AI will create far more content than humans can consume.
Fortunately, people can just use Artificial Intelligence to interpret all of their Artificial Intelligence. What could possibly go wrong?
In reality, nothing “economic” happens until two or more people come together and make something useful.
Search Engines of the future must therefore identify the most worthy knowledge surplus and match it to the most worthy knowledge deficit in order to achieve a net productivity gain.
That is what opportunity, equity, and access are made of.
That’s what innovation is made of.
That is what money is made of.
The Ingenesist Project uses game theory, blockchain technology, and artificial intelligence to convert intangible assets to a more tangible form.
Artificial Intelligence (AI) is frequently mentioned for its capacity to blur the lines between facts and fiction. Numerous articles envision a future in which AI bots construct believable scenarios without relying on direct observation. Many instances illustrate the potential pitfalls of this. So, if AI can excel at finding the best incorrect answer, why can’t it excel at finding the best correct answer?
In this early stage of widespread AI and machine learning adoption, many proponents acknowledge the necessity of human involvement in the learning process. This raises the age-old question: “Who can we trust?” This is especially pertinent when the incentive is to replace humans with machines. The enduring challenge (and opportunity) is to avoid wholesale human replacement and instead focus on enhancing human abilities with the aid of new technology.
Economics is fundamentally driven by incentives.
The Ingenesist Project’s Innovation Bank provides an ideal environment for AI and machine learning to prioritize facts over fiction. Through a strategic blend of game theory, blockchain technology, and AI, The Innovation Bank introduces an alternative set of incentives that guide participant actions. The Innovation Bank serves as a self-regulating truth engine, safeguarding society against malicious actors attempting to disseminate unfounded or fraudulent claims.
A Multi-Agent Algorithmic Game:
In essence, The Innovation Bank operates as a game in which participants make claims about the state of the world, which must then be validated by other participants. Each participant is rewarded with an electronic token for creating an immutable node on a network graph. As the network expands, the graph accumulates increasingly valuable business intelligence. Accessing this intelligence requires the expenditure of tokens, potentially purchased by institutional users from a third-party clearinghouse. This system eliminates incentives for cheating.
Natural Language Processing (NLP):
AI-powered NLP algorithms can scrutinize the language used in node creation, detecting patterns, inconsistencies, or suspicious elements. NLP models understand context and semantics, enabling them to identify potential fraud or falsehoods. NLP also assists in verifying claims by cross-referencing them with external sources (validating the validator).
Data Analysis and Pattern Recognition:
AI can process and analyze vast amounts of blockchain data to uncover patterns and anomalies. By comparing multiple claims and validations, AI can identify discrepancies or abnormal behavior indicative of fraud. These capabilities help distinguish genuine claims from fraudulent ones, with no incentive for dishonesty.
Image and Video Analysis:
In cases involving visual evidence, AI employs computer vision techniques to analyze images or videos for authenticity. AI assesses image metadata, detects alterations, and evaluates facial expressions and body language to spot potential manipulation or fraud. Here, the condition arises where crafting a believable falsehood becomes more expensive than simply presenting facts.
Network Analysis:
AI examines the connections between nodes in the blockchain network, identifying suspicious networks or clusters that suggest collusion or fraud. This analysis sheds light on the credibility and trustworthiness of suspect nodes.
Continuous Learning and Adaptability:
AI systems continuously learn from new data, adapting algorithms to evolving fraudulent tactics. Machine learning enhances accuracy in distinguishing truth from fraud, even as the system encounters new forms of deception.
Risk Scoring and Fraud Detection:
AI assigns risk scores to nodes based on factors like proximity to other nodes, validation history, and information consistency. Predictive models identify high-risk nodes or validations, alerting the system to isolate these sources.
Conclusion:
A new economic framework can be seamlessly integrated into existing business methods, creating a condition where falsification is costlier than authenticity. This sharpens the blurry line between fact and fiction. Under this condition, AI can play a vital role in discerning fact from fiction by tracking the creation, circulation, and adoption of digital receipts. AI’s analytical prowess, pattern recognition, and continuous learning ensure the system remains robust at isolating fraudulent activities. The combination of blockchain technology and AI-driven analysis forms a potent framework for curating truthful information and upholding system integrity.
Artificial Intelligence is widely cited for the potential to spoof facts with fiction. Countless articles predict a world where AI bots craft statistical plausibility in the absence of direct observation. Countless examples demonstrate how this can go terribly wrong. So, If AI can be used to find the best wrong answer, why can’t it be used to find the best right answer?
At this early stage of widespread adoption of artificial intelligence and machine learning (AI/ML), many proponents have conceded that human involvement in the learning protocol will be necessary. This leads to the age old problem of: “who do you trust?” – especially where the incentive is to replace humans with machines. The age-old challenge (and opportunity) will be to resist the wholesale replacement of humans and focus on creating a higher order where humans ability is amplifies with the assistance of new technology.
Economics is the Science of Incentives
The Innovation Bank creates an environment ideally suited for AI/ML to anchor facts over fiction. Using a strategic combination of game theory, blockchain, and AI, The Innovation Bank introduces an alternate set of incentives under which participants will operate. The Innovation Bank forms a self-regulating truth engine that can safeguard the health and welfare of society against malicious actors actively trying to pass off unfounded or fraudulent claims.
Multi-Agent Algorithmic Game
Briefly described, the Innovation Bank is a game where players make claims about the state of the world. These claims must then be validated by another player. Each player is then rewarded an electronic token for producing an immutable node on a network graph. As the network grows, its graph stores increasingly valuable business intelligence. In order to access this business intelligence, one must expend tokens. Institutional users would likely need to purchase tokens from a 3rd party clearinghouse listing from those who may seek to liquidate their tokens, thereby giving them a market value based on supply and demand. There is no incentive to cheat.
Natural Language Processing (NLP):
AI-powered NLP algorithms can analyze the language used in the formation of nodes, looking for patterns, inconsistencies, or suspicious elements. By understanding the context and semantic meaning of the text, NLP models can identify potential instances of fraud or falsehoods. NLP can also assist in verifying claims by cross-referencing them with external sources of information (validating the validator).
Data Analysis and Pattern Recognition:
AI can process and analyze large volumes of data within the blockchain to identify patterns and anomalies. By comparing multiple claims and validations, AI algorithms can detect and isolate discrepancies or abnormal behavior that may indicate fraudulent activities. These analytical capabilities help in distinguishing genuine claims from fraudulent ones. Again, there is no incentive to cheat.
Image and Video Analysis:
In scenarios where claims involve visual evidence, AI can employ computer vision techniques to analyze images or videos and determine their authenticity. AI algorithms can assess image metadata, detect alterations, or analyze facial expressions and body language to identify and isolate potential manipulations or fraudulent content. An essential condition is reached where forming a viable falsehood is more expensive than simply providing fact.
Network Analysis:
AI can examine the relationships and connections between nodes in the blockchain network. By analyzing the patterns of validations and associations, AI algorithms can identify suspicious networks or clusters that might indicate collusion or fraudulent behavior. This network analysis provides valuable insights into the credibility and trustworthiness of suspect nodes.
Continuous Learning and Adaptability:
AI systems can continuously learn from new data and adapt their algorithms to evolving fraudulent techniques. By leveraging machine learning, AI models improve over time, becoming more accurate in distinguishing between truth and fraud. As the system encounters new types of fraud, AI can detect emerging patterns and update the validation mechanisms accordingly.
Risk Scoring and Fraud Detection:
AI can assign risk scores to specific nodes based on various factors, such as proximate to other nodes, validation history, and the consistency of information. By utilizing predictive models, AI can identify high-risk nodes or validations, alerting the system to isolate that particular source node.
Conclusion:
A new economic game can be easily inserted to existing business methods to create the essential condition where falsification is more expensive than authenticity. Under this condition, AI can become very useful in isolating fact over fiction by simply tracking the creation, circulation, and uptake of digital receipts. AI’s analytical capabilities, pattern recognition, and continuous learning ensure that the system remains robust and effective in isolating fraudulent activities. The combination of blockchain technology and AI-driven analysis forms a powerful framework for curating truthful information and maintaining the integrity of the system.
In the realm of economic development, the interplay between banking, insurance, and engineering forms a virtuous circle that drives modern civilization forward. However, the crucial role played by engineers, scientists, and technicians in this cycle is often overlooked in economic discourse. Their primary responsibility is to produce material facts, which involves identifying risk exposure, calculating the probability of risks materializing, and assessing the consequences of failures. When these components are harmoniously integrated, finance, insurance, and engineering can collectively support the sustainable and peaceful habitation of our world.
The Virtuous Circle of Economic Sustainability
The Importance of Material Facts:
Material facts are integral to decision-making processes. They are facts whose suppression could reasonably lead to different decisions. However, in our increasingly polarized society, the dissemination of disinformation poses a significant threat to the integrity of material facts. Counteracting this challenge becomes even more complex considering that technology facilitates the creation and widespread distribution of misinformation at an unprecedented scale. Meanwhile, securing material facts requires adherence to a specific sequence, a standard of proof, and an immutable record. This presents a simple problem in need of a solution.
The Role of AI in Securing Material Facts:
Enter the Innovation Bank—an initiative that leverages AI to curate and integrate validated material facts across diverse physical conditions, preempting the risk of disinformation. By acting as a formidable gatekeeper, this powerful system establishes a filter through which disinformation must pass to attain credibility. The value of such a “disinformation filter” transcends individual projects and encompasses the entire economy. Building this AI-driven solution is not only feasible but also imperative.
Join the Movement:
To learn more about the projects spearheaded by The Innovation Bank and contribute to this transformative endeavor, reach out to The Ingenesist Project. Together, we can construct a robust foundation that promotes economic stability, fosters material facts, and guards against the perils of disinformation.
The real estate market is trashed, money markets are unstable, commodities are in the tank, the banking system is corrupted to the core, inflation is looming around every corner, and the politicians are engorging themselves in a game of Gridlock.
There is no safe place to put your money
Instead, people are investing their productivity in social media – social media is simply a storage device for knowledge assets. Soon it will become a stock exchange for knowledge assets. Investors should not take this lightly – the best place to store your money is in the real productivity of real people.
People are trading knowledge assets in social media
This exchange is denominated in social currency. If we mimic the structure of the Financial System with the emerging structure of Social Value Systems, we see a huge opportunity to develop an alternate financial system that can capitalize and securitize knowledge assets in social media.
Bankers don’t care about money, they care about the rate of change of money. At The Ingenesist Project we are not entirely interested in change – we are entirely interested in the rate at which things change. As you can imagine, we get all giddy when we see the rate at which the rate of things change…that’s all that banking is and all that banking ever will be.
Each of the Facebook Applications posted below are to Facebook what The NYSE is to Commercial Banking. Note that Facebook is growing at an astonishing rate. Now, these applications – on top of Facebook – will increase the rate of change of the rate of change in how people communicate, transact, organize, and deliver conversation.
You are hearing it here; these innovations are the most significant disruption that Wall Street can’t possibly imagine. Money is a social agreement and these are the banks of the future. Although many come from the gaming industry, many games are modeled after the real world, therefore, transition back to the real world is not as difficult as one may think. If people are willing to trade it, it becomes money. This is serious business. While many of these new innovations are on the right track – not all of them will survive.
It is only a matter of time until professional contacts will be for sale. The problem is that the ROI (return on investment model) is such a poor valuation tool for social media. Another valuation tool used in finance is called Real Options. An option is the right, without the obligation, to act on an opportunity at some time in the future. Social Networks, friends, family, and professional contacts behave much more along these lines.
Five Easy Pieces:
While the calculation for the value of an option is complex, the things we need to plug in are fairly simple in the context of social media:
1. There must be an inventory of the assets
2. The future date when the asset can be acquired must be known
3. The cost of acquiring the asset must be known
4. The value effects on the enterprise must be estimated
5. The uncertainty related to the asset must be estimated
The term “asset” in social media space may include: Knowledge, skill, an undertaking of a new project, or the generation of a new idea, etc.
The Social Networking Manifesto:
The objective of the building a social network is to know where the knowledge assets are, how much they can help you, how much they cost to exercise, and the certainty that they will be applicable, available and useful when you need them. Conversely, the best way to increase the value of a social network is to be visible to others, tell people what you can do for them, tell people what you need from them, and establish a reputation for reliability.
Most importantly, everyone must have the right, without the obligation, to accept or decline the opportunity. This is what jump starts ‘supply and demand’ and makes a market a market
Let’s consider all options:
To estimate the value of an option to call on anyone in your network use a financial option calculator tool on the web and plugged in social media numbers. Let’s use Linkedin as the knowledge inventory; 40 million knowledge assets also hold options with their contacts. Say that the expiration date is 1 year (for tax reasons). Assume the market value of their skill is 100 dollars and that at some point in the next year, the value of their skill relative to yourself becomes 200 dollars. The right to buy the asset at the earlier price is worth a premium. Suppose that the volatility of the asset is 50% and the interest rate is 7%.
The value of the “call” is worth about $3.47 dollars. The Call is an option contract that gives the holder the right to buy a certain quantity of an underlying security from the writer of the option, at a specified price up to the specified expiration date.
The value of options in a network:
For the above scenario assuming all assets are equal in price of 100 dollars; if someone has 10,000 1st and 2nd level contacts on Linkedin, the value of their implied call option is about 34,700 dollars. If Linkedin were a stock market, the value of the social contracts that people have with each other is 34K x 40M = 1.3 Trillion Dollars market value for the contracts that people hold and trade.
This is not even the value of the transaction – only the right to have a transaction. The value of the social contract is in the conversations that they hold. Contracts are a financial instrument that can be traded, combined, diversified, and aggregated for real money. It’s only a matter of time.
The Ingenesist Project specifies the structure of an innovation economy where a knowledge inventory, a percentile search engine, and an innovation bank will facilitate and aggregate the 5 components of Option Valuation. Social media applications form the operating system for the market in options.
Mentors provide expertise to less experienced individuals to help them advance their careers, enhance their education, and build their networks. In many different arenas people have benefited from being part of a mentoring relationship: Freddie Laker mentored Richard Branson, Bach mentored Mozart, Dr. Dre mentored Eminem, Aristotle mentored Alexander the Great, and Obi-wan Kenobi mentored Anakin Skywalker.
Mentorship: a Valuable 2-way Conversation
Suppose that mentorship could be monetized like financial instruments. Within the structure of an innovation economy specified by The Ingenesist Project; a knowledge inventory, a percentile search engine, and an innovation bank will match the most worthy student to the most worthy mentor in the respective market structure. The mentor would take an equity position in the protégé, not unlike taking a stock in a corporation.
For example: A single mid-career mentor could take on 10 protégés with an option to exercise, say, 1% of the students future salary for every year mentoring upon predetermined retirement date. Say that the average mentorship lasts 10 years. Likewise, each of the protégés also becomes a mentor taking on 10 protégés of their own. The Master mentor will collect 1% of the revenue that each of the 100 sub-protégés provide to their middle mentors per year.
The Educational Pyramid Scheme
If each protégé becomes at least as successful on average as the mentor, the master mentor can collect the equivalent of their average salary for the duration of their retirement. If each of the protégés become equally effective mentors, then the master mentor can double their average salary for the duration of their retirement. A third tier adds another salary to the master mentor.
This is what actually happens in an informal way within companies, government, and Jedi Knighthood; the exception is that social media will enable this to occur outside the construct of a corporation – and such.
Game Theory for the Rest of Us
An interesting social game emerges: It becomes the best interest of the mentor that each of their protégés is successful in their field and practice high integrity. It is in the best interest of the mentee to learn as much as they can and become as proficient as they can. It is the best interest for mentees to pick appropriate mentors and it is in the best interest for mentors to take on appropriate mentees. It is efficient for mentees to form a social network among themselves and for Master Mentors to form a network among themselves. A multiplier effect surges with cross-mentoring.
In aggregate, it is in the best interest for the membership in the social network to cooperate rather than compete because their income would ultimately benefit less from competition than from cooperation.
2.3 Trillion Dollars Market
The American Public education system is in disarray. Standardized education defies the diversity of the country. Teacher’s pay has been stagnant. Curriculum takes years to respond to new knowledge. Recent McKinsey research finds that a persistent gap in academic achievement between children in the United States and their counterparts in other countries deprived the US economy of as much as $2.3 trillion in economic output in 2008
None of this has anything to do with the dreams of our children. None of this has anything to do with the intellect, motivation, and perseverance of our kids. It has everything to do with Political stalemate and failure of the economic system. All children can achieve their dreams, and ours, if there were a market for mentors.
The objective of this series is to contain what we know about social networks within the construct of the financial system. The intention is for knowledge to behave, and thereby trade like a financial instrument. In prior articles, we discovered the currency, the inventory, the institutions, and the entrepreneurs of the next economic paradigm. This module will construct the business plan:
A business plan is the blue print for the construction of enterprise.
Like the construction of any tangible asset, an inventory of parts is assembled in strategic proportions. The ability to accomplish this gives the enterprise a strategic and competitive advantage in a market.
Business failures are knowledge failures
Most enterprises will emphasize design, or service, or performance or price in their proprietary secret sauce of market success. The question becomes, what quantities and qualities of strategic components allow the new enterprise to create a positive economic outcome.
Most business failure are due to knowledge deficits such as the inexperienced management team, a poor assessment of market conditions, under estimating the amount of money needed, under estimating a competitor, loss of a key employee, or the poor understanding of the technology, etc. These are knowledge problems not financial problems.
Prediction is the quality of knowledge:
To solve the knowledge problems is to decrease the risk of innovating and increase the predictability of innovations. To decrease the risk will decrease the cost, and increase the availability, of venture capital. To increase the predictability would increase entrepreneurial activity.
The Unit Business Plan:
The business plan of the innovation economy is very simple; it starts with the single transaction between two people. The lender provides information and the borrower combines the information with their existing knowledge to create more knowledge. This single transaction has a value of 1 unit of currency and we call it a unit business transaction:
The Parallel Circuit:
Now we will assemble these single transactions in many combinations. When we combine two unit transactions in a parallel circuit. This represents a brain storming session between two people.
The Percentile Search Engine matches the person with the most worthy knowledge supply to a person with the most worthy knowledge demand. The transaction is a simple conversation and the outcome is a prototype process, system, method, or iteration.
The Series Circuit:
The next transaction type is modeled as two unit business transactions occurring in a series circuit. This represents a product development cycle.
Each cycle of these transactions is an improvement to the business objective. Each time the transaction occurs there is a net increase of new knowledge and therefore an increase in value. New options are created. The conversation stops when the product is ready for the market, cancellation, or next physical iteration.
The transaction is recorded as an event between two known persons of known knowledge inventories. The transaction is stored in the intellect of the participants and becomes their property in the form of a knowledge asset represented by the things they create with their knowledge.
The Social Network:
Now if we combine the parallel transaction with the series transaction we have what now looks like a network. In practice, we know that strong networks of people freely exchanging ideas make organizations better, smarter, and more efficient. Networks are where knowledge and community wisdom is stored. A network is fault tolerant, if one person leaves, the network survives. For a relatively small input into a network, we can produce a large output of new knowledge – we have a learning organization.
However, in society, these interactions are largely accidental; people meet at Church, Starbucks, and Social Events or by word of mouth. Other times, these interactions are concentrated inside a single community of very similar people such as a technical conference, group meeting, or lunch buddies and are often not well diversified. More recently, interaction is self selecting through social media devices such as Twitter, Linkedin, Craigslist, Biznik, and Meetup, etc.
What if the social interactions could be made less random and more intentional?
Suppose interactions be designed with a specific purpose by the entrepreneur as a means toward producing a unique outcome. The Innovation Bank will combine people of complementary knowledge assets in a calculated manner in order to arrive at specific business approaches and applications.
What if Innovation could be made less random and more intentional?
The Multiplier Effect:
A special case business plan is called the Multiplier Effect. In effect, building a network of applications from a network of knowledge assets.
Suppose that a company owns composite material technology for use on aircraft. Since the company specializes in airplanes, they have no intention of pursuing other applications such as recreational equipment, energy production, or health care products.
The Innovation Bank:
Suppose that the company could deposit this asset in a bank and collect interest. The Search Engine can scan the business landscape to find persons or organizations with a worthy knowledge deficit in the area of your technology. The originator holds the option to see what those other companies invent and hold the right to use their new ideas in an aircraft application.
Contracts manage those options. Those contracts are social contracts and they can be traded. They are a form of currency – or stored value.
In the event of a cyclic downturn, instead of “laying off” knowledge assets, people can work in tangential industries where they will continue developing – literally putting “Knowledge in the Bank” – to be called back to their original company when market conditions improve. A mobile knowledge asset increases in value and continually becomes smarter and more productive over time. This is not socialism, this is not capitalism, this is Ingenesism – from the root word: Ingenuity.
Market Efficiencies:
With an innovation Bank, a company can reduce their Research and Development costs and create additional revenue in a tangential innovation market. Millions of people are being layed off work from corporations – billions upon billions of dollars of innovation potential is being squandered. With reduced cost and risk of innovation, The new American corporations will specialize in inventing, networking, and applying new ideas as their primary revenue source.
The Internet is a lot like a commercial airplane – it is very useful in transporting us to distant lands but the real work must happen on the ground. The organization of society at both ends of an Internet destination must be developed if real wealth is to be created. Social Media needs to develop this component at this critical juncture of human history when vast amounts of social capital, creative capital, and intellectual capital are being sent to the shores of despair upon Unemployment Air Line.
Computer enabled society:
The great opportunity of our generation in the fair, sustainable, and equitable creation of wealth through innovation in a computer-enabled, open-sourced, and democratic society that can organize its own knowledge in the form of a financial instrument. The great danger, of course, is if we miss our flight and engender a computer simulated society where it is easier to interact with online community than our own neighbors. It’s like getting on an airplane for the fine view, good food, and interesting conversation. Social capital is by far the most powerful force of change and social media must now touch the ground in a meaningful, systemic, repeatable, and scalable manner.
The analogy continues:
The earliest days of aviation were a novelty at best. Some commercial enterprise emerged in the form of barnstorming, carrying the mail, light cargo, aerial photography, and warfare. Likewise, the evolution of the internet brought us on-line gaming, e-mail, e-commerce, assorted photography, and hacking, etc. It was not until the invention of municipal airports that the airplane became a true time machine by increasing human productivity and allowing us to see history that would otherwise be unavailable traveling by sea. The true value of both commercial aviation and social media over “sail mail” is precisely through the increase in human productivity to transfer information to the ground.
Three Web Applications:
First, social media needs to develop a knowledge inventory system by geographic areas. Second, Social Media needs a search engine at a local level that combines knowledge assets to form “strategic” social networks that can execute a specific business plan at reduced risk; cooking the “secret sauce”. Third; an Innovation Bank must “pull” knowledge surplus and “pull” knowledge deficits together from diverse communities. These three applications will provide everyone with the tools needed to create wealth in their communities.
Social Media has the potential to become the airport of the Internet Transportation System. Nothing meaningful can happen until the rubber meets the tarmac. So, let’s start building runways.
So now, what are the entrepreneurs going to do with this percentile search engine?
Entrepreneurs wander the earth looking for valuable things that are being used at a low level of productivity and they move those assets to a higher level of productivity and then pocket the difference, called profit.
Think pet rock, condo conversions, sand, corn, etc.,…it goes on forever.
The entrepreneur needs to have a clear view of what the asset is, the lower level of productivity, and the higher level of productivity of the asset. These three elements are the focus of all business plans. Then they set things in motion and give life to the market system.
When we look at financial banks we see the classic entrepreneurial activity. In the simplest form, banks do little more than find people who have a surplus of money and they match them with people who have a deficit of money. Bankers have a clear view of the asset, the lower level of productivity and the higher level of productivity for the asset.
They pay a lower interest to the depositor than they do to the borrower and pocket the difference. In addition, they enjoy a multiplier effect that allows them to lend the same money many times effectively creating money from a promise to pay, or debt.
It is in the best interest of the bank to find rich people who will not need their money for a while, and poor people that have the best likelihood of paying the money back in time. This is to minimize the risk that the depositor will pull out their deposits and the risk that the borrower will not pay back the loan. The problem is that some assumptions need to be made, some of which may no longer be valid:
The bank assumes that the borrower has the knowledge required to execute the business plan that they are financing. Unfortunately, the credit score does not predict knowledge on future ventures. For this reason, new ventures are not easy to finance.
The financial bank makes the assumption that the entrepreneur has the knowledge to execute a business plan that they seek money to fund.
On the other hand, the Innovation Bank makes the assumption that the entrepreneur has the money available to execute the business and is searching for the knowledge to do so. This service will be required in the innovation economy since no single person can live long enough to possess as much knowledge as is required to manage the complexity of problems that face the World. We will need to mind meld.
The Innovation Bank simply matches most worthy knowledge surplus with most worthy knowledge deficit and a market is born.
The challenge for the innovation Bank is to match the most correct knowledge surplus to the most correct knowledge deficit. This is accomplished with the computer enabled knowledge inventory. A search can be conducted of the supply and demand for knowledge assets. The Percentile Search Engine will calculate the probability that the specific business objective will be successful.
The business plan for the entrepreneur is very simple but the implications are vast.
The Percentile Search Engine is a way of using a computer to make predictions about all types of combinations of knowledge Assets.
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 Percentile Search Engine returns probabilities – that is, what’s the probability of success for any number of scenarios.
For example; an entrepreneur may want to know if her team has enough knowledge to execute a business plan. Maybe the team has too much knowledge and they should try something more valuable. Maybe the team does not have enough knowledge and they should find someone else, take training, or try something simpler. The Percentile Search Engine can look into the community and identify the supply and demand of a knowledge asset. If it is unavailable or too expensive, the Percentile Search Engine will even tell them what training they need to increase their probability of success.
The entrepreneur may also want to determine what competitors have a dangerously high probability of competing with her new business. The Search Engine will allow competitors to scan each other’s knowledge inventory to determine how long it would take for their secret sauce copied. They can take then choose to take evasive action, compete, or cooperate. 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.
While companies such as Disney and Boeing both use Engineers, each would have proprietary combinations of knowledge that represents their “secret sauce” of success. These recipes can be adjusted and improved to reflect the wisdom of an organization.
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.
Literally thousands of new business plans will emerge from this important new paradigm. Knowledge will become tangible outside of the organizational construct of the corporation. Knowledge combinations will become the new corporate structure. The rate of change of knowledge with respect to time is the key metric and fundamental building block of the innovation economy.
