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Tag: Craigslist

The Invisible Currency Among Us

Liquid Swords - by Megan Olson

Liquid Swords - by Megan Olson

Invisible Currency

On my birthday, I received many greetings on Facebook from friends and family.  So, let’s say for example that Hallmark sold 10 less cards (@$3.95 ea), the telephone company sold 10 less long distance phone calls phone calls (@$.60 minute),  FedEx delivered no additional packages, oil companies sold no gas, and my friends did not deploy, say, 20 hours (@$25/hr) of human productivity buying stuff, licking stamps, or delivering mail in my honor.  Total productivity savings can be valued over $500.00; or roughly $50.00 per message.

Conversational Capital

One billion messages are sent on Facebook every day.  Each message sent and received constitutes a conversation.  Each of these conversations has a value that can be expressed in terms of productivity saved and assigned a dollar value. Suppose that each Facebook message has a value of only $1.00 per person engaged in a conversation.  That comes out to 730 Billion dollars per year of human productivity saved – enough to fund TARP.

Twitter is worth a cool 100 Million tweets per day.  Let’s assign a net productivity gain of $1.00 per tweet sent (not received).  If you think that tweets are not productive, follow the Iran Crisis; a revolution fought with liquid swords.  So let’s assign Twitter $36 Billion per year in increased human productivity.

Next, according to Google analytics, about 100 real people spend enough time on my little blog every day to read at least one article.  Suppose each blog article increases human productivity by $1.00 each. Technorati tracks well over 100M blogs.  That is 10 billion dollars per day – or a whopping 3.6 Trillion dollars per year.  Let’s discount that by 50% to only $1.8T in fairness to the skeptics.

The grand total is 2.5 Trillion Dollars worth of conversational currency – 2 times the 2009 national deficit and 5% of America’s entire debt obligation – and growing.   Where is all this productivity going?

What’s happening is what’s not happening.

People are NOT sitting through hours of TV commercials anymore.  People editorialize their own news and do NOT watch what is designed to corrupt them.  People are NOT letting their ideas die unheard.  People are NOT letting politics run them down and have now elected health care, the environment, and the end of warfare to the Presidency of this and other nations.  People have become far more focused and more productive through the rediscovery of family, friends, Art, Music and social priorities over debt enslavement.  Next, social media is coming to the neighborhoods.

Millions of people practice “social media” in their spare time.  This is invisible productivity that effectively magnifies the productivity of others with an astonishing multiplier effect.  Craigslist, CarFax, Zillow, Epinion, Amazon, and Expedia are all eliminating arbitrage opportunity and sending brokers scurrying for a real education. Product reviews are killing the scams and delivering the right product to the right market.

The Anti-buck

Maybe the Dollar is not so overvalued after all. Maybe the dollar deficit is counter balanced by this new invisible currency.  Suppose the more inflation that occurs, the more this invisible currency will affect the overall economy.  Suppose people are hedging dollar currency with conversational currency.  Suppose social priorities are replacing Wall Street Priorities.  Suppose we are approaching a new equilibrium rather than an impending free fall – except for those who try to control it.

Special Thanks to Megan Olson

The Next Economic Paradigm; Part 4: Institutions

In part 1, we introduced a new paradigm of economic growth; the innovation economy. In part 2, we identified information as the currency of trade for an innovation economy and we defined that currency’s relationship to knowledge and innovation.  In part 3 we demonstrated a structure for a knowledge Inventory that would enable an Innovation Economy.  In this module, we will discuss the institutions in social media that could keep an Innovation Economy, free, fair, and equitable.

In civil society, there are laws and regulations that protect our constitutional rights; these are essential institutions.

The legal system of the United States is extremely expensive, however, the expenditure is necessary to keep the society upright, productive and prevent it from falling into chaos.  Where a country’s legal system fails, so does its economy.  Entrepreneurs do not invest in places without a good legal system and where property rights are not protected. It is that important.  Investment abhors risk.

Arguably, the most important element of the Innovation Economy will be the vetting mechanism.

Fortunately, social media has the potential to serve this function; in fact in many cases it already does.  A feedback system supports Ebay ($35B Cap), community flagging supports Craigslist (40M ads/mo), peer review supports Linkedin (150M users).  These are not small numbers.  All markets must have a vetting mechanism in order to operate efficiently and if done correctly, social vetting has vast economic implications for an Innovation Economy.

First, let’s return to our financial analogy.

In the old days, the banker was the person to know if you wanted to be successful in town.  But with the emergence of the credit score, the “banker” became digitized; now a Saudi Billionaire can lend money to a young couple in Boise to buy their first home – and neither is aware of the other.  The credit score is responsible for the creation of great wealth because many more entrepreneurs could borrow money to invest in enterprise.

The credit score is statistical in nature; it isolates about 30 or so indicators of your financial activity and puts them on a bell curve relative to everyone else.  These include how much debt you have, how much your assets are worth, your income, etc.  These ratings are run through the FICO Equation and out pops your credit score.  Anyone can now predict the likelihood that you will default on your obligation.

All of the data that feed FICO are collected from public records, your employer, and the people who you borrow money from because these same organizations have a vested interest in a system of correct credit scores.

We are competing with ourselves.

It is interesting that you and I do not compete for our credit score because it is not a ranking system. On the other hand, with no credit, we are invisible and the system shuts us out.  With bad credit, the system shuts us out. We lose some freedom and privacy, but we accept these terms well because they provides us with tremendous benefit to finance a business, automobile, or a home without needing to save cash.

Now we will draw the comparable analogy from the social media.

In the old days, the hiring manager was the person to know if you wanted to get a job.  They would read your resume and compare it with “bell curve” in their experience about what has worked or not worked in their past.  This worked great in the industrial economy, but it falls far short in the innovation economy.  Innovation favors strategic combination of diverse knowledge where the Industrial economy favored identical packets of similar knowledge.

Not unlike the FICO score, the knowledge inventory is a collection of statistical variables and the social network is the reporting agencies who have a vested interest in a system of correct values.  Unlike FICO however, the variables are infinite and it responds to positive event input.
Social networks are by far among the most exciting and important new technology for an Innovation Economy.

Social networks must now evolve to become the vetting institutions for knowledge assets.

All the pieces are almost in place; now we need to develop a new type of search engine.

The Percentile Search Engine is generic term for the ability to make statistical predictions about all types and combinations of knowledge Assets in a network. Conceptually, the percentile search engine is where all of the equations that we use to analyze financial assets are now applied to knowledge assets.  The main characteristic is that the search engine returns probabilities for the entrepreneur to test scenarios.

For example; an entrepreneur may want to know if her team has enough knowledge to execute a business plan.  Perhaps the team has too much knowledge and they should try something more valuable.  Maybe the team does not have enough knowledge and they should attempt another opportunity or accumulate training.

The search engine can look into a network and identify the supply and demand of a knowledge asset. If it is unavailable or too expensive, the search engine can adjust for price, risk, or options that may emerge at a later date.

Talent will bid up to their productivity value, and brokers will bid down to their productivity value.

Competitors can scan each other’s knowledge inventory to compete, cooperate, acquire, or evade. If a key person retires, the entrepreneur would simulate the knowledge that is lost and reassign people strategically. All of these scenarios can be examines prior to spending money. They can be made during the project cycle, or after the project is completed.  Lessons learned can be used to adjust the algorithm perfecting it over time.

For example: companies such as Disney and Boeing both use Engineers, each would have proprietary algorithm of knowledge that represents their “secret sauce” of success. These recipes can be adjusted and improved to reflect and preserve the wisdom of an organization.

When the innovation economy will catches fire….

Over time, these algorithms will far more valuable then the Patents and Trade Secrets created by them – this will allow technologies to be open sourced much more profitably and shared across more industries.

In the next module, we will talk about the entrepreneurs.

The Credit Score Analogy; Part 2

Now we look for a similar situation for Knowledge Markets.

In the cuurent times, the hiring manager is the person to know if you want to get a job. The manager would read your resume and compare it with “bell curve” in their brain about what has worked or not worked in their past. This was a great system for the industrial economy, but it falls far short in the innovation economy.

The world is evolving so fast with new technology, new disciplines, and global cultures that what worked in the past may not work in the future. Innovation favors different combinations of knowledge where the Industrial economy favored similar knowledge. A hiring manager may not accumulate sufficient experience in a lifetime to make a proper assessment in the complexities of a diverse, global, and technical future market.

If we look in society, there are many vetting mechanism in place. Social networks are by far among the most exciting and important new technology that can serve this purpose. Social networks must now evolve to become a local vetting mechanism for knowledge assets.

Just like the reporting agencies in the credit system, Social Networks can serve an extremely valuable function in permitting human knowledge to emulate a financial instrument by acting as the “Recording Agencies” who have verified the asset in terms of quality and quantity. The knolwedge Inventory acts as the independent variables that are used to calculate the probability of market success. The difference is that the credit score measures mostly negative events while the new system will seek only positive events and can be designed to give the participants much greater influence on how they appear to the market.

One thing is missing. The credit score uses the FICO equation; Innovation Economics will use something called the Percentile Search Engine.

The Credit Score Analogy; Part 1

We have defined the currency, the factors of production, and the inventory of the Innovation Economy; we destroyed the old resume system and turned it into a computer language that makes knowledge appear like money in the eyes of the entrepreneur.

Now, we need a system that keeps the game free and fair. For example; EBay does little more than protect the feedback system, Craigslist uses community flagging, Linkedin keeps track of comments and contacts, etc. All markets must have a vetting mechanism in order to operate efficiently. Entrepreneurs do not invest in places without a good legal system and where property rights are not protected. When vetting fails, investors leave – It is that important.

In the Innovation Economy, the knowledge market is analogous to the credit market.

In the old days, the banker was the person to know if you wanted to be successful in town. If you needed to borrow money to start a business or buy a house, the banker would review your work history and financial records as well as your reputation in the community where you both live. If you were deemed an acceptable risk, the banker would lend you money from the deposits of local companies and individuals.

Then an engineer named Bill Fair and mathematician Earl Isaac created the first behavior scoring system to predict credit risk. They formed the Fair Isaac Corporation FICO and their invention came to be known as the FICO credit score. With the credit score, the local banker is almost irrelevant; now a Saudi Billionaire can lend money to a young couple in Boise to buy their first home – and neither of them are aware of the other. The credit score is responsible for the creation of a lot of wealth because it made many more entrepreneurs who invested borrowed money in business. The credit score even allows you to recover if you hit hard times – you just pay more a little interest until you prove yourself solvent again.

The credit score isolates about 22 or so measurements of financial activity and puts them on a bell curve relative to everyone else. These include how much debt you have, how much your assets are worth, your income, etc. These ratings are run through the FICO Equation and out pops your credit score. Anyone can now predict the likelihood that you will default on your obligation.

All of the data that feed FICO are collected from public records, your employer, and the people who you borrow money from – all of these organizations have a vested interest in a system of correct credit scores.

It is interesting that you and I do not compete for our credit score because it is not a ranking system. The old saying “No credit is worse than bad credit”, although inaccurate, is cited often because with bad credit, you are visible to the system and it can adjust to find a suitable interest rate. With no credit, you are simply invisible.

We lose some privacy with FICO, but we accept these terms well because they provides us with tremendous benefit to finance a business, automobile, or a home without needing to save cash. Likewise, we lose some privacy engaging each other on the Internet and in our community, however, the benefit of Social Networks far exceed many perceived privacy issues.

My personal complaint with credit scores is that they track largely negative events and seem to predict failure. What if we had a system that tracks success and used that data topredict varying degrees of success.

In the next section, we will identify the institutions that exist in society and how Social Networks can act to duplicate the benefits of the credit score without the downsides….watch

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