SOPHISTICATED FINANCE

Examples of Good Thinking

 

Yesterday's reading discovered some excellent articles:

1. 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.
2. 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.
3. 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.
4. 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.
5. An interesting article about neuroscience, "Measures of Entropy and Complexity in altered states of consciousness". What could be more geeky than entropy, complexity and neuroscience. What caught my eye was the notion of plotting complexity vs entropy. 
6. 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.)
7. 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
    

Image credit: Marginal Revolution

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A Moviemaker's Insight on Technology

One of the domains that is studied at the MIT Media Lab is the use of computers in early childhood learning. Both Marvin Minsky and Seymour Papert said that the computer would only make a meaningful contribution to learning if we could find new ways to learn through the computer. Clayton Christensen from HBS shared the same view in his book on disrupting education. For example, flash cards on a computer was no better than the old paper flash cards. Khan Academy and all the MOOC programs did little to change how people learned (although they had a profound impact on the availability of good teaching).

Today on the AVC blog there is a video interview of film maker Werner Herzog. In the interview they ask Herzog if he is considering to develop movies in VR. Herzog answers that he will not do VR movies.. He says we have to look for new ways to use VR (for it to be valuable).

This concept that we should use computer technologies in new ways got me thinking about AI. Using AI to do data analysis is not all that big an improvement over what humans have done since Descartes. However, using machine learning to do pattern recognition to diagnose cancers is not something humans can do at scale. So on the one hand AI is focused on 20th century objectives with limited real benefit and on the other hand is being used for state of the art medical diagnostics of potentially enormous benefit.

The takeaway is that with new technologies we should look for new ways to use them and not fall into the trap of re-using them in old ways.

How soon will we kill off humans?

You might think this would be a post on the environment, but it is actually about what might be a bigger threat to the extinction of humans. For the first time in history we now have the ability to interfere with evolution. 

An article on autism helped me to see this point. The silly article was about whether we should use the word "cure" when talking about autism. The week before a student had presented the idea that the autistic might be the next evolutionary species in the human line (Neanderthal, Homo sapiens sapiens, etc.) Novel idea, particularly from an 18 year old student. I have no opinion on such a question particularly given my lack of expertise on autism. Obviously if we "cure" autism we might very well kill off the future direction of human evolution. 

Such an issue is of particular interest to me when I consider morality. After a very good education in meta-ethics, I now think that much of morality should be concerned with "not doing harm to future generations". Plato did not have much to say on genetics or the environment, but these topics look very relevant today.

To think the government might have to legislate on evolution is very scary, especially when one considers that humans are not really built to survive. Cock roaches, alligators and turtles are all very old surviving species. We  humans share very few characteristics with these species. 

My Summer Reading List

This year's reading list is shaped in part by a new course I want to teach, "Cognition, Neuroscience and Artificial Intelligence". Also, I am still trying to answer some questions for a new book on market opportunities. All of this is increasingly tied together by my growing interest in evolution and biology. For several years I have told my students to think like ants. Now I have enough background to defend the position.

The recommended readings are:

1. "The Master Algorithm" by Pedro Domingos  The book is a history of artificial intelligence with a focus on machine learning (no math). The notion of a master algorithm that can create all knowledge is a very interesting idea.
2. "Money Changes Everything" by William Goetzmann  A history of money. Should be the first reading in every introductory finance class.
3. "Our Mathematical Universe" by Max Tegmark  Reconsiders the age old question of what is reality. 
4. "The Invention of Nature" by Andrea Wulf  A biography of the first naturalist scientist--Alexander von Humboldt
5. "The Evolution of Everything" by Matt Ridley  Questions many traditional explanations of issues and shows that evolution is a better explanation
6. "The Pre-history of the Mind" by Steven Mithen  Scholarly work on the cognitive origins of art, religion and science.

 

 

The New Approach to the Environment

In the last few months various initiatives at MIT have signaled a change in approach at that university toward environmental problems. (I am not sure this is an institutional view and might just be the view of various groups within MIT.)  No longer is there time for long term solutions and changing human behavior. Problems must be solved now before it is too late. Other organizations I am sure share this proactive approach which goes well beyond mere conservation.

A story on Medium, "How an Army of Ocean Farmers Are Starting an Economic Revolution", describes a new way to do ocean farming that immediately reduces environmental issues, but provides almost a balanced diet from the ocean. A point that did not occur to me until I read the article is that all life began in the ocean. Therefore the ocean has the ability to provide all the nutrients to keep us alive. Land-based alternative sources of nutrients required less energy so early man moved away from the ocean as a principal food source. Scaling may have also been an issue in an ocean food supply. As the article shows, the ocean can be a more environmentally friendly, highly productive food source with modern technology. We may have to go back to our origins to survive.

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Entrepreneurship and Complexity

Are the Doctors Ready for the Future of Healthcare

Beta Boston has a nice story, "I’m a physician, and I saw the future of medicine at CES", about a doctor's visit to this year's CES show in Las Vegas. The doctor enthusiastically describes several devices that will improve healthcare. Right after reading the article I received a phone call. Transcript follows.

(Names are changed to protect the ....)

 

Caller: This is Dr. Bozo's office calling to confirm an appointment tomorrow with Dr. ...

 

Me: I responded to the text message to confirm the appointment; why are you calling me?

 

Caller: No one monitors the text messaging system for responses.

 

Me: Why do you send them out and waste my time?

 

Caller: The system sends the texts out and people don't all respond so we call everybody

 

The doctors may have great devices to use, but I am not so confident they will use the equipment in the most effective way.

 

Forecasting, Prediction and the Future

I spend quite a bit of time considering the future. This practice started in Indonesia where I had to consider the future in order to mitigate risk. Since Indonesia I have tried to predict the future in order to better understand technology. This thinking has led me as well to take a serious interest in the nature of the customer experience and how it will evolve. All of this thinking about the future hopefully also has some positive impact on my teaching of entrepreneurship. 

Steve Jobs once asked his former boss, Nolan Bushnell, “How in the world do you figure out what the next big thing is?" Bushnell answered:

"You’ve got to figure out how to put yourself into the future and ask what you want your computers to be able to do"

I rarely think about the future of technology this way but the technique looks imminently reasonable after Bushnell points it out. Excellent advice for an aspiring entrepreneur.

Lately I have been reading Our Mathematical Universe: My Quest for the Ultimate Nature of Reality by Max Tegmark. While the book largely deals with cosmology, the origin and development of the universe, the part I find more fascinating is the scientific methods used by the scientists. Given that the universe began around 14 billion years ago, many of the problems are very complex. One technique is the reverse of Bushnell's approach. The scientists know the status of the universe today from observations. Therefore, they assume what had to happen 14 billion years ago according to quantum mechanics to explain today's universe. Then they look for empirical eveidence to support their assumptions about the start of the universe. A lot of math later, if the empirical observation matches the assumption about the beginning of the universe, then the assumption is correct. If the assumption is proven wrong, it may actually mean that the question asked in making the assumption was wrong. Another example of the importance of asking the right question.

Bushnell says to assume the future you want. The cosmologists assume the past to prove their theories. No guessing about the future or the past. Assume what you need and then develop  it.

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Physics and Economics

A story at the Santa Fe Institute led me to this fascinating article, "Arrogant physicists — do they think economics is easy?". A few quotes from the article.

1. "This is precisely why many physicists, myself included, are convinced that modern economics is indeed, in an important sense, “held back because of a deficiency of mathematical tools and techniques”
2. "The economy is a vast and complicated set of arrangements and actions wherein agents—consumers, firms, banks, investors, government agencies—buy and sell, speculate, trade, oversee, bring products into being, offer services, invest in companies, strategize, explore, forecast, compete, learn, innovate, and adapt. In modern parlance we would say it is a massively parallel system of concurrent behavior. And from all this concurrent behavior markets form, prices form, trading arrangements form, institutions and industries form. … One of the earliest insights of economics—it certainly goes back to Smith—is that these aggregate patterns form from individual behavior, and individual behavior in turn responds to these aggregate patterns: there is a recursive loop. It is this recursive loop that connects with complexity. Complexity is not a theory but a movement in the sciences that studies how the interacting elements in a system create overall patterns, and how these overall patterns in turn cause the interacting elements to change or adapt. … Complexity is about formation—the formation of structures—and how this formation affects the objects causing it." Brian Arthur Complexity Economics
3. "To look at the economy, or areas within the economy, from a complexity viewpoint then would mean asking how it evolves, and this means examining in detail how individual agents’ behaviors together form some outcome and how this might in turn alter their behavior as a result. Complexity in other words asks how individual behaviors might react to the pattern they together create, and how that pattern would alter itself as a result. This is often a difficult question… And so economics early in its history took a simpler approach, one more amenable to mathematical analysis. It asked not how agents’ behaviors would react to the aggregate patterns these created, but what behaviors (actions, strategies, expectations) would be upheld by—would be consistent with—the aggregate patterns these caused. It asked in other words what patterns would call for no changes in micro-behavior, and would therefore be in stasis, or equilibrium." Brian Arthur Complexity Economics

Interesting notion that economics was in part defined by the math available at the time.

I also find the description of economics as a complex system one of the better descriptions of complex systems. This could, however, just be explained by the fact I understand more about economics than physics or quantum mechanics.

A related article from Santa Fe Institute.

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Networks, Organizations and Math

If you have not been paying attention, more and more of what was considered random behavior is now being explained by math. To satisfy this standard of explanation, the math must be able to accurately forecast behaviors. Several good examples of this evolution in math, or perhaps more precisely in the understanding of social behavior, are seen in Sandy Pentland's new book, "Social Physics: How Good Ideas Spread-The Lessons from a New Science". Interesting discussion of social networks, information flows and how to modify behavior. Anyone who appreciates "big data" should read the book. Pentland's proposed policies on privacy and transparency make the book worthwhile even if you do not care about big data. Implications for the nature and role of government are the best partof the book in my opinion. 

Another example of math being applied to social organizations is the work of Geoffrey B. West, “Why Cities Keep on Growing, Corporations Always Die, and Life Gets Faster”. West trained as a physicist and late in his career turned to studying the growth pattern of cities. Regardless of location around the world, culture, type of government, etc, cities behave according to certain mathematical rules. Cities also exhibit certain properties that insure they last forever, whereas companies and people have properties which explain a definite lifetime. Maybe we should encourage the return of city states. Maybe Shanghai has already reached that status.

One should not overlook the irony that computers are crunching the numbers to explain more and more of our lives by numbers. The pace at which we approach the world of Ray Kurweil is perhaps accelerating. "How to Create a Mind, the Secret of Human Thought Revealed" by Ray Kurzweil. Fascinating book.

 

 

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AI, Jobs and Government

Lately I have been reading Ray Kurzweil's "How to create a mind: the secret of human thought revealed". The book deals with the history of neuroscience, AI and thinking, with a dash of epistemology and meta-ethics thrown in for completeness. One of those rare books where you read for twenty minutes, go away and think about what you read for several days and then read some more. Kurzweil's book provides much of the intellectual underpinning for an article in The Economist,"Technology and jobs: Coming to an office near you". 

The Economist chronicles the upcoming dislocation in jobs, with computer technology replacing up to 47 percent of jobs in the next 20 years (numbers very similar to other sources I have seen). Basically artificial intelligence and their devices, what you call robots, have advanced to the point where many traditional jobs can be done by devices of one type or another. You have been following Google's driverless cars and contact lenses to measure sugar levels for diabetes patients?

Back to Kurzweil, who along with Marvin Minsky and Herbert Simon (founders of AI), point out that AI and neuroscience advances are teaching each other about their subjects. AI teaches us about neuroscience and neuroscience helps us to improve AI, all with the outcome of computers increasingly approaching the abilities of the human mind. I think Kurweil might be saying that critical thinking may be the only function of the brain/mind that cannot yet be duplicated through a computer. 

This increasing sophistication in AI suggests that the disruption to jobs may be underestimated significantly and especially by the governments in developed countries such as the U.S. While certain governments talk about wealth concentration, this is just a number of no consequences. Popular politically but of no consequence in the lives of ordinary people. Jobs might be the better issue but the government does not have a solution, which is why they are distracting us with the speciousness of wealth concentration.

Actually, the issue the government needs to address is how do people need to be educated and trained to live productively (economically) in a world where computers and robots will be able to do 90-95% of all the work performed in 1900.  Governments are not designed to handle environmental change of such consequence. Governments manage status quo adequately but do not shine in rapidly and dramatically changing environments they have not seen before. Governments can barely handle a hurricane let alone the complete disruption of the labor force...in the U.S. Perhaps the days of government as "Big Brother" are numbered. Perhaps the private sector will need to take more responsibility. I guess organized religion is another alternative. Probably does not matter where the solution comes from, but someone needs to prepare people for this new world where AI plays a bigger role.

Sounds like a business opportunity to me. Maybe the charter schools were just practice for a declining role for government.

Pattern Recognition

I am not much of a game player, except for an interest in Texas Hold'em. I believe that computer games offer a new way to improve children's learning, but it is not an area that interests me. A recent article in Wired, "How an Entirely New, Autistic Way of Thinking Powers Silicon Valley" got me thinking about Go and chess, two of the oldest and most popular games in the world. Go was developed in China in the 4th century BC and chess was invented in India in the 6th century. Why have these games been so popular for so long.

Both Go and chess are widely admired as complex strategy games, which in part explains their popularity. However, it may be that the popularity of both games is also because they develop a different way of thinking--paternicity or pattern recognition. Patern recognition may be a third way of thinking, in addition to visual and verbal. The Wired article states:

"For a century now, chess has been the petri dish of choice for cognitive scientists. What makes a chess master a chess master? Definitely not words. But not pictures, either (which is what you might think). When a chess master looks at the board, she doesn’t see every game she’s ever played and then find the move that matches the move from a game she played three or five or twenty years earlier or from a nineteenth-century chess match that she’s studied closely. The stereotype of a chess grand master is someone who can think many moves ahead. And certainly, many chess players do strategize that way. But the grand masters retrieve from their memories not more possibilities but better possibilities because they are better at recognizing and retaining patterns or what cognitive scientists call chunks."

While everybody uses visual, verbal and pattern recognition ways of thinking, certain disciplines generally require a particular way of thinking. For example, pattern recognition is widely used in mathematics, engineering and certain sciences. Pattern recognition is also an important skill in programming, as the Wired article explains.

John Von Neumann, the great 20th century mathematician, said that chess was "trivial" because at any point in a game one could identify all the remaining moves in a game (with enough computing power). Watson, the IBM computer that beat the world chess champion in 1997, perhaps proved Von Neumann correct. However, in this case the computer was programmed to utilize a Von Neumann type strategy and not pattern recognition. Never the less, Chess remains widely popular, and approached correctly, can develop pattern recognition skills. Go offers the same way to improve one's thinking.

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Philosophy and Physics

George Polya, the famous Stanford math professor, once quipped " I am too good for philosophy and not good enough for physics. Mathematics is in between". Amongst the many implications of this quote, Polya implies that there is a relationship between philosophy and physics.

The intersection of philosophy and physics is an admittedly escoteric subject but a great example of interdisciplinary thought. However, as physics advances and becomes increasingly complex, the challenge is for the philosophers to understand the physics and identify the philosophical questions that must be considered. The discipline that addresses such issues is the philosophy of science.

The philosophy of science deals with "what science is, how it works, and the logic through which we build scientific knowledge". Building scientific knowledge requires a theory of epistemology, albeit a somewhat specialized epistemology or theory of knowledge. Philosophers were doing a good job of keeping up with the physicists until recently.

The Guardian newspaper has a great article on the three possible roles for the philosophy of science, as physics and perhaps all science gets increasingly complex. The three possible roles, as defined by Peter Godfrey-Smith, are:

1. an integrative role, whereby philosophy can assess and connect various fields with an emphasis on generic categories and perspectives; 
2. an incubator role, where philosophy develops new ideas in a broad and speculative form, which are then pursued in a more focussed and specific way within an individual science; 
3. an educative role, where philosophy teaches various general skills, including critical and abstract thinking

I will leave it to to your own deliberate thinking to decide which role you believe is the right course for the philosophy of science to pursue, although the Guardian writer argues for one particular role.

Now you may be wondering why I wrote this post on a subject for which the term "esoteric" might be an understatement. My three reasons are:

1. To demonstrate that philosophy is still relevant in the modern world
2. To show that the complexity of science has many implications, to which I think we are paying insufficient attention
3. To highlight a great example of interdisciplinary thought--the philosophy of science

I also think the Guardian should be commended for writing on such a learned subject. Other posts on public intellectualism are here, here and here.

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Competence and Comprehension

One of the debates that I have been following is framed as follows:

Do we need to teach aritmetic if computers can perform the same task?

Until today I thought we should teach arithmetic.

Another related question is why we cannot develop computer software that does more than traditional teaching methods.

This article from Atlantic, "A Perfect and Beautiful Machine': What Darwin's Theory of Evolution Reveals About Artificial Intelligence" provides insight on both questions. This quote provides a possible answer:

"What Darwin and Turing had both discovered, in their different ways, was the existence of competence without comprehension. This inverted the deeply plausible assumption that comprehension is in fact the source of all advanced competence. Why, after all, do we insist on sending our children to school, and why do we frown on the old-fashioned methods of rote learning? We expect our children's growing competence to flow from their growing comprehension. The motto of modern education might be: "Comprehend in order to be competent." For us members of H. sapiens, this is almost always the right way to look at, and strive for, competence. I suspect that this much-loved principle of education is one of the primary motivators of skepticism about both evolution and its cousin in Turing's world, artificial intelligence. The very idea that mindless mechanicity can generate human-level -- or divine level! -- competence strikes many as philistine, repugnant, an insult to our minds, and the mind of God."

The distinction between competence and comprehension provides a possible answer to both questions. Competence does not lead to comprehension. We do not need to teach to achieve competence in arithmetic because computers can do it for everybody (with a computer and electricity). Comprehension in math, the higher level objective, is a totally different objective which is not necessarily derived from competence.

This distinction also explains the weakness in current educational software and most online offerings. Rather than using software/content to teach competence, we should focus on developing software to facilitate reasoning and comprehension. Perhaps harder said than done, but if we stop focusing on competence we will be on the right path.

Question: How many numbers between 0 and 10 can be divided by 2

Competence answer: 2,4,6,8,10

Comprehension answer: all the numbers

I found the Atlantic article on Arts & Letters Daily.

 

Integrating Science, Engineering and Ethics

I have been re-reading Richard Hamming"s "The Art of Doing Science and Engineering". It always amazes me the range of subjects that great thinkers can integrate. This quote demonstrates my point:

"What is possible?

What is likely to happen?

What is desirable to have happen?

In a sense the first is Science—what is possible. The second is Engineering—what are the human factors which choose the one future that happens from the ensemble of all possible futures. The third is ethics or morals or whatever other word you wish to apply to value judgments. It is important to examine all three questions, and in so far as the second differs from the third, you will probably have an idea of how to alter things to make the more desireable future occur, rather than let the inevitable occur and suffer the consequences."

Creativity and Failure

Marvin Minsky at the KI 2006 artificial intelligence conference in Bremen (Photo credit: Wikipedia)

I have never thought of myself as creative. I am not a designer or developer, whether it be software, music, poetry or new devices. However, I am a student of the creative process and a big believer that techniques, such as heuristics, can be used to help creativity. Relax the Assumption is such a technique.

I have also found that many great thinkers were students of creativity, such as these comments from Marvin Minsky, a legendary MIT professor. Thoughts on the creative process from three other notable thinkers, Hamming, Austin and Munger, are here, here and here.

To substitute for creativity, I use an iterative process. In other words, I keep trying solutions until I find a satisfactory solution. The use of heuristics and other techniques makes the iterative process more efficient. The iterative process requires doggedness, a willingness to not give up, and it works for me most of the time. What I have learned over time is that when I cannot find a solution to a problem I usually have the problem framed incorrectly. Re-thinking the problem, rather than continuing to look for a solution, usually does the trick. 

So rather than trying to be "creative", find your own process for how to solve problems and believe in the process so you have the determination to see it through to the end.

Just saw this quote from Jonah Lerner on Mashable.com from a very good article on creativity:

"Because innovation is hard. If it were easy to invent an idea, that idea would already exist. Creative success is not about the avoidance of failure. It’s about failing as fast as possible, going through endless iterations until the idea is perfect."

U.S. Military Leads Change Again

Image via Wikipedia

The U.S. military is a popular target for criticism and worse. This is especially true during the current two war period. What is frequently forgotten is the social contribution made by the U.S. military. In my lifetime I would point to two major accomplishments:

1. In the 1950s the U.S. military was the first major organization to eliminate segregation and foster an environment of non-discrimination
2. In 1969 DARPA, a part of the Defense Department, began the research that lead to the Internet

Today the military is at the forefront in research and development of unmanned aircraft and vehicles. I believe that such equipment will be commonly available to citizens for their every day use within twenty years.

Despite the controversy over global warming and Washington's unwillingness to address the problem, the military is aggressively expanding its use of solar power. This story from Fast Company highlights Project Solar Strong (ok-the name is a little hokey). Solar Strong is a project to provide solar power to 160,000 military residences in the U.S.

One could argue that all this technology was originally developed for war fighting, but that misses the point. The U.S. miliatary is a major force for positive change in the U.S. and much of our way of life is due to their leadership in our society.

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Lessons from 100 Years at IBM

I found the video below on the history of IBM at Engadget. The video makes several important points about entrepreneurship. The implicit point in the video is that the best survival strategy is to stay close to the customer. The explicit points in the video are:

1. Solve big problems (put a man on the moon)
2. Change the market (barcode technology)
3. Do the impossible (the personal computer?)
4. The paradigm shift in computing technology was to make information user-centric through ease of access

Watch the video. There are 20 other lessons in entrepreneurship and a nice section on IBM's history of leading on social issues. One thing about great companies is that they are consistently great in every facet of their business.

 

Certain Truths are Inevitable

"The Universe is a grand book which cannot be read until one first learns to comprehend the language and become familiar with the characters in which it is composed. It is written in the language of mathematics."  Galileo Galilei

Some further, perhaps more practical thoughts on mathematics and mathematics education are here. 

Quote: Source

Image  

The Science of the Brain May Define Customer Need

This weekend I attended an education conference sponsored by One Laptop Per Child. One of the presenters made an interesting comment “we know how to educate children...the technology (computers) is satisfying different needs". Traditional education begins worldwide at five years old and focuses on memorization as the principal methodology. Why do we start at five years old? At that age the brain is capable of reading, as discussed by Stanislas Dehaene in Reading in the Brain. Basically our experiences showed us when humans could begin to read and science confirmed this conclusion about four thousand years after we started reading.  

The next speaker up talked about teaching and the fact that humans are the only animals capable of teaching. In fact humans demonstrate teaching skills at 2-3 years old, as confirmed by scientific research described by Antonio Battro. We learn to teach before we learn to read. This development path suggests that in teaching young children we should perhaps be focusing on their own abilities as teachers more and rely less on their ability to read.  

If you think about the true objectives of teaching they are arguably to encourage creativity, foster better reasoning and develop collaboration skills. This method of teaching is what OLPC develops through the use of its computers. The computer is satisfying the higher level needs of creativity, reasoning and collaboration of the young "teachers" which may go unsatisfied in a memorization approach to learning. Now for the big inter-disciplinary leap…at least for me...to entrepreneurship.  

Many of us traditionally focus on science and technology as a means to satisfy a customer need. However, as the example above shows, science highlighted the human need. The research on the human brain shows that teaching abilities precede reading abilities. We have built an education system to satisfy a need perhaps based on the wrong premises, as shown by the pure science. Education should be encouraging the teacher in all of us more and the reader less (or maybe later).  The point here for entrepreneurs is that with the continued research into the human brain, science will be defining or at least giving us new insights into understanding the customer need. Now we should be following this science of the brain not only for its application value but also for its value to give us more profound understanding of the customer. Effectively, understanding customer need has now moved beyond an emotional or psychological approach to include the development of the human brain.

Note: (1) One technique for finding breakthrough ideas is to look at where different disciplines intersect. The three disciplines examined here are pure science (biology), education and entrepreneurship. I do not assume that there are any great thoughts here but the post may illustrates the potential power of the methodology; (2) for parents with children that have reading and dyslexia issues Reading in the Brain may be helpful.

Image credit

MIT Entrepreneurs have $2 Trillion in Annual Sales

This is my week to get great stuff from readers. Please keep it coming.

A reader sent me a story from Xconomy about the economic contribution of MIT graduates. According to a study completed by two MIT professors, worldwide alumni of MIT have created operating companies with an estimated $2 trillion in annual sales. For the quantitative reader, each of the 119,000 alums of MIT contribute average annual sales of approximately $16 million. Setting aside any prejudice on the part of the professors, both numbers are staggering!!

It is well documented that the highest concentrations of entrepreneurship and VC money are nearby to great universities such as MIT and Stanford. Research revenues at MIT in 2006 (last year available) totaled $570 million and a substantial portion of that funding came from the U.S. government. Makes one wonder if more money for MIT and the other great universities in the U.S. would not have a more positive effect on the economy (in the medium term) than the current efforts in Washington.