government, academia, business, investors and NGOs from all over the world.  This year’s event, - Disrupting Development with Digital Technologies, - explored the impact of the digital economy on the ways business and development organizations now engage with emerging and developing countries.

In a pre-Roundtable blog, Kemal Derviş, - Brookings VP, Global Economy and Development, - identified three major trends with the potential to redefine global development over the next 10 years: the growing adoption of digital payments serving people everywhere with near-frictionless transactions; the spread of Internet connectivity and digital literacy; and the harnessing of data to better serve the poor and to generate new knowledge.

 Discussions were organized around six different sessions over three days.  Each session looked at the impact of digital technologies on economic development through a different lens, including electronic payments, access to information and the future of work.  Prior to the Roundtable, Brookings commissioned a policy brief for each session to help set the stage for the ensuing presentations and discussions.

The Digital Evolution Index

Last year, the Fletcher School of Law and Diplomacy at Tufts University published Digital Planet: Readying for the Rise of the e-Consumer.  The report, - based on a research study by the Fletcher School in collaboration with MasterCard^*, - explores the economic transformations taking place around the world as countries continue their evolution toward the 21st century digital age.

The report introduces the Digital Evolution Index, which was created to quantify the unique digital journey being pursued by each of 50 advanced and developing countries, to measure the rate of change of their digital evolution, and to provide information-based insights to companies, investors and governments.  The Index is based on four key underlying drivers: