Challenges and Opportunities
Last year I was in Singapore and met Israel’s former economic minister. When I asked why he was there he said, “Like Singapore, Israel is a small country. Most of the world’s important opportunities, talent, and resources are somewhere else. I am here to discuss how to make the world transparent for us.” That is an important idea. This objective is also being pursued by companies and universities around the world.
Definition: Transparency in a region or enterprise is the overall ease of movement of ideas, people, money, transactions, and objects. High transparency implies low friction in conducting these activities. Silicon Valley, with its high density of innovative companies, venture capitalists, entrepreneurial talent, research universities, and networking activities, is an exemplar.
For thousands of years, society has worked to make the world more transparent through roads, ships, the pony express, trains, cars, airplanes, teletypes, telephones, radio, television, and now the Internet. The impact of these advances has brought the world together and created greater transparency.
The great cities, which are based on trade, have developed along corridors of high transparency. The growth of these cities shows the power of transparency in all its forms – communications, speech, commerce, finance, government policy, and logistics. Similarly, cities are where most of the great innovations arise.
The Internet is a giant step forward because it gives every person the ability to instantly connect with everyone else while providing access to the world’s knowledge. But today’s access and bandwidth are still limited for most across the globe. Image quality for video teleconferencing is too often reminiscent of last-generation’s analog television. And access to information is often hard or impossible. Google search is still primitive. The world’s ocean of knowledge has the equivalent of billions of fish it it, but only a few can be caught with today’s fishing rods.
What is often most valuable is not just one idea, but the synthesis of multiple ideas. Innovation is defined as the creation of new knowledge with sustaining value for society. As Peter Drucker noted, a “characteristic of knowledge-based innovations is that they are almost never based on one factor but on the convergence of several kinds of knowledge, not all of them scientific or technological.” Putting together multiple forms of knowledge in new, surprising ways is what creates valuable innovations. It is also why cities are so important. As they grow and become more diverse, the opportunities and competitive forces that drive the convergence of different forms of knowledge increases.
Today’s artificial-intelligence (AI) tools for making connections between ideas are still like hand tools, when we need industrial-strength power tools. But advances in machine learning, AI, and increase connectivity are showing what is possible. For example, at the online competition site Kaggle, teams from around the world were given two months of airplane flight data and asked to optimize the plane routes. This is a version of the “traveling salesman” problem that mathematicians have worked on for centuries.
A team of four Singaporeans and a Frenchman won the $100,000 prize using a machine-learning algorithm that is 40% better than today’s benchmarks. Even a fraction of that potential translates into billions of dollars of yearly savings.
Their achievement is impressive since this is one of most studied problems in mathematics. Yet a small team working for only a few months created a meaningful advance by tackling it from a completely new direction using mostly open-source computer applications. As Drucker noted, they brought together several different forms of knowledge to create a novel solution. They also proved that a small “pick-up” team from around the world can address extremely hard problems and create major new innovations. The intellectual “city” they worked in was not Singapore, but the world.
The team won $100,000 but more importantly for them, the entire world now knows that they are machine-learning superstars. The team’s value has skyrocketed because they proved they can create extraordinary value for society.
The other technical limitations I mentioned earlier are being rapidly addressed. Over the next few decades almost all of the world’s population will have adequate Internet and phone access, teleconferencing will be at 4-K resolution or more, in 3-D, and with intelligent computer assistants, like Siri, increasingly exhibiting savant-like abilities. A major factor is the advent of 5-G with both the bandwidth and reduction in latency. Experiments show that at the vividness provided by 4-K, being there virtually can feel as real as being there physically. In may ways it will be better becuse the visibility around the room will be better than sitting in one location.
Siri-like computer systems will become word mavens and insightful analysts. They will provide simultaneous translation in any language, real-time meeting input, and the creation of follow-up agendas. In addition, advanced AI and machine learning systems will, in real-time, find and assemble information. They will be able to identify opportunities and synthesize information to help create new knowledge.
Ray Dialo, for example, has created a radically transparent organization to profoundly improve decision-making. They use a family of computer tools to track performance but to also understand the capibilites of staff so as to better create productive teams. He is working, to a surprising degree, to replace mangers with AI tools. These kinds of tools will be applied globally to find, evaluate, and hire the best expert. These experts can be either added or subtracted to the team, as needed.
Such developments will not be limited to algorithm advances. Developments in 3-D printing, virtual supply chains, and real-time delivery by drones and autonomous vehicles will make it increasingly possible for global teams to design, manufacture, and deliver products throughout the world.
Some consider even these predictions to be too restrained. For example, Ray Kurzweil at Google predicts that we will become human-computer hybrids by the 2030s and 2040s. Our brains will connect directly to the cloud, where super-computers will augment human intelligence. “Our thinking then will be a hybrid of biological and non-biological thinking,” he says. Eventually our thinking will be more non-biological than biological. We don’t have to agree with everything Kurzweil predicts to know that the world is going in that direction.
Transparency can be thought of as a signal-to-noise detection problem. Would-be innovators are working to find those faint “signals” in a background filled with “noise” that will allow the creation of new knowledge and new innovations. It is about connecting unmet needs to both existing and new knowledge to create surprising new innovations. To stay competitive societies and enterprises must make the “signals” easier to find by using signal “amplifiers” while removing signal “attenuators” and sources of “noise.”
Signals: changes in technology, consumer preference, government regulations, competition, demographics, and natural resources.
Amplifiers: free speech, trade, and people, transparent institutions, ubiquitous communications systems (e.g., Internet and 5G), efficient infrastructure, knowledge clusters, networking organizations, reliable legal institutions, high levels of education, complementary diversity, auspicious locations, abundant natural resources, a productive culture, and positive incentives (e.g., fair rewards for the formation of new ventures).
Attenuators: inappropriate regulations and taxes, legal restrictions, monopolies, labor laws favoring selected groups, long approval processes, poor management practices, lack of efficient value-creation methodologies, top-down enterprises, prejudice and discrimination.
Noise: financial instability, regulatory and tax uncertainty, national security threats, crime and corruption, crony capitalism, political favoritism, weather and natural disasters, and legal ambiguities.
As described by Drucker, all major innovations are multidisciplinary and often arising from multiple major changes in technology. For example, consider what we call “colliding exponentials.” Computer performance is an exponential, with 100% price-performance improvements every two years. But machine learning, natural language, and computer vision are also all improving exponentially. The combination of these different forms of knowledge can “collide” and open up transformational innovations, such as Siri.
The ability to synthesize multiple forms of information to create surprising new knowledge is the essence of innovation. If a new innovation doesn’t first seem surprising, it is unlikely significant. Consider the first time you saw a ketchup bottle upside down on a flat top. That simple, surprising solution provided new customer value. Now we expect it. Today, if the bottle is not upside down we are surprised, but now because it has negative value.
Creating new innovations is inherently difficult. Understanding the impact of colliding exponentials requires intense collaboration, increasingly from global teams. Everything possible should be done to make it easier. Transparency helps the innovator see the different signals. Hong Kong has until recently been a model of economic transparency. Silicon Valley is an exemplar today. Going forward global teams will create their own virtual ecosystems to embrace such advantages.
These emerging trends lead to several conclusions. First, as the world becomes more transparent the rate of innovation will increase along with the intensity of competition. Second, when teleconferencing systems break down the barriers of language and distance the competition for professional jobs witll be global. This will accelerate innovation but may suppress wages. Third, in many markets it will be like the Olympics, with only a few major winners in each category. As Tom Friedman says, “average is over.” An enterprise must aspire to be the best at what it does or go home. And, like training for the Olympics, every advantage matters. Transparency matters.
The Kaggle flight-planning competition is an example of how the world is adapting to the global innovation economy. Going forward success will require assembling the finest teams wherever they reside, using the best value-creation practices, and leveraging the most powerful infrastructure and collaboration tools. In subsequent posts I will discuss what these ideas mean for companies and universities.
Thanks to Norman Winarsky and Greg Eying.
