Irving Wladawsky-Berger

Health and AI

The March 30, 2024 issue of The Economist includes a special  section on Health and AI, with six articles on the topic. “Artificial intelligence (AI) is generating excitement and hyperbole everywhere, but in the field of health care it has the potential to be transformational,” said the lead article, “The AI doctor will see you … eventually.” “In Europe analysts predict that deploying AI could save hundreds of thousands of lives each year; in America, they say, it could also save money, shaving $200bn-360bn from overall annual medical spending, now $4.5trn a year (or 17% of GDP).”

Healthcare is a system of coupled systems, encompassing medical and pharmaceutical research; the delivery of healthcare to patients by a variety of practitioners, including hospitals, physicians, nurses, and pharmacists; and the insurance companies and governments that pay for healthcare. It’s a highly regulated industry, which creates major barriers for the sort of innovative start-ups that have been the engine of transformation in other sectors. In advanced economies, a handful of companies, — e.g., Cerner, Epic, Athena, — support large healthcare providers with proprietary platforms that don’t interoperate with each other, making it difficult for smaller companies and startups to develop innovative AI tools and applications as has been the case in other industries.

There’s considerable hope that AI could help us better deal with the inherent complexity of the healthcare sector. “AI systems can enhance diagnostic accuracy and disease tracking, improve the prediction of patients’ outcomes and suggest better treatments,” notes The Economist. “It can also boost efficiency in hospitals and surgeries by taking on tasks such as medical transcription and monitoring patients, and by streamlining administration. It may already be speeding the time it takes for new drugs to reach clinical trials. New tools, including generative AI, could supercharge these abilities.”

However, “although AI has been used in health care for many years, integration has been slow and the results have often been mediocre.” Among the major reasons for the slow progress are the concerns about accuracy and trust necessary to protect patients’ safety. “Improving accuracy and reducing bias in AI tools requires them to be trained on large data sets that reflect patients’ full diversity.” But, while there’s lots of available health data, the data is highly fragmented making it difficult to use properly.

The Case for Open Healthcare Systems

As we’ve learned since the advent of the Industrial Revolution, major technological advances have the potential to radically transform a whole industry, but realizing that potential generally requires large intangible investments and a fundamental rethinking the industry being transformed. So, it’s not surprising that there’s much hope and excitement that the advent of AI as a major 21st century technological advance might, over time, help to radically transform our highly complex and expensive healthcare industry. 

Healthcare is a system of coupled systems, encompassing medical and pharmaceutical research; the delivery of healthcare to patients by a variety of practitioners, including hospitals, physicians, nurses, and pharmacists; and the insurance companies and governments that pay for healthcare. Healthcare costs have continued to rise across the world, especially in the US. Total healthcare spending in 2023 was approximately $4.7 trillion, accounting for 18% of US GDP, and is projected to grow at an average of 5.5% per year to over $7 trillion in 2031, roughly 20% of US GDP.

The potential evolution of healthcare brings to mind my personal experience in the information technology (IT) industry for the past 50 years.

The Promise of Digital Health in the 21st Century

In 2021 the Linux Foundation (LF) announced the formation of Linux Foundation Research, a new organization to broaden the understanding of open source ecosystems and to explore opportunities for new open source initiatives. Given my long involvement with Linux, the Linux Foundation and open source communities in general, I was invited to become a member of the newly created LF Research Advisory Board (RAB).

At a September, 2023 meeting of the Advisory Board, we discussed that one of the few industry sectors in which the LF does not have projects is healthcare, despite its size and importance around the world. The LF had launched healthcare initiatives in the past, but they all eventually failed. At that meeting, LF Research launched a study to understand what we should be doing in the healthcare sector. I’m involved in the study, and for the past several months, I’ve been learning about the opportunities of digital technologies in healthcare systems by reading a number of articles and talking to key experts.

“The Promise of Digital Health: Then, Now, and the Future,” a discussion paper published in June of 2022 by the US National Academy of Medicine is one of the articles that I found most instructive. The paper is based on the contributions of 25 member of the National Academy of Medicine (NAM), including two of the experts I’ve recently spoken with, John Halamka and Peter Lee.

Taking the Pulse of AI in Medicine

“AI explodes: Taking the Pulse of artificial intelligence in medicine,” is the title of the latest issue of the Stanford Medicine Magazine. The issue includes a number of articles that explore the promise of AI in medicine, ranging from What’s driving this tumor, — which discusses the efforts to stymie breast cancer through gene testing and AI, — to Adding ethics to the mix when developing health care AI, — which deals with the potential hazards posed by algorithms developed by AI experts with no formal training in the ethical standards for treating patients.

“Imagine a future where your doctor has an AI medical assistant by their side – distilling, in seconds, a world’s worth of medical research into a personalized treatment plan for you,” wrote Dr. Lloyd Minor, Dean of the Stanford University School of Medicine in the issue’s Letter from the Dean. “What if, at the click of a button, a researcher could design a custom molecule with the potential to treat a previously untreatable disease? With artificial intelligence’s rapid emergence, we are barreling toward this reality. Academic medical centers around the world, including Stanford Medicine, have begun investigating how AI, including large language models such as ChatGPT, can help us improve patient care, reduce clinician workload, better understand complex biological systems and accelerate drug discovery.”

As I discussed in a recent blog, “The Promise of Generative AI in Healthcare,” there’s a lot of excitement that AI might help us address our highly complex healthcare industry. Healthcare is a system of coupled systems, encompassing medical and pharmaceutical research; the delivery of healthcare to patients by a variety of practitioners, including hospitals, physicians, nurses, and pharmacists; and the insurance companies and governments that pay for healthcare.

According to Wikipedia, the healthcare industry comprises over 10% of the GDP of most developed countries. “The per capita expenditure on health and pharmaceuticals in OECD countries has steadily grown from a couple of hundred in the 1970s to an average of US$4'000 per year in current purchasing power parities.” In 2022, US healthcare spending “grew 4.1% to $4.5 trillion in 2022, or $13,493 per person, and accounted for 17.3% of Gross Domestic Product (GDP).”

In addition to its inherent complexity, healthcare has several attributes that make the successful deployment of new technologies significantly more challenging than in other industries. HIPPA, for example, protects the privacy of individuals in the US, but it also restricts the data sharing that’s essential to achieving many of the benefits of generative AI. And because the stakes in healthcare are too high to tolerate flaws that could harm patients, it’s harder to introduce new technologies and applications compared to most other industries.

The Promise of Generative AI in Healthcare

“Since they became publicly available in late 2022, generative artificial intelligence (genAI) tools such as ChatGPT have elicited enormous enthusiasm, as well as concern, in all sectors of the economy,” said “Will Generative Artificial Intelligence Deliver on Its Promise in Health Care?,” a recent article in the Journal of the American Medical Association (JAMA) by Robert Wachter, — professor and chairman of the Department of Medicine at the University of California, San Francisco (UCSF), and Erik Brynjolfsson, — professor and director of the Digital Economy Lab at Stanford University.

“But the potential impact of genAI in health care seems particularly noteworthy. In a field in which an estimated 30% of the $4.3 trillion spent each year in the US adds little to no value, in which many tens of thousands of people die yearly from preventable mistakes, and in which access to care is fragmented and inequities are commonplace, it is natural to be enthusiastic about the potential for genAI to improve quality, efficiency, equity, and patient experience.”

A few weeks ago I posted an entry in my blog on “AI and the Future of Healthcare Systems,” in which I discussed the huge challenges posed by the inherent complexity of the healthcare sector of the economy. Healthcare is a system of coupled systems, comprised of medical and pharmaceutical research; the delivery of healthcare to patients by a variety of practitioners, including hospitals, physicians, nurses, and pharmacists; and the insurance companies and governments that pay for healthcare. The convoluted interactions of these various  domains, — each of which is quite large and complex in its own right, — is one of the main reasons why healthcare systems are so incredibly complex.

Given the central role of data in AI, electronic health records (EHRs) play a critical role in the development of AI systems capable of dealing with the complex real-world challenges in the healthcare industry. As explained by the Centers for Medicare & Medicaid Services (CMS): “An Electronic Health Record (EHR) is an electronic version of a patients medical history, that is maintained by the provider over time, and may include all of the key administrative clinical data relevant to that persons care under a particular provider, including demographics, progress notes, problems, medications, vital signs, past medical history, immunizations, laboratory data and radiology reports.”

AI and the Future of Healthcare Systems

In 2009 I participated in a panel at an MIT Symposium on complex systems where I gave a talk on complex social organizations. The panel included talks on financial, energy, and healthcare systems by three eminent leaders in their fields. I was particularly impressed by the talk given by Denis Cortese, who at the time was the president and CEO of the Mayo Clinic, and who after retiring in 2010, joined Arizona State University as Foundation Professor and director of its Center for Healthcare Delivery and Policy.

Dr. Cortese explained that healthcare is a system of coupled systems. Healthcare is composed of three interconnected domains: knowledge, — the domain of medical research, where new ideas, inventions and medical approaches are developed; care delivery, — the domain of physicians and hospitals where patients are treated; and payers, — the domain of insurance and governments that pay for the delivery of healthcare. Each of these domains is quite large and complex in its own right, but their convoluted interactions is one of the main reasons why healthcare systems are so incredibly complex.

Could AI now help us better deal with the inherent complexity of healthcare systems? After decades of promises and hype, AI has finally become the defining technology of our era. Over the past two decades, the necessary ingredients have come together to propel AI beyond universities and research labs into the broader marketplace: powerful, inexpensive computer technologies; advanced algorithms and models; and huge amounts of all kinds data. Data has been the key element in the major AI advances over the past 20 years, including big data and data science in the 2000s, machine and deep learning in the 2010s, and Large Language Models (LLMs) and generative AI in the past few years.

In trying to understand the potential use of AI in healthcare systems, I came across the work of John Halamka. Dr. Halamka is president of the Mayo Clinic Platform, an organization that aims to drive innovations in diagnosis, treatment, and operational improvements in healthcare systems. He’s also a prolific writer, having authored a number of articles and books on the subject.

Jobs Expected to Grow and Jobs Expected to Decline Through 2030

“The COVID-19 pandemic disrupted labor markets globally during 2020,” said a February 2021 McKinsey report on “The future of work after COVID-19.” “The short-term consequences were sudden and often severe: Millions of people were furloughed or lost jobs, and others rapidly adjusted to working from home as offices closed. Many other workers were deemed essential and continued to work in hospitals and grocery stores, on garbage trucks and in warehouses, yet under new protocols to reduce the spread of the novel coronavirus.”

Two and a half years later, a recently published report by the McKinsey Global Institute (MGI), “Generative AI and the future of work in America,” paints a radically different picture: “the US job market has come roaring back from its sudden drop. The nature of work has changed as many workers have stuck with remote or hybrid models and employers have sped up their adoption of automation technologies. More recently, the accelerated development of generative AI, with its advanced natural language capabilities, has extended the possibilities for automation to a much wider set of occupations.”

The US labor market is now undergoing a rapid evolution in the way people work and the work people do. “Some 8.6 million occupational shifts took place from 2019 through 2022. Now even more change is in store. We expect an additional 12 million occupational shifts by 2030.”

The Importance of Open Source Digital Wallets to the Future of the Internet

On September 13, the Linux Foundation (LF) announced its intent to form the Open Wallet Foundation (OWF) at its Open Source Summit Europe in Dublin. The OWF aims to develop open source software, key building blocks, and best practices that anyone can use as a starting point to build multi-platform, highly secure, privacy-protecting digital wallets. In addition, the OWF will advocate for the wide adoption of open source wallets that can be used to support a wide variety of applications, from payments to digital identities.

The LF was originally founded in 2000 as the Open Source Development Labs to help set the standards for the Linux operating system and support its continued development and commercial adoption. It grew over the years and assumed its current name, Linux Foundation, in 2007. Over the past decade, the LF has undergone a major expansion beyond its original Linux mission. It now has over 1,260 company members and supports hundreds of open source projects. Some of the projects are focused on technology horizontals, - e.g., AI, blockchain, security, cloud, - and others on industry verticals, including energy, automative, government, and health care.

Let me attempt to explain the importance of this announcement by addressing three key questions: what is a digital wallet?; what are digital identities?; and why do we need standard-based, open source digital wallets?

Getting Ready for the 100-Year Life

“In the United States, demographers predict that as many as half of today’s 5-year-olds can expect to live to the age of 100,” said The New Map of Life, a recent report from the Stanford Center on Longevity. The   cross-disciplinary Stanford Center was founded in 2007 to conduct research on the key issues associated with increased longevity, - from cognitive health to physical well-being and financial security, - with the aim to make long lives healthy and rewarding.

While the 100-year life may be here, we’re not ready. “By the middle of this century, this once unattainable milestone may become the norm for newborns, continuing a remarkable trend that saw human life expectancies double between 1900 and 2000, and still rising in this century, despite the grievous toll of the Covid-19 pandemic,” notes the report. “Longevity is one of the greatest achievements in human history, brought about by reductions in infant mortality, advances in sanitation and medicine, public education, and rising standards of living. Yet the change came about so quickly that the social institutions, economic policies, and social norms that evolved when people lived for half as long are no longer up to the task.”

According to the Stanford Center, there’s a clear distinction between aging and longevity. Aging is the biological process of getting older - the accumulation of changes in a human being over time. Longevity is “the measure of long life,” - the ways to enhance the quality of a long life “so that people experience a sense of belonging, purpose, and worth at all ages and stages.”

A Pandemic Is Fundamentally an Information Problem

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

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

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

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

A New Contract with the Middle Class

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

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

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

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

The Public Face of Science - Implications of the Covid Crisis

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

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

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

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

Reconnecting Society and Reopening the Economy

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

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

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

How Will Covid-19 Transform Urban Life?

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

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

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

An Increasingly Digital “New Normal”

About a dozen years ago, I attended a conference where I was interviewed on stage by then WSJ technology columnist Walter Mossberg.  He started out by asking me about IBM’s near-death experience in the early 1990s, and the subsequent technical and cultural transformation that made it possible for IBM to reinvent itself and survive, while many other IT companies didn’t make it.  In particular, we discussed whether a successful company transformation must be preceded by the kind of major crisis IBM went through.  When it comes to humans, the ancient Greeks certainly thought so, as reflected in their tragedies.

Transformative change is very difficult for established companies.  Over the years, they’ve amassed valuable assets and extensive organizations.  Already consumed with managing their existing operations, they may look at transformative change as more of a threat or distraction than an opportunity, - unless they’re in dire straits and have no other choice, as was the case with IBM.

A serious crisis is an opportunity for companies to focus on the actions needed to survive in a fast changing environment.  As Rahm Emanuel famously said in a 2008 interview with the WSJ: “You never want a serious crisis to go to waste.”  In that spirit, how should companies take advantage of the Covid-19 crisis, - arguably the biggest shock the world has experienced since WWII, - to accelerate their journey toward what most everyone agrees will be an increasingly digital future?

Blockchain and Public Health Solutions

The Blockchain Research Institute (BRI) is a global think tank dedicated to the strategic implications of blockchain technologies to business, government and society.  On March 26, I participated in a virtual roundtable convened by the BRI to discuss the potential use of blockchain technologies for public health solutions.  The roundtable’s findings and recommendations were released in early April in Blockchain Solutions in Pandemics: A Call for Innovation and Transformation in Public Health.

The report identified five key areas where blockchain could be deployed to fight Covid-19 as well as future pandemics: identity, health records and shared data; just-in-time supply chains; sustaining the economy; a rapid response registry for medical professionals; and incentives models to reward responsible behavior.  In each of these areas, the report presented uses cases where blockchain is already being deployed, and recommended a number of blockchain related public health measures that will help better prepare for future pandemics.  Given the broad scope of the report, I will focus my attention on one area in particular: identity, health records and shared data.

Measuring the Effectiveness of Social Distancing Policies

One of the most interesting projects in the MIT Connection Science group I’m affiliated with is The Atlas of Inequality.  The project, - led by visiting professor Esteban Moro and professor Alex ‘Sandy’ Pentland - uses aggregated anonymous geolocation data from digital devices to estimate where different groups of people in US cities spend their time.  Over time, the project will be expanded to cities around the world.  The data show the significant income inequality among people in those cities, not just by neighborhoods as you’d expect, but also in the restaurants, stores and other places beyond their neighborhoods which they visit every day.

A couple of weeks ago, the Atlas research group started to apply their geolocation data and methods to analyze the effectiveness of the social distancing policies adopted in the New York metropolitan area in response to the Covid-19 pandemic.  These policies include school closures, bans on non-essential gatherings, limiting restaurants to take-out orders, and strict stay-in-place measures.   There’s no way to empirically measure the impact of these social distancing measures in real time on the spread of Covid-19.  You can only measure their impact retrospectively, or simulate what might happen in the future based on past data.

However, you can empirically address a key set of important question: how have these social distancing policies changed mobility and social behavior?; how does social distancing behavior vary across the New York metropolitan area?; how does the behavior vary across the variety of demographic groups in the NY metro area?; and overall, how well are people following these social distance measures?

The Evolution of the Social Contract in the 21st Century

“Life has changed substantially for individuals in advanced economies in the first two decades of the 21st century,” notes The social contract in the 21st century, a new report by the McKinsey Global Institute (MGI).  “In many ways, changes for individuals have been for the better, including new opportunities and overall economic growth…  Yet, the relatively positive perspective on the state of the economy, based on GDP and job growth indicators, needs to be complemented with a fuller assessment of the economic outcomes for individuals as workers, consumers, and savers.”

The report takes an in-depth look at the changing economic outcomes for individuals between 2000 and 2018 in 22 advanced countries, - 16 European ones, Japan and South Korea, Australia and New Zealand, and Canada and the US.  In aggregate, these countries constitute 57% of global GDP. 

The report closely examines the evolution of the social contract, that is, “the arrangements and expectations, often implicit, that govern the exchanges between individuals and institutions.”  Its overriding finding is that the social contract has changed considerably in the 21st century, with individuals having to assume greater responsibility for their economic outcomes.  Opportunities for work and employment rates have risen significantly, but outcomes vary considerably across socioeconomic groups and geographies.  While many have benefited from this evolution, those in the bottom 60% of the income distribution are facing significant economic challenges, leading to an uncertain future and a general loss of trust in institutions.

The report analyzes the evolution of the social contract by looking at the changing outcomes for individuals as workers, as consumers, and as savers.  Let me summarize the findings in each of these three categories.

Despite All the Bad News that Surround Us… Is the World Actually Getting Better?

The World is Getting Quietly, Relentlessly Better is the title of a recent WSJ article by its chief economics commentator Greg Ip.  “If you spent 2018 mainlining misery about global warming, inequality, toxic politics or other anxieties, I’m here to break your addiction with some good news: The world got better last year, and it is going to get even better this year,” writes Ip in his opening paragraph.  “Poverty around the world is plummeting; half the world is now middle class; and illiteracy, disease and deadly violence are receding.  These things don’t make headlines because they are gradual, relentless and unsurprising.”

Ip’s article is mostly based on data insights from Our World in Data, a comprehensive website that quantifies the evolution of our global living conditions over the past few centuries.  Our World in Data (OWID) is an initiative of the Oxford Martin Programme on Global Development, led by economist Max Roser at the University of Oxford.

OWID analyzes longitudinal data on how the world has been changing over decades and centuries, as well as explaining the causes and consequences of those changes in its accompanying articles. It makes extensive use of visual aids, including interactive graphs and maps, to present its analyses and insights.  Its content is organized into 15 main sections:  population, health, food, energy, environment, technology, growth & inequality, work & life, public sector, global connections, war & peace, politics, violence & rights, education, media and culture, -  each of which further includes a number of subsections.

Let me summarize just a few of the key trends in the OWID website.

Will Humans Be Better Off in an Increasingly AI-Based Future?

After decades of promise and hype, artificial intelligence is finally becoming one of the most important technologies of our era.  As AI continues to both spread and advance, will it enhance human capacities or will it lessen human autonomy and agency?  By 2030, will most people be better or worse off than they’re today?

To shed light on these very important questions, the Pew Research Center canvassed AI experts this past summer, including technologists developers, and business and policy leaders.  It received almost 1,000 responses, which formed the basis for its recently published report Artificial Intelligence and the Future of Humans.

Overall, 63% of respondents were optimistic, predicting that most individuals will mostly be better off, while 37% thought otherwise.  But optimistic or not, most experts expressed concerns about the long-term impact of AI on “the essential elements of being human.”

The survey further asked the experts to explain their hopes and fears, to sketch out how they envision human-machine interactions over the coming decade, and what actions should be taken to assure the best possible future. Many answered, and their detailed comments are organized into the report’s three main sections: concerns; suggested solutions; and expectations for the future.  Let me briefly discuss the key points in each section.

The World Bank’s Human Capital Index

Last week I wrote about a recently published World Bank report, The Changing Nature of Work.  The report highlights the increasing importance of investing in human capital by both the public and private sectors.  All around the world, the demand for workers who are good at complex problem-solving, interactions with clients and colleagues, and able to adapt to new tools and technologies is rising, while the demand for less advanced skills that can be replaced by technology is declining.  Neglecting investments in human capital, it warned, can dramatically weaken a country’s competitiveness.

“The world is healthier and more educated than ever…,” notes the World Bank in a companion report, The Human Capital Project.  “But a large and unfinished agenda remains.  Life expectancy in the developing world still lags far behind that of rich countries…  Worldwide, more than 260 million children and youth are not in school. Meanwhile, nearly 60 percent of primary school children in developing countries fail to achieve minimum proficiency in learning.”

Why should countries invest in human capital?  Can early health care and education prepare children to succeed and prosper as adults in a rapidly changing world?  What are the barriers to nurturing human capital and how can countries overcome them?  To address these important questions, the World Bank introduced the Human Capital Index (HCI).  The HCI is designed to quantify the amount of human capital that a child born today can expect to attain by age 18 given the prevailing health and education conditions in the country where the child lives.  It will be updated periodically and refined as data measures improve.  This video nicely explains the HCI and what it measures. 

Blockchain Beyond the Hype

A recent issue of The Economist included a special report on cryptocurrencies and blockchains.  The Economist’s overall conclusion was that “Bitcoin has been a failure as a means of payment, but thrilling for speculators.”  Its assessment of blockchain was somewhat more positive.  “For blockchains, the jury is still out,… For all the technology’s potential, though, most attempts to use it remain tentative,…  The advantages of blockchains are often oversold.” 

In 2016, blockchain made the list of the World Economic Forum’s Top Ten Emerging Technologies.  That same year, blockchain also made its first appearance in Gartner’s yearly hype cycles.  Even The Economist has been guilty of overselling when it featured blockchain in the cover of its October 31, 2015 issue with the tag line “The Trust Machine: How the technology behind Bitcoin could change the world.” 

Is there too much hype surrounding blockchain?  Absolutely,… but not surprising.  All potentially transformative technologies are oversold in their early stages.  Remember the dot-com bubble of the late 1990s.  Blockchain is still in its early phases of experimentation and adoption.  Much work remains to be done on standards, platforms, interoperability, applications and governance. 

But, does blockchain have the potential to become a truly transformative technology over time?  Yes, said McKinsey in a recent article on the strategic value of blockchain beyond the hype.  The article starts out by acknowledging that all the hype around blockchain makes it difficult to nail down not just blockchain's long term strategic value, but also what it actually is and what it isn’t in the present. To make sure everyone is on the same page, the article first recaps what it calls “the nuts and bolts of blockchain.”  Let me start by summarizing blockchain’s nuts and bolts.

The Economic Value of Artificial Intelligence

 PwC recently released a report on the potential economic value of AI to different regions and industry sectors around the world.  The report defined AI, “as a collective term for computer systems that can sense their environment, think, learn, and take action in response to what they’re sensing and their objectives.”  By this broad definition, AI includes the automation of physical and cognitive tasks; assisting people to perform tasks better and faster; helping humans make better decisions; and automating decision making with no human intervention.

The report’s overriding finding is that AI is the biggest commercial opportunity for companies, industries and nations over the next few decades.  PwC estimates that AI advances will increase global GDP by up to 14% between now and 2030, the equivalent of an additional $15.7 trillion contribution to the world’s economy.

Around $6.6 trillion of the expected GDP growth will come from productivity gains, especially in the near term.  These include the continued automation of routine tasks, and the development of increasingly sophisticated tools to augment human capabilities.  Companies that are slow to adopt these AI-based productivity improvements will find themselves at a serious competitive disadvantage.

But, over time, increased consumer demand for AI-enhanced offerings will overtake productivity gains and result in an additional $9.1 trillion of GDP growth by 2030.  Moreover,  network effects, - that is, the more data and better insights companies are able to gather, the more appealing the products and services they’ll be able to develop, - will further increase consumer demand.  AI front-runners will gain an enormous competitive advantage through their ability to leverage this rich supply of customer data to shape product developments and business models, making it harder for slower moving competitors to catch up. 

The Impact of AI on R&D and Innovation

For the past couple of centuries, general-purpose technologies (GPTs) have been the key drivers of productivity and economic growth, - thanks to their rapid improvements in price and performance, pervasive applications, and ability to spur complementary innovations across a wide variety of industries.  The steam engine, electricity and the internal combustion engine are prominent examples of GPTs in the 18th and 19th century.  More recently, semiconductors, computers and the Internet have led to the digital revolution of the past several decades.

Beyond innovations in existing sectors, the rapidly improving price/performance of GPTs have led over time to the creation of whole new applications and industries.  For example, the steady declines in the price of electricity-generated power and the improvement in the efficiency of electric motors led to the radical transformation of manufacturing in the early part of the 20th century with the advent of the assembly line.  It also led to the creation of the consumer appliance industry, e.g., refrigerators, dishwashers, washing machines.  Similarly, as the semiconductor industry took off, it led to the historical transition from the industrial economy of the past two centuries to our ongoing digital economy.

How about artificial intelligence?  Beyond its use by leading edge technology companies, we’re still in the early stages of AI deployment.  It’s only been in the last few years that major advances in machine learning have taken AI from the lab to early adopters in the marketplace.  While considerable innovations and investments are required for its wider deployment, AI is likely to become one of the most important GPTs in the 21st century. 

Artificial Intelligence is Ready for Business; Are Businesses Ready for AI?

AI is now seemingly everywhere.  In the past few years, the necessary ingredients have come together to propel AI beyond the research labs into the marketplace: powerful, inexpensive computer technologies; advanced algorithms and models; and most important, oceans and oceans of data.

“Artificial intelligence is getting ready for business, but are businesses ready for AI?,” asks McKinsey in a recently published report - Artificial Intelligence: the Next Digital Frontier.  “AI adoption outside of the tech sector is at an early, often experimental stage,” is the report’s succinct answer.  “Few firms have deployed it at scale.”

The report is based on a survey of over 3,000 AI-aware C-level executives across 10 countries and 14 sectors.  Only 20 percent of respondents had adopted AI at scale in a core part of their business.  40 percent were partial adopters or experimenters, while another 40 percent were essentially contemplators.

AI encompasses a broad rage of technologies and application.  It’s often viewed as the leading edge of IT.  As soon as AI is successfully applied to a problem, the problem is no longer a part of AI.  The McKinsey report is focused on five technologies being increasingly deployed in business, that most everyone agrees are part of AI: robotics and autonomous vehicles, computer vision, language, virtual agents, and machine learning.

Digital Twin: Bringing the Physical and Digital Worlds Closer Together

A few weeks ago I first learned about a relatively new concept - Digital Twin.  A Digital Twin is essentially a computerized companion to a real-world entity, be it an industrial physical asset like a jet engine, an individual’s health profile, or a highly complex system like a city.  It’s a highly realistic, one-to-one digital model of each such specific physical entity.

Digital Twin helps bring the physical and digital worlds closer to each other.  It’s intertwined with and complementary to the Internet of Things (IoT).  The huge amounts of data now collected by IoT sensors on physical objects, personal devices and smart systems make it possible to represent their near real-time status in their Digital Twin alter-ego.

“The myriad possibilities that arise from the ability to monitor and control things in the physical world electronically have inspired a surge of innovation and enthusiasm,” said a 2015 McKinsey report on the Internet of Things.  Experts estimate that the number of connected things or devices will reach 50 billion by 2020, growing to 100s of billions in the decades ahead.  The economic potential of the smart solutions this makes possible is enormous, possibly reaching several trillion dollars within a decade.

The Promise and Challenges of Health Analytics

On February 24 I attended a workshop in MIT on the Future of Health Analytics.  The event was sponsored by MIT Connection Science, a recently organized research initiative aimed at leveraging data science to quantify and analyze human behaviors, and to leverage the new insights thus obtained in key societal applications, including healthcare, transportation and finance.  Connection Science, - with which I’m affiliated as a Fellow, - was founded by Media Lab professor Alex “Sandy” Pentland.  He’s the author of several books, including the recently published Social Physics: How Good Ideas Spread.  

I’ve worked with Pentland for the past several years, and have previously written about his research on Reinventing Society in the Wake of Big Data, as well as his work with the World Economic Forum and others on the creation of trust frameworks for the sharing and protection of personal data.  In his opening remarks at the workshop, Pentland talked about Big Data and Health.  The little data breadcrumbs that we leave behind as we move around in the world can now be reality mined to help us better understand our behaviors and thus improve our lives and health.  He discussed several applications of big data to health, based on research at his MIT Human Dynamics Lab, as well as startups he’s involved in.

Following Pentland, Dr. Dennis Ausiello talked about Quantitative Human Phenotyping and the opportunities it offers to transform the practice of medicine.  Ausiello is professor of medicine at the Harvard Medical School, Chief Emeritus of Medicine at Massachusetts General Hospital (MGH), and director and co-founder of the Center for Assessment Technology and Continuous Health (CATCH), a joint MGH-MIT initiative aimed at finding new ways of measuring the human condition, i.e., phenotypes.

The Gulf Between Planning and Reality

It’s way too early to know what really happened with the botched launch of Healthcare.Gov.  We don’t know how it will all play in years to come and what its impact will be on the evolution of the Alternative Care Act (ACA), on election results over the next few years, or on President Obama’s legacy.  Depending on how it all turns out over time, this will be just a chapter in future books on the history of the ACA and the Obama administration, or the subject of major books and investigative reports.   

Most everyone who’s been involved with the development of complex IT systems knows how wrong things can sometimes go.  So, when serious problems do happen, we are eager to learn the lessons that might help us avoid similar problems in the future.  It’s quite possible that Healthcare.gov and the ACA’s overall IT system are such complex outliers, - technically, organizationally and politically, - that any lessons learned might apply to few other projects.  But, given the increasing complexity of private and public sector IT systems, the lessons are worth thinking about.

I like the way Clay Shirky, - NYU faculty member as well as author and consultant, - framed the problem in a very interesting blog, - Healthcare.gov and the Gulf Between Planning and Reality.  He writes about the gulf between those charged with planning the overall rollout of the ACA and health care exchanges and the realities of trying to get such a complex system designed, built and launched in a short amount of time.  It’s essentially a tale of failure is not an option versus the messy world of highly complex IT systems.  While the blog is focused on the launch of Healthcare.gov, it can also be read as a more general discussion of the kinds of problems often encountered with highly, complex IT-based projects when a management decision to win a deal at all costs comes back to haunt the implementation of the project.

Some Thoughts on the Affordable Care Act

My friend and former IBM colleague John Patrick posted a very good entry in his blog on the Affordable Care Act (ACA), aka Obamacare.  As we all know, the ACA has had a rough start.  In his entry, John asks two basic questions: do we need the ACA?; and, should it be repealed?

John has always been a pioneer in embracing new technologies.  He understood the power of the Internet very early on and worked tirelessly to get IBM involved.  Together, we organized IBM’s Internet Division in the mid-1990s and continued to work closely until his retirement from IBM in 2001.  He was one of the first people I knew who had a blog, - which is still going strong after all these years, - and was a big influence in my decision to start my own blog in May of 2005. 

Do we need the ACA or something like it?  John points out that “The United States is the only developed country in the world that does not have universal healthcare, meaning that all citizens have healthcare insurance.”  Different countries have developed universal health care along different models.  The UK has a single payer system.  Germany’s is based on over 200 payers.  Canada’s is operated by its 13 provinces.

Are Markets Efficient, Irrational, or Both?

The 2013 Nobel Prize in Economic Sciences was awarded last month to professors Eugene Fama and Lars Peter Hansen from the University of Chicago, and Robert Schiller  from Yale University “for their empirical analysis of asset prices.”  While there is general agreement that these three economists are most deserving of the prize, quite a few were also surprised that Fama and Schiller shared the award because they hold such different views of their discipline.

Professor Fama is the father of the efficient market theory, which says that prices in financial markets reflect all available information.  He has long maintained that he does not understand what people mean by financial bubbles and is thus not sure if they actually exist.  He is associated with the Chicago School of Economics, which believes that people generally make rational choices about their financial interests. 

Professor Schiller, one of the fathers of behavioral economics, holds very different views.  He believes that individual and crowd psychology strongly influence the behavior of markets and that social and emotional factors have a strong influence on the economic decisions made by individuals and institutions.  In 2000 Schiller published Irrational Exuberance, a book about the dot-com bubble, which he updated in 2005 to cover the housing bubble.

Cognitive Systems and Big-Data-driven Applications

In the first week of October I participated in a Cognitive Systems Colloquium hosted by IBM at its Thomas J. Watson Research Center.  IBM defines cognitive systems as “a category of technologies that uses natural language processing and machine learning to enable people and machines to interact more naturally to extend and magnify human expertise and cognition.  These systems will learn and interact to provide expert assistance to scientists, engineers, lawyers, and other professionals in a fraction of the time it now takes.”  

The need for such systems is a result of the explosive growth of data all around us.  Not only are we now able to collect huge amounts of real-time data about people, places and things, but far greater amounts can be derived from the original data through feature extraction and contextual analysis.  One of the key lessons from Watson, - IBM’s question-answering system which in 2011 won the Jeopardy! Challenge against the two best human Jeopardy! players, -  was that the very process of analyzing data increases the amount of data by orders of magnitude.  

This is challenging our ability to store and analyze all that data.  The new generation of cognitive systems will require innovation breakthroughs at every layer of our IT systems, including  technology components, system architectures, software platforms, programming environment and the interfaces between machines and humans.

Smart Homes - Building for America's Bravest

In the Fall of 2007, I taught a graduate course in MIT - Technology-based Business Transformation.  The course focused on the major challenges that a business must deal with to successfully bring a disruptive innovation to market, including technical and market strategies as well as organizational and cultural issues.  The course drew heavily on my concrete experiences at IBM, especially what I learned as general manager of the Internet Division in the second half of the 1990s.

Within the limits of a one-semester course, I wanted to give the students a fairly comprehensive picture of what it takes to bring a disruptive innovation to market, including the key role played by marketing and communications.  I wanted the class to hear from a top professional in the field what brand and strategic marketing are all about, so I invited Chris Wall, - Vice Chairman of Ogilvy and Mather, one of the top marketing and advertising agencies in the world, - to be a guest lecturer in the class.  For a number of years, I worked closely with Chris and his O&M colleagues in the development of marketing campaigns for IBM initiatives I was leading.  These included the award-winning e-business campaign launched in 1997, - which explained what we meant by e-business in a series of really clever 30 second vignettes, - and the Linux campaign a few years later which included this incredible ad. 

In his excellent class seminar, Chris explained the difference between trying to establish a brand through mindless jingles or paternalistic assertions that no one believes, versus engaging your audience in a conversation about the future.  To engage in such a conversation, you need to essentially tell a story about your aspirations for the brand and how these aspirations are driving your strategy.  And, the more powerful and complex the messages you are trying to convey, the more important it is to do so by telling a compelling, emotionally resonant and simple story.

Chris and I became friends, and over the years he has shared with me some of the marketing campaigns he’s worked on that he is particularly proud of.  A couple of weeks ago he sent me an e-mail telling me about his latest project with a small foundation, Building for America’s Bravest.  Chris and a few of his Ogilvy colleagues created the integrated marketing campaign for the foundation, including its website, ourbravest.org which has just gone live, and includes a few short video clips along with pictures and stories.

I was frankly left speechless by ourbravest.org.  Compelling and emotionally resonant does not begin to do justice to its content.  The video clips and pictures truly grab you by the throat, or rather, by the heart.  I cannot possibly describe them in words, so please take a look and judge for yourself.

New Tools Beget Revolutions: Big Data and the 21st Century Information-based Society

On May 22 I attended the 2013 MIT Sloan CIO Symposium.  This year’s theme was The Transformational CIO: Architecting the Enterprise of the Future.  “The enterprise of the future will be very different from the one we know,” wrote the organizers in the event’s website.  “It will be complex, develop hitherto unforeseen forms, and will have to respond to unforeseen challenges.  All while the windows of opportunity and response will continue to shrink.  There will not only be the need to be agile and adapt to changes as they occur, but to be proactive in shaping the next generation enterprise to be ready for the future.” 

The Symposium included a number of talks and panels on the key issues facing CIOs in our post-digital world, that is, in an era when digital technologies permeate just about every nook and cranny of the business, and where every business is a digital business, the title of one of the talks at the event.  While a number of transformative technologies were discussed, big data was the most prominent.    

MIT professor Erik Brynjolfsson led an all-MIT academic panel of experts on The Reality of Big Data.  In a brief introductory talk, Brynjolfsson pointed out that throughout history new tools beget revolutions.  Scientific revolutions are launched when new tools make possible all kinds of new measurements and observations.  In 1676, for example, Antonie van Leeuwenhoek used a microscope, a relatively recent and rare tool, to discover the existence of microorganisms in a drop of water.  Thus was microbiology born, leading to major discoveries in biology, medicine, public health and food production in subsequent decades and centuries.

What Doesn't Kill Us Makes Us Stronger

Complex systems, whether natural or engineered, are composed of many parts.  But it’s not the mere number of components that makes them complex.  After all, stones are composed of huge numbers of molecules, yet we would not consider them complex.  A truly complex system consists of many different kinds of parts, intricate organizations and highly different structures at different levels of scale.  Humans, bacteria, advanced microprocessors, modern airplanes, global enterprises, healthcare organizations and  urban environments are all examples of complex systems exhibiting these massive, heterogeneous, intricate characteristics. 

What makes these systems so complex?  Whether they were designed by humans or evolved in nature, why aren’t they simpler?  What purpose does this complexity serve? 

A few years ago I heard a very interesting talk addressing these questions by Cal Tech professor John Doyle.  The talk was based on a paper, Complexity and Robustness, which he co-authored with professor Jean Carlson from UC Santa Barbara. 

According to Carlson and Doyle, you can find very simple biological organisms in nature, and you can design very simple objects.  The key ingredient you give up is not their basic functionality, but their robustness - that is, the ability to survive, for biological organisms, or to perform well, for engineered objects - under lots of different conditions, including the failures of individual components.  Robustness implies the ability to adapt and keep going in spite of a rapidly changing environment.

Complex Sociotechnical Systems: the Case for a New Field of Study

Digital technologies are enabling us to develop systems with huge numbers of interconnected components and sophisticated software that infuses them with seemingly unlimited capabilities.  They are penetrating just about every nook and cranny of the economy and of society in general.  And, they are profoundly changing the way all organizations operate, as well as our working and personal lives. 

We are increasingly able to pull all these capabilities together and develop sociotechnical systems, which combine the powerful, inexpensive and ubiquitous digital technologies with the people and organizations they are transforming.  But, we have much to learn on how to best design and operate these systems.  They generally exhibit a level of complexity that is often beyond our ability to understand and control.  Not only do they have to deal with the complexities associated with large scale hardware and software infrastructures, but with the even more complex issues involved in human and organizational behaviors. 

A few weeks ago, MIT professor Joseph Sussman addressed these issues in a lecture - Complex Sociotechnical Systems: The Case for a New Field of Study.  Sussman is Professor of Civil and Environmental Engineering and Engineering Systems and interim director of the MIT Engineering Systems Division. 

Complex sociotechnical systems are high-impact, difficult-to-understand, technology-intensive systems that have major societal, political and economic implications.  While this definition can rightfully apply to many of the systems we have been developing in the last few decades, their importance is on the rise now for two major reasons. 

We are increasingly using systems thinking to address some of our most critical contemporary problems including climate change, energy and the environment, cities and metropolitan areas, jobs and productivity, the global economy, financial systems and national security.  At the same time, we now have the technologies, tools, engineering methodologies and scientific principles to be able to better design and manage such systems.

The Emergence of Cognitive Computing

On October 21 I participate in a Colloquium on the Frontiers of IT at IBM’s Thomas J Watson Research Center.  The colloquium, - which was part of IBM’s Centennial celebration, - brought together experts across industry and academia to discuss and debate the direction of four key Grand Challenges at the very leading edge of IT:  nano systems, exascale, big data, and cognitive computing.

John Kelly, senior VP and director of IBM Research, gave an overview of these four areas.  Here is a similar version of his talk given a week earlier at the University of Melbourne.  John explained that these four areas have the potential to transform the IT industry because of their exponential growth, a result of both continual improvements and disruptive innovations.  “Exponential curves,” he said, “will either put you ahead of the competition of kill you.  It’s one of the other.”

Over the next decade, nano-devices are expected to advance by three orders of magnitude, from a billion to a trillion transistors in a chip.  We will be able to design sophisticated, powerful nano systems-on-a-chip that will be totally contained within such a trillion transistor nano device.  To do so, we will have to shift from silicon to other carbon-based materials.  This requires disruptive technologies and innovations at all levels, including new materials, fabrication processes and design tools.  The work is underway.

The MIT Systems Thinking Conference

I recently participated in MIT’s 2010 Systems Thinking Conference for Contemporary Challenges.  This annual conference is sponsored by Systems Design and Management (SDM) - an interdisciplinary program between MIT’s School of Engineering and Sloan School of Management.  The SDM program aims to provide mid-career professionals with a systems perspective that will help them address and solve large-scale, global, complex challenges.  Most of the students in the classes I have taught at MIT are enrolled in SDM.

The Systems Thinking Conference is intended to showcase innovative ways of addressing complex challenges, in particular, how to integrate technology, management and social sciences to successfully solve very tough problems.  The agenda included sessions on sustainability and urban systems, health care and services.  The talks covered a wide range of subjects, from the global development of Boeing’s 787 to the home of the future.  I was co-organizer of the session on service systems, gave a talk on Technology and Innovation in the Service Economy and moderated a panel with the other speakers in the session.

John Sterman - professor in MIT’s Sloan School of Management and director of the Systems Dynamics Group - gave a very interesting talk: A Banquet of Consequences: Systems Thinking and Modeling for Climate Policy.  The title of his talk is based on a quote by Scottish writer Robert Louis Stevenson: Everybody, soon or late, sits down to a banquet of consequences.

Lessons from the Rescue of the Chilean Miners

I first visited Chile about 25 years ago, and have continued to do so from time to time, most recently in September of 2009 when I went to Santiago to join in the celebration of the 80th anniversary of IBM Chile.  I will return in a few weeks to participate in the Smarter Cities meeting that IBM is holding in Santiago on November 23.  Over the years, I have met, worked closely with, and established personal connections with a fair number of people in the country.

This personal connection added an extra dimension to my interest in the rescue of the 33 Chilean miners, although the rescue story has been so compelling that I am not sure anything extra was needed to capture my attention.  Along with a large portion of the world, I was transfixed by the rescue of the miners. Would everything work as planned?  What if something went horribly wrong as we were all watching on live television?  Disaster movies have taught us that just as you become confident and relaxed, things start going haywire.  Would that happen here?

Thankfully, everything went smoothly.  There was indeed a lot of drama, but it was all provided by the emotional reunion of the miners with their families as each reached the surface, as well as by the warm welcome they each received from everyone present, including Chilean president Sebastian Piñera and mining minister Laurence Golborne.  We held our breaths from the time the first miner, Florencio Ávalos started his ascent right before midnight (Chile time) on October 12, to the time the last one reached the surface less that 24 hours later, Luis Alberto Urzúa, their shift supervisor and overall leader.

A lot of the attention is now likely to focus on how the miners and their families deal with their new celebrity status and potential financial rewards.  Everyone agrees that while their fame may be lucrative, it will also be stressful.  There will be lots of opportunities for public appearances, press and TV interviews, and possible book and film deals.  Some will undoubtedly find their new fame too stressful and will yearn for their simpler lives as miners.

Values, Trust and Reputation in an Increasingly Complex World

Both present and future leaders expect the business environment to grow significantly more complex over time.  This is one of the main conclusions of two recent studies conducted by IBM, the 2010 Global CEO Study, and the companion student study, Inheriting a Complex World.  CEOs and senior government leaders - who I presume are mostly in their 50s and members of the Baby Boom Generation, - said that their primary challenge is figuring out how to operate in a world that is substantially more volatile, uncertain and complex.  The students, on the other hand - mostly Millennials in their 20s, - understand implicitly and intuitively that economies, societies and organizations are interconnected and interdependent.  They don’t even need a definition of complexity, since that is the only world they have ever known.

These two generations of leaders, - one at the top of their careers and the other about to start out on theirs, - are reacting to the changes all around them in distinctly different ways.  The Boomers keep replaying the ideological and cultural battles with which they grew up.  “What degree of government regulation is needed to help curtail the kinds of abuses that led to the ongoing global financial crisis?  Are self-regulated free markets always the best answer?  What does it mean to live in an increasingly multicultural society?  Should society accommodate to the different kinds of nuclear families all around us?

The Millennials are in a very different space.  They don’t need to keep defending market economies against communism, as this issue was settled with the fall of the Berlin Wall and the subsequent collapse of the Soviet Union, which happened when they were little or even before they were born.  They have generally grown up and are comfortable living in a much more diverse environment.  They have had openly gay and lesbian friends since high school.  Get a life is what I imagine they are thinking when they hear the tired ideological and cultural debates of the older generations.

Growing Up in a Complex World

Several weeks ago IBM released its 2010 Global CEO Study.  This is IBM’s fourth and largest CEO study since 2004, based on more than 1,500 face-to-face interviews with CEOs and senior public leaders from more than 60 countries.

I wrote about the CEO study in this recent blog.  The primary challenge emerging out of the CEO conversations was complexity - the fact that CEOs now operate in a world that is substantially more volatile, uncertain and complex.  They feel that incremental changes are no longer sufficient because the world is operating in fundamentally different ways.  The study concluded that Standout organizations - those that have been able to deliver good business results despite the recent economic downturn - feel much more prepared to capitalize on complexity by focusing on three key areas:  embodying creative leadership, reinventing customer relationships and operational dexterity.

On June 14, IBM released a companion to the CEO study, this time focusing on the views of young people, members of what is often referred to as the Millennial Generation or Generation Y.  Inheriting a Complex World: Future Leaders Envision Sharing the Planet invited graduate and undergraduate students to participate in a Web-based survey between October 2009 and January 2010.  More than 3,600 responses were received from students in more than 40 countries.  They were pretty evenly split between undergraduates and graduate students, as well as between emerging and mature markets.  More than two thirds were between 20 and 25 years old.

Smarter Public Health

The increased importance and fast rising costs of healthcare in the US and many other countries are causing a much greater interest in the subject of public health - “the science and art of preventing disease, prolonging life and promoting health through the organized efforts and informed choices of society, organizations, public and private, communities and individuals.”  

We are all very familiar with the fierce political debates surrounding US healthcare reform, which culminated with the historical Health Care Act of 2010 signed into law by President Obama on March 30.  But healthcare is not only a major political challenge, but one of the grandest overall challenges facing the world in the 21st century.  

The problems are enormous at multiple levels.  Healthcare involves lots of people and institutions - patients, insurers, device manufactures, pharmaceuticals, advocacy groups, biotech, research institutions, IT companies, governments of all sorts, state licensing, state insurance commissioners, and on and on and on.  And this is before you get to the provider side, which involves doctors, nurses, hospitals, pharmacies, non-traditional providers, medical schools, and others.

History in the Making

I have been transfixed by the long health care reform debates in the US, which finally culminated with the House of Representatives passage of the health care reform bill on March 21, and which President Obama signed into law two days later.  The House also passed the reconciliation bill which the Senate subsequently approved on March 25.  The health care reform bill is now the law of the land.

This bill joins other landmark social legislation, like President Roosevelt’s 1935 Social Security Act, and President Johnson’s 1964 Civil Rights Act and 1965 Medicare and Medicaid Acts.  And, like those previous bills, you cannot analyze their pros and cons in purely tactical terms.  You have to focus on the impact of such landmark legislation on the long term evolution of the country.  You have to look at the 2010 health care legislation as history in the making.

There is no question that this legislation is imperfect, perhaps considerably so.  But there is also no question that health care in the US has been frozen in decades-old models that no longer work.  As many have pointed out, despite expenditures that are significantly higher than those of other industrialized countries, US healthcare performance has been declining relative to these countries on just about all key indicators of health, including quality, access, efficiency and equity.  Unique among industrialized countries, over 15% of the US population lacks health insurance, which according to several studies, is responsible for tens of thousands of unnecessary deaths every year.

The status quo was unacceptable.  Something had to be done.  Most of us would agree that, the US is better off for having passed social security in 1935, and Medicare and the civil rights act in the mid 1960s.  The key question we must now ask is whether years from now, our country will be better off as a result of our having just passed these health care bills.

The Healthcare Reform Debates

The ongoing US healthcare debates - or is civil war a better description? - remind me how incredibly hard it is to bring about disruptive transformations of any kind. 

In my experience, organizing disruptive transformational efforts is very difficult.  I learned this first-hand at IBM with efforts like the Internet initiative in 1996 and the Linux initiative in 2000.  Given that the organizational complexities go way, way up with the size and scope of the initiative, I am not surprised how incredibly difficult it has been to try to bring about the badly needed transformation of healthcare across the whole country.

A transformational initiative is subject to very different organizational dynamics from more incremental ones.  With incremental initiatives, you are looking to improve something that already exists in the marketplace - e.g., better products and services, higher customer satisfaction, increased overall efficiency.  Because you are improving something with a history, there is lots of information that can be analyzed to estimate the impact of the improvements on the business.  You can make a case for the improvements based on quantitative, fact-based, rational arguments.

Not so for initiatives based on disruptive technologies or ideas.  Disruptive transformations are, indeed, disruptive.  They are a break from the past, either because past approaches no longer work and are getting us into deep trouble; because a new technology or idea now offers us much better opportunities; or both.  But, while the changes might be absolutely essential, it is important to keep in mind that you are asking people to move from something that, while imperfect and flawed, they are familiar with, into unknown, most likely uncharted territory.

Reflections on Smarter Healthcare Systems: Practical, Concrete, Expert Advice

On October 1 and 2 IBM held its second global Smarter Cities conference in New York City.  I subsequently wrote about the excellent talk, Great Expectations for US Healthcare, given by Dr. Denis Cortese, CEO and President of the Mayo Clinic on the first day of the conference.

The next day, there were break-out discussions in six key areas relevant to building a smarter city: transportation, education, public safety, energy and utilities, government services and healthcare.  I was co-moderator of the healthcare session, along with Dan Pelino, IBM’s General Manager of Healthcare and Life Sciences.  Our panel of experts included Dr. Cortese; Chris Coburn - Executive Director of Innovations at the Cleveland Clinic; Dr. Ronald Paulus - Chief Technology and Innovation Officer at the Geisinger Health System;  and Dr. Armando Ahued Ortega - Health Secretary of Mexico City.  Let me summarize their practical and concrete remarks.

Designing a Smart Healthcare System

On October 1 and 2 IBM held its second global Smarter Cities conference in New York City.  The first such conference was held in Berlin this past June, and the third will be held in Shanghai next year.

As was the case with Berlin, the New York Smarter Cities event had a very impressive agenda.  It included talks by IBM Chairman and CEO Sam Palmisano, New York City mayor Michael Bloomberg, and Melody Barnes, Director of the White House Domestic Policy Council.  The agenda also included panels with governors, mayors, and leaders of cultural institutions. 

In addition, there were break-out discussions to enable participants to share their experiences on what it takes to build a smarter city in six key areas: transportation, education, public safety, energy and utilities, government services and healthcare.  I helped organize and moderated the healthcare session.  Our panel included Denis Cortese - CEO and President of the Mayo Clinic; Ronald Paulus - Chief Technology and Innovation Officer at the Geisinger Health System; Chris Coburn - Executive Director of Innovations at the Cleveland Clinic; and Armando Ahued Ortega - Health Secretary of Mexico City.

The Health Care Debates, Tribalism and The Golden Rule

Earlier this summer, I was in Berlin to participate in a Smarter Cities conference hosted by IBM.  I had not been to Berlin in a while, and was looking forward to seeing it, especially since it is one of my daughter’s favorite cities in the world.  I was not disappointed.  Berlin is a very nice city indeed, with lots to see and do, full of young people and positive energy.

But, you cannot visit Berlin and not be struck by its history, especially if you are Jewish.  Its Memorial for the Murdered Jews of Europe is haunting in its simplicity.  Newsreel images of Berlin Nazi rallies sweep through your mind.  And a question keeps coming up.  What happened?

Richard von Weiszacker, - who was mayor of the then West Berlin from 1981 to1984, and President of Germany from 1984 to1994, which included the fall of the Berlin Wall and the reunification of  East and West Germany, - spoke at the conference on the history of Berlin. He reminded us that before the Nazis came to power in the 1930s, the city was the intellectual center of the world.  People everywhere learned German to be able to read the best textbooks and academic journals in their fields, much as they do now with English.  How could such an advanced civilization engage in such monstrous acts?

Numerous books have analyzed this question.  The answer that makes the most sense to me is rather simple.  Civilization is a relatively recent and thin veneer on human behavior.  People are capable of terrible actions against their fellow men, especially when they are under severe stress and are incited to blame others for their fears by skillful demagogues.

The Innovator's Prescription: A Disruptive Solution to Health Care

Clayton Christensen is Professor of Business Administration at the Harvard Business School.  He is one of the world's foremost thinkers in strategy and innovation. In particular, Clay – since I know him personally, I feel I can call him by his first name - is an expert in dealing with disruptive innovations, developing organizational capabilities and finding new markets for new technologies.  In addition, he has a major quality that distinguishes him from most experts.  Not only does he repeatedly come up with great ideas, but he also comes up with innovative ways of communicating his ideas so that they are accessible to lots of people in the business world and the general population. 

Clay is also an accomplished writer.  His first book, The Innovator's Dilemma is a classic.  His second book, The Innovator's Solution - co-written with Michael Raynor – is a comprehensive guide to innovation in all aspects of a business.  I use it extensively in my MIT graduate seminar.

His new book, The Innovator's Prescription: A Disruptive Solution to Health Care - co-authored with Jerome Grossman and Jason Hwang, - is scheduled to come out on September 19 of this year.  When I learned that he is co-author of a new book on health care, I quickly invited him to MIT to give a public lecture on the subject.  Clay came to MIT last month, and not only was his seminar - which can be seen here - excellent because of its fascinating content, but it could also serve as a master class on how to discuss a very complex subject in an accessible, interesting and elegant way.

A Grand Challenge Crying Out for Leadership

The November 25 Sunday New York Times included yet another editorial bemoaning "The High Cost of Health Care."  It is a good editorial, and I generally agree with both its list of Causes as well as its recommended Solutions.  But I wonder if anything will come of it.

The editorial points out that "health care costs are far higher in the United States than in any other advanced nation, whether measured in total dollars spent, as a percentage of the economy, or on a per capita basis."  This would be fine, or at least tolerable, if the U.S. enjoyed a quality of health care commensurate with its higher costs.  But as we well know, this is not the case. 

The Commonwealth Fund, a private foundation, reported in a recent article, "Despite health expenditures that are twice those of the median industrialized country, a new national scorecard of U.S. health care system performance finds the nation falls short on key indicators of health outcomes, quality, access, efficiency, and equity."  It goes on to say that "Among 19 industrialized countries, the U.S. ranked 15th on mortality from conditions amenable to health care, or deaths before age 75 that are potentially preventable with timely, effective care. The U.S. rate was more than 30 percent worse than the benchmark—the top three countries. The U.S. also ranks at the bottom for healthy life expectancy and last on infant mortality."

There is nothing new here.  We have all been reading editorials and reports like these for a while now.  Calls for action abound.  Among the top recommendations of the 2004 U.S. National Innovation Initiative was a call to build a health care test bed, including electronic health reporting, standards for an integrated health data system, pilot programs for international exchanges on health care research and delivery, and the use of performance-based purchasing agreements.

Finally, the 2005 report, A Healthy System issued by the Technology CEO Council, concluded, "If there's one thing that everyone agrees on about the U.S. health care system, it's that it isn't, in fact, a system," and that "the sad truth is that in health care today the whole is much less than the sum of its parts."  The report went on to say, "We will never fix this problem simply by tinkering with its parts. As a practical matter, and as a moral imperative, we have to address the systemic problems of health care.  And the most glaring - and promising - is health care's shocking lack of modern, networked information technology (IT), and the lost quality and efficiency that result."

Applying "Lean" Thinking to Healthcare Solutions

The second Innovation Lecture Series: Engineering Systems Solutions to Real World Challenges took place on December 14 at MIT.  The series is co-sponsored by MIT's Engineering Systems Division and IBM's University Relations as part of its Skills for the 21st Century initiative.  The first lecture in the series was held in October and featured IBM's Senior Vice President Linda Sanford, discussing the IBM transformation initiatives that she leads.    

The Innovation Lecture Series are delivered by business and technical leaders, who discuss their concrete experiences in leveraging technology and engineering capabilities to address complex problems in their organizations.  This past lecture focused on healthcare and featured three top executives of the Vassar Brothers Medical Center, a regional medical center and hospital in New York State's mid-Hudson Valley: Dr. Daniel Aronzon, President and CEO; Nicholas Christiano, Vice-President and CIO; and Dr. Stephen Katz, Chief Medical Officer and Senior Vice-President of Medical Affairs.  A webcast of the lecture as well as additional materials are posted in the Innovation Lecture Series web site.

Building Open, Collaborative Health Care and Education Platforms

I wrote in a recent blog that "the Internet showed everybody how much more valuable IT is when you can connect and access everything regardless of vendor, and started the IT industry on a whole new strategy based on embracing open standards."  The Internet enabled IT to become an open, global platform for innovation, in particular a platform for open, global, collaborative innovation.