I have liked Twitter since the first time I heard about it, probably on Fred Wilson's blog AVC. Twitter was like Dropbox and the Palm Pilot. Love at first sight. Twitter instinctively filled a need for me and the interface was so simple there was no learning curve.
I joined Twitter February 29, 2008, about 18 months after the launch. My statistics on Twitter come from my Twitter Archive, which is under Your Twitter Data in Personal Settings. A few stats:
5695 Tweets
1316 tweets on "finance", mostly about this blog
584 tweets on entrepreneurship and an additional 116 on social entrepreneurship
261 tweets on StartUP FIU
208 on One Laptop per Child
166 on MIT
143 on Google
117 Tweets on Facebook
91 on government
83 on economics
79 on the environment
Most popular blog I tweet on--Marginal Revolution--is devoted to economics with an Austrian School point of view.
All of the above looks fairly representative of what I do and think about. Economics is probably underrepresented.
I was talking to someone recently that argued that government grants to private companies were the most effective grants because the companies had proven methods to commercialize innovation. The person cited government funding for Tesla, but I can find little evidence of government cash as opposed to incentives going to Tesla.
This Tesla example reminds me of a big difference now at the beginning of the Fourth Industrial Revolution compared to the Third Industrial Revolution that began in the 1960s with the advent of computing and digital information. In the 1960s government funding was plentiful at top universities like MIT and for government agencies like NASA. This investment lead to new technologies such as computer networks, microwave and advanced materials which were widely adopted. Eventually the resultant creation of economic and social benefit reached unheard of levels of prosperity.
The situation today is one where government funding, in limited amounts, is made available for basic research at universities. Little money is available for applied research and agencies like NASA have been greatly reduced for many years. If we think about when a startup needs money, the answer is in the early stage when it cannot easily access capital markets. If we look at an Industrial Revolution, again the capital is needed in the earliest stages to fund the primary innovations.
What might save the Fourth Industrial Revolution from a lack of government funding is that so much innovation surrounds data, information and technology (like the Blockchain) that does not require huge amounts of funding. Now generally I favor limited government and a commercial playing field not disrupted by government. However, government funding for significant basic and applied research makes sense to me, particularly given the declining spending on research by corporates. The corporates with the best ROI still invest in research according to HBR. Almost all the other corporates choose to enrich management or shareholders rather than invest in research.
The views expressed herein are my personal views and do not reflect the views of any organization that I might represent.
For expert advice on real estate in Queens, NY, please contact my daughter Christina at 347-768-0427 or email [email protected]
I have just finished my third book, tentatively titled "The Foundation of Entrepreneurship: Large Market Opportunities that have Repeated for 40,000 Years". Book deals with large market opportunities that have repeated throughout history. For example, every time money changes form, there is a new large market opportunity. Title suggestions welcome. If you would like to read the latest draft, email me.
I have started thinking about my fourth book, which will be on assumptions or maybe assumptions and boundaries and how they affect the way we think about problems. Thinking about assumptions reminded me of this post I wrote in 2010, "Why can I not Timeshare a Dog". Sometimes it takes awhile to figure things out and some times I get distracted by other issues. The delay in getting back to assumptions I will blame on a multi-year study of complexity, which resulted in four chapters in book three.
Each of these articles deals with the advances in AI with respect to data analysis. The articles herald the amazing conclusions we have only recently been able to draw from the data. The second article goes on to talk about how the way humans think is changing to better use the new AI tools. The third article talks about how AI tools have totally changed in the last ten years, moving away from rules toward something that approximates human "learning". I could have picked 10-20 other articles in the last month that herald the same trends as these three articles.
The depressing conclusion I draw is that science and social science is now going to be almost entirely shaped by the available data sets and the AI tools available to researchers. Also, probably for the first time in history private companies now have greater resources to do AI research than universities and more importantly are using the resources for this research. However, this corporate research is more likely to find the next behavioral insight than a breakthrough such as chaos theory or quantum mechanics. Furthermore, the best academics in Physics, math and computer science are being lured away by the corporates to do AI research. The outlook for breakthrough research that changes the future of mankind looks much less likely.
All of this would be distressing if not for a bigger concern. As we continue to advance science we are coming to realize that almost all human behavior can be explained by biology and physics. A representative article showing this trend is Swirling Bacteria Linked to the Physics of Phase Transitions. (For some unknown reason I love these articles where the apparently chaotic is explained.) I call this the "think like an ant theory". To understand a problem, think like an ant.
A popular emerging field is the combination of biology and business, where complexity science brings a cohesiveness to two such disparate fields. From this increasing understanding and reliance on biology and complexity science, one comes to realize that these simple models and methods can probably explain nearly everything. For example, to understand cities, first understand hunter-gatherer tribes. To understand entrepreneurship, first understand exploration and exploitation (what we now call Lean Startup), the fundamental behaviors of every living thing. This trend toward simplicity, however, is not supported by the popularity of AI and data sets.
If we look back in human history, until the twentieth century research was not heavily reliant on data collection and data sets. Therefore, most of the great thinking in human history was done by methods that were far simpler than AI. I do not think we need to return to the 16th or 17th century methods at the expense of AI, but I do think we need to realize that AI is not a panacea and traditional thinking still has much to contribute.
One could probably argue that the problem with research since the last century has been an increasing effort for it to look data-based and scientific. AI will only make such approaches easier and wider ranging. The original style of thinking of Aristotle, Descartes and Hayek should not be forgotten or held in disdain.
Brain Pickingstoday writing about Bertrand Russell:
"But beneath such a surface impression is enormous depth of insight and a timeless, increasingly timely clarion call for nuance in distinguishing between the sort of knowledge driven by a greed for power and the higher-order wisdom that makes and keeps us human."
I have been reading a fascinating book which I will use next semester in at least one course I teach--How We Got to Now by Steve Johnson. On the surface, the book deals with six inventions that changed the modern world. Perhaps more interesting is the insights about the inventors and in particular the mental frameworks that led to the breakthroughs. Equally interesting is how the book helps to illustrate the seminal work of Thomas Kuhn on paradigm shifts and their impact.
One particular story about the AT&T telephone monopoly illustrates the power of open source technology. Almost from the birth of telephony, AT&T had a monopoly in the U.S. The company worked very hard to maintain the monopoly. In 1956 AT&T agreed to license all the technology of its subsidiary Bell Labs for free to American companies in return for keeping the telephone monopoly. Bell Labs went on to create and advance technologies such as transistors, computers and cell phones, all of which were licensed to other companies. The quality of the technology and its subsequent adoption and impact demonstrate to me the power of the open source model. Wikipedia defines open source as "a decentralized development model that encourages open collaboration."
Perhaps this example from AT&T will help people to remember the alternative of open source.
In the latest book that I am writing, on how to find the business opportunities that have repeated multiple times over the last 40,000 years, I draw on insights from complexity science. Think of complexity science as an alternative to chemistry to explain the relationship between physics and biology. Two different languages and ways of thinking to explain the same events.
A fundamental part of complexity science is the concept of a network. Examples of networks are the Internet, Facebook and every "community". In a chapter on organizations in the book I make the point that great organizations are a stack of networks. For example, if we look at a great university like Harvard or MIT, we can understand them by their networks: students, faculty, alumni, institutes of learning, research partners, etc. These networks process information separately but compliment the whole of information. Fail to create a strong network in any one of these categories, and the university probably fails to achieve greatness.
This morning I was reading an article by Ray Kurweil, futurist and authoity on AI who trained at MIT with the late Marvin Minsky. Kurweil tells the story that multi-layer neural nets were proposed in the 1960s but were rejected by Minsky and his associates. Such networks are commonly used in AI today. The point of the story--multi-layer neural nets look an awful lot like stacked networks in great organizations.
Patterns that repeat in nature and in computer science are the basis for powerful thinking frameworks. Keep your eyes open for stacked networks.
Yesterday's reading discovered some excellent articles:
Esko Klipi on Medium, "It is only a few network connections away". He points out that networking is growing increasingly important as the Internet shrinks the world. Makes one realize that networks created by people could be more powerful than 20th century forms of organization.
Evonomics.com on inequality, "The Science of Flow Says Extreme Inequality Causes Economic Collapse". What caught my attention was a quote from Robert Reich, "But in The Work of Nations (2010), Robert Reich also points out that the companies that are flourishing through globalization and technology are ones pursuing what he calls high-value capitalism, the high-quality customization of goods and services that can’t be duplicated by mass-produced uniformity at cheap places around the world." I rarely agree with Robert Reich, but I think he is correct this time. I think that corporate governance has enforced too narrow a set of objectives and the executives have opted for the easiest path. BTW, Evonomics is doing an excellent job of trying to redefine how we look at government economic policy with a particular emphasis on complexity economics.
Stanford Social Innovation Review on corporate social responsibility, "Corporate Social Responsibility for a Data Age". In managing disasters much valuable data is behind corporate firewalls and not normally available to the government. The article suggests that the data be made available after the disaster, but it appears more logical to me to pre-position the data.
At 25iq two great articles on entrepreneurship, "A Dozen Lessons on Growth" and "A Dozen Lessons About Product/Market Fit". Just simply one of the best blogs around on entrepreneurship. Step-by-step type detail on understanding subjects that most people misunderstand.
In another of my favorite blogs on economics, Marginal Revolution, "Online Education and Personalized Learning". The article makes the point that in any class there are students performing at many different grade levels. Online learning provides one way for students to follow their own pace of learning. Pace of learning is a big issue that I see rarely addressed. (See image above.)
Aswath Damodaran on ValueWalk, "My Snap Story: Valuing Snap Ahead Of It’s IPO!". Damodaran is a leading academic authority on valuation and Snap will be one of the biggest IPOs of 2017, if it gets away. Sorry, got confused and included a finance article
I do not think I have ever posted my work-in-progress notes on a subject. These are unedited excerpts that I put together from my archive as the first step in a new project. The document attached is on "proof of concept" and how one might think about delivering such a concept. Notes are not complete but there are definitely some nuggets included that go back to 2009. Document is here Download POCC Notes 2017.
For the last seven years I have taught an IAP course at MIT on social entrepreneurship. The early years focused on my experience at One Laptop per Child (OLPC). OLPC started at MIT and was one of the largest social entrepreneurship ventures (SEV) at the time. In recent years I have focused the course more on scaling an SEV and use three different models to develop an understanding of the key concepts for scaling. This week I am at MIT.
Coincident with this year's course I have been reading the writings of Ludwig von Mises. Von Mises is considered by some to be the leading thinker in the Austrian School of economics. I prefer Hayek for the wide range of his writings, which arguably included complexity, information theory, behavioral economics, psychology, political theory and economics. Von Mises is however the better writer with a lucidity and logic that is both compelling and original.
One of the points von Mises makes clear is the importance of capitalism and markets in allocating capital. He wrote at a time in the 20th century when socialism and communism were being actively advocated for as better alternatives than capitalism. In class one of the students was advocating for government subsidies to support certain social initiatives. I asked why he thought the government was better at allocating this capital than the individual taxpayers. Silence followed, and then he said that a small group in Washington was better able than the public to make decisions about the future. I replied that small group decision making was the same model used by dictatorships. Deafening silence. In fairness to the student, everyone has problems with decision making about the future, but let's continue to explore von Mises point.
Suppose the government announces that they are raising taxes to subsidize a lunch program for students. Sounds good, research shows that children learn better when not hungry. However, this tax revenue will now prevent the next Google from raising its first round of venture capital because certain people will not have the capital to invest. Setting aside the question of financial return, what if the next Google cures cancer! Now it may not be so obvious that we should let the government use our money to subsidize school lunches.
The point of this post is that when you look at government investment and social projects one should always consider the allocation of capital. Such an approach probably reduces the role of government and raises the bar for social projects, which I assume here will nearly all be social entrepreneurship. The bar is raised because now the social project needs to focus equally on impact and capital efficiency. One could argue that such an approach prevents certain worthwhile projects from being funded. Perhaps, but there are so many good social projects now, why not pick one that is capital efficient. It is not for me to decide whether clean drinking water or childhood education is more important, so I have no concern picking the capital efficient one amongst the two. When both projects are capital efficient I am willing to consider other factors. This paper from SSIR, Across the returns continum, offers a logic for such trade offs from Omidyar Network. If the project were a platform to facilitate additional social projects, that would probably be a deciding factor for me.
Personally I find nothing inconsistent with combining the thinking of the Austrian School of economics with social entrepreneurship. I think it brings an added discipline to the practice of social entrepreneurship. In the end the Austrians always come back to the concept of individual empowerment, whether it be in economic development or capital allocation. I am always very comfortable looking at social entrepreneurship through the lenses of individual empowerment.
This is a chapter from a new book that is almost finished. Comments are most welcome.
The book explores ten large market opportunities that have repeated throughout the last 40,000 years of human history. Every methodology for entrepreneurship that I have studied or taught always assumes an opportunity. I thought it was time to address how to find the opportunity beyond the usual advice to follow your passion.
After WWII the U.S. economy transitioned from a wartime to normal economy. In the 1960s the first large (30,000 square feet) discount stores appeared, K-Mart being a notable example. What K-Mart represented is that retailers could no longer succeed by pushing basic merchandise at the consumer. Instead the retailer had to offer a varied merchandise assortment from which the consumer "pulled" what they wanted.
Roll forward to today and we see several opportunities for the transition from push to pull. Instead of a doctor-centric approach ("push") to healthcare, Kaiser Permanente, the large healthcare provider, is switching to a patient-centric model ("pull") and achieving significant cost savings to boot. Another example is in university education where the monopoly of universities has broken down in favor of MOOCs and other providers such as Kahn Academy. Now students cannot only select what and where they learn subjects but when--high school, university or as part of lifelong learning. Healthcare and education may suggest that many services that are heavily regulated by the government are going to transition from push to pull. However, as is the case in education, the consumer is initiating the change and not usually the service provider.
In a recent article, Networked Leadership, the author makes the point that leadership is transitioning to a pull model directed from the bottom rather than an asymmetric, top-down push model. To me it makes sense that if the business is living in a real time environment dictated by the customer, then leadership and management styles have to change to much less rigid, hierarchical alternatives.
The economic disparity will be exaggerated by the increasing use of AI. AI requires massive processing power and storage for the required data to power the "learning". If you cannot afford such resources one will not be able to use AI to create competitive advantage and will fall further behind.
In considering disparity one must create solutions that anticipate the future, particularly in the current period of paradigm shift. See 1 above.
Multiplicative systems are systems where each part of a system must function correctly for the system to produce the desired result. Additive systems are such that when one part of a system breaks down, the result changes but the end product still has a value. 8*2*0*7=0, 8+2+0+7=17. Modern computer program design uses an additive approach, but historically used a multiplicative approach.
I think that social problems are generally multiplicative. One has to get all parts correct. Usually one needs to both change a behavior and act in a way that supports the behavior change. For example, the abstains alcoholic needs to stay out of bars.
Read Write Web has an interesting article on the challenges of city management, "Smart cities need banks’ data muscle more than governments". The article states that cities are not likely to be able to manage all the data required to provide modern services in an age of IOT. To solve the data management problem perhaps the banking industry with its expertise in large volume, real time data management is a solution for cities. Given that I think most banks will not survive the coming disruption from distributed networks and related technology, maybe banks should move into data management for cities.
Of course you may have realized that cities and banks share one common characteristic. They are both subject to significant government regulation. Just like healthcare and education, they are also leading industries to be disrupted. Effectively, the artificial boundary of government regulation is now being pierced by new technology.
The point on data got me thinking about whether we should not consider outsourcing more city services than just data management. If we consider cities a stack of software services or perhaps a stack of networks, we realize that every part of the stack is a candidate for outsourcing. In the end, the only service that may remain with the city government is the right to set policy, which is, of course, a basic requirement of a democracy. This notion of the outsourced city government perhaps becomes more interesting when we recognize that power is going to shift away from the national level and back to the cities. Networks and communities are naturally gaining power through the new technology, which will lead to local initiatives that will manifest themselves in the cities and their governance. The networks and the communities are gaining power because comparatively more information is now flowing to the local level through the new technology. Effectively, the individual captures information better than the government, as evidenced by the article that began this post.
The role of information in the shift of power is explained in this Powerpoint, "The Great Convergence". Download .
In January 2013 I wrote in SF about Milton Glaser.
"Over the last few years I have become a student of design. I think it is the closest discipline to entrepreneurship and many principles of design are directly applicable to new business development. I have been reading Debbie Millman's new book, "How to Think Like a Great Graphic Designer " in which she interviews many of the great graphic designers of the late 20th century. Several designers defined design as the combination of strategy and intellect. Interesting that they omit art or creativity in the definition. Also noteworthy is that so many graphic designers moved on to do architecture and product design. The chapter on Milton Glaser is perhaps the best. The intellect of the man is quite exceptional."
In a recent Quartz article, Glaser defines design:
“Design is the process of going from an existing condition to a preferred one,”
I increasingly believe that BCG is doing the best thinking and writing on business and related topics, far superior to HBS, Stanford or McKinsey to name a few organizations. In a recent article in BCG.Perspectives, Why Technology Matters, there are two interesting quotes:
"...the energy industry produces the highest income per dollar of technology spending ($24.24). At the other end of the spectrum, the software publishing and internet services industry produces the lowest ($0.98)."
"...in the US, the IT cost per day of a hotel bed is $2.50, and for a hospital bed, it is $65. The IT cost of a car is $323."
My observations on each quote:
Pricing in the energy market is probably the largest wealth transfer mechanism ever devised or to be devised. Increasingly the issue of income inequality comes back to governments that tolerate it or facilitate it.
The low revenue/IT cost in software and Internet publishing is consistent with the relatively low value-add in those services
The IT cost per day figures demonstrate competitive advantage to me and the lower the number the easier it is to use IT technology to disrupt the industry. Airbnb would be an example. BCG does not provide statistics for all industries, but I imagine the number is low for retail also where disruption is rampant. For your next entrepreneurship venture, calculating the IT cost might document the opportunity. Note, it might not document the timing.
I have just returned from teaching a program at Babson College to a group of entrepreneurs from across the U.S. A few observations:
- More and more women entrepreneurs, who tend to be better educated than the men (in my opinion)
- The trend toward older startup entrepreneurs is confirmed in my experience
- Many people innovating in medical care, focused on improving the customer experience through personal approaches (as opposed to digital)
- Much interest in applying technology to improve services for mental health
- Starting to see companies that have developed information management products for the government thinking about how to commercialize these products in the private sector; suggests to me that the government may be ahead of the private sector in information capture and collaboration
- People that offer professional services such as attorneys, accountants, architects are very concerned about their future viability; they lack any method to understand where in the customer service process the value is created
- Everybody thinks they understand the need for cybersecurity, but few people really understand the depth of the issue; affordability is an issue for most SMB (Small and Medium Businesses)
- Most SMB still do not have effective web presence for e-commerce
- Marketplaces are an area of great interest for new businesses; few companies understand the complexity of starting such a venture despite the quality of writing on the business model
"Increasingly I believe that we can form a new social contract using the technology available to transfer increased decision making authority to the individual. Rather than "fan the fire" or fight the status quo we should use the technology to avoid the current nodes of power and explore alternative approaches at the individual level. Everyone acknowledges that the current paradigm shift in technology will have profound economic and social changes, but we should not overlook the chance to change the political system."
On Saturday September 24 I am speaking at an event for WiseTribe. I am interested in what they are doing because I think they are exploring a new form of "organization" that could be common in the future. Some of my remarks are below.
I have three interests: 1. Entrepreneurship 2. Creativity and early childhood learning 3. Complexity science
• Entrepreneurship is a result of individual empowerment and leads to economic well being. I spend most of my time teaching people to use social entrepreneurship to solve social and environmental problems. My hope is that eventually we can drop “social” because entrepreneurship becomes so responsive to society’s problems. • Creativity interests me because it is the basis for invention and innovation. I study it from the perspective of the young child because so many geniuses say their secret was to maintain a childlike attitude. • Complexity is important because it brings so much insight to understanding people, organizations and networks. There are three types of problems—simple, complicated and complex. Tying your shoes is a simple problem. Building a bridge is complicated, but follow engineering, apply math and bingo a bridge is built. Complicated problems are linear and deterministic. These are the kinds of problems that AI will solve, leaving only the complex problems. Complex problems have independent variables that produce emergent features that are not caused by the variables. Stock markets and social problems are examples of complex problems. Black Swans are a subset of complex problems. • Now if we take complexity in a simple form to understand people, organizations and networks, we see that the roles of each component changes throughout history. When we lived in caves 40,000 years ago the individual was paramount and there were no organizations or networks. Why—no trust and no sharing • Roll forward to the Dark Ages—individuals are enslaved, kingdoms and the Catholic Church are dominant organizations and there are no meaningful networks. • Next 1800s in the U.S.--individuals are becoming empowered after the French Revolution, many small networks such as railroads emerge and the government is emerging as a powerful force. The government increases its dominance throughout the 19th and 20th century because small disorganized networks lend themselves to dominant nodes or organizations. • However, what we have today thanks to computing and the Internet is large, well organized and connected networks. In this environment what network science tells us is that we no longer need large nodes like government. When networks are organized, information exchange is easy and we no longer need large organizations like universities or governments to store and organize information. • Now we could talk about how to redefine government or the modern university, but the more interesting question to me is how do we bring about change through the power of the networked individual. Stanford Social Innovation Review has a very interesting article in which they discuss the new concept of emergent strategy. Emergent strategy, as opposed to the traditional strategy concepts of Michael Porter, focuses on an iterative approach using networked partners to solve problems. Trial and error, decentralized exploration, solid evaluation at every step, transparent reporting—these are the features of emergent strategy, 21st century organizations and movements. In fact this has always been the approach of movements like Gandhi and Mandela. This approach based on emergent strategy has also been embraced by the Rockefeller Foundation, one of the most accomplished social organizations in the U.S. • Now how does all of this apply to WiseTribe? WiseTribe is not an organization. It is a movement, of networked individuals, focused on social and environmental change. WiseTribe is an alternative to government for the management of society—for economic, social and political well being. The government is no longer the default solution. We need to iteratively explore this new power, figure out how to communicate it to more and more people and use WiseTribe(s) to solve the impossible problems that are the ones really worth solving.
Recently someone compared me to a bomb throwing revolutionary. I thought that was a bit overstated. I merely believe that we should be in a constant state of improvement, even if we are working on an impossible problem. Frequently I believe that reducing the scope of government is a productive part of innovation. A few thoughts related to these themes:
Spirituality is reaching an understanding that life is iterative
Constructive anarchy is replacing government with an egalitatian populism
Network theory says that large well organized networks do not need dominant nodes
Do not fan the fire but take a new approach
Increasingly I believe that we can form a new social contract using the technology available to transfer increased decision making authority to the individual. Rather than "fan the fire" or fight the status quo we should use the technology to avoid the current nodes of power and explore alternative approaches at the individual level. Everyone acknowledges that the current paradigm shift in technology will have profound economic and social changes, but we should not overlook the chance to change the political system.
[This article was influenced by ideas that have existed for thousands of years.]
