Nobel Laureate Dr. Robert Solow calculated that 80% of economic growth can be attributed to technological change. This is the domain of engineers, scientists, and technologists. Accordingly, knowledge assets and their derivatives are not actually “intangible” but rather, they are simply invisible and unable to be measured directly. Like the proverbial “tip of the iceberg” the visible part of the economy is supported by the invisible assets below the surface.
True to form, emerging technology now offers us the ability to quantify this vast reservoir of value. We now have the opportunity to unlock an economy many times larger than the one we currently grapple with – the one in which there is “never enough money” to care for our planet and meet the needs of our civilization.
The Innovation Bank:
The Innovation Bank utilizes game mechanics, blockchain technology, and Artificial Intelligence to measure the natural interactions of engineers, scientists, and technologists within a simulation representing this hidden economy. Novel Financial Instruments may then represent this new value.
What is an Ingenesist?
A “Capitalist” is a person who uses money to invest in trade and industry for profit. An “Ingenesist” is a person who uses ingenuity to invest in trade and industry for profit. Both operate in tandem to arrive at optimal solutions to market requirements.
Join Us:
The Ingenesist Project comprises the collective vision, intellect, and creativity of more than 250 engineers, scientists, and technologists who have collaborated across various industries over the past 30 years as a non-profit research and governance organization.
Classical economics is built upon a scarcity model of supply and demand of physical assets. In the trade of knowledge assets, the transfer of knowledge to one party does not require the cessation of knowledge by the other. As a result, it is estimated that 80% of a modern economy is intangible simply because it is not measured in accordance with generally accepted accounting practices. New methods in Blockchain and AI allow us to measure new value assets into tangible existence. This article proposes an accounting system for the next economic paradigm.
When Bears and Bulls Collide
In conventional accounting practices, a positive entry in the asset column of a balance sheet must correspond to a negative entry in the debit column. However, Knowledge Assets (K-Assets), function differently. The transfer of K-Assets does not require deducting the asset from the previous owner. Consequently, K-Assets are abundant and necessitate a different form of accounting to correctly attribute the contributions of STEM practitioners on a balance sheet.
A Brave New GAAP:
The Innovation Bank by The Ingenesist Project, provides the substrate for the production of K-Assets. This process is similar to how financial institutions facilitate the production of Capital Assets (C-Assets), but with distinct differences. Furthermore, the successful accounting system would facilitates the equitable exchange between of K-Assets and C Assets. The goal is to establish parity between these previously separate asset classes based on an universal risk-adjusted basis, rather than a scarce profit-adjusted basis.
Revolutionizing Technology Transfer
The Innovation Bank revolutionizes technology transfer by focusing on knowledge assets in their natural state – the mind of the practitioners – rather than a physical objects like machines, buildings, or processes that they may create. Although the end result is identical, this approach proves far more efficient.
In the Innovation Bank, the K-Asset, is created when one practitioner makes a claim and another practitioner validates it on a decentralized database. As a reward, they each receive cryptographic tokens that can later be used to access system metadata or traded on an open exchange for business intelligence. This dynamic “nano-credentialization” in aggregate, forms a means to measure economic potential.
A simple game with extraordinary implications.
The system operates autonomously, providing practitioners with incentives to generate new K-Assets. The rate at which they gain access to other practitioners depends on the quality and quantity of their own K-Asset production. Practitioners are driven to maximize token rewards and accumulate a personal transaction record consisting of successful claims and validations. Access to the database opens up more opportunities for them to generate further claims and validations, creating a positive cycle of growth.
Digital Career Path
Individual transaction records essentially serve as a digital public key, representing a practitioner’s résumé, CV, or portfolio. The owner maintains full control over this record. To ensure integrity, the same game mechanics that populate the Innovation Bank discourage trivial, false, inaccurate, and malicious transactions. The ledger is immutable, auditable, and incorruptible, providing a robust system that prevents such fraudulent or malicious behavior.
The Economy of the Future
In this brave new world of accounting, where knowledge assets are valued on their intrinsic merit rather than their scarcity, the Innovation Bank represents a significant step forward. By embracing this new accounting paradigm, we can unlock the full potential of human knowledge, foster innovation, and create a more inclusive and sustainable economy for the future. Imagine the world that humanity can build for itself if the other 80% of economic growth could be measured into tangible existence.
The world is facing increasingly systemic challenges that pose significant threats to the global economy. The risk of a catastrophic event in one part of the world triggering widespread instability or collapse is now more imminent than ever. This isn’t merely a political issue; it’s an engineering challenge with the potential for a straightforward solution.
Insurance plays a vital role in ensuring the smooth operation of the global economy by providing a steady financial backbone for its builders, innovators, and participants. However, insurance can only function effectively when we have a clear understanding of known risks, their probabilities, and the consequences of potential losses. This underscores the critical importance of curating accurate and validated information about the physical state of the world.
The Domain of Engineering
Engineers, fundamentally, are professionals dedicated to reducing risk in complex systems. Interestingly, their analytical methods bear a striking resemblance to those employed by actuaries in the insurance industry. This highlights that the task of mitigating global systemic risk hinges on harnessing the expertise and observations of global engineers, scientists, and technologists.
The Age of Disinformation
In the information age, the business model predominantly revolves around collecting, manipulating, and leveraging information. Sadly, there are limited incentives to curate and verify accurate information. It’s worth noting that the absence of information can be as detrimental as false information, and both are considerably cheaper than producing and validating factual information. This is where the financial system faces significant challenges.
Converting Intangible Assets into Tangible Assets
One of the most pressing issues facing society today is the misallocation and confinement of engineers and scientists within various silos, such as academic institutions, political boundaries, corporate structures, arcane ontologies, and other factors unrelated to the natural laws equally affecting us all. Their knowledge is often categorized as “intangible assets,” not because it lacks substance, but because it’s challenging to quantify. Imagine if there were a quick and straightforward method to measure these intangible assets, transforming them into “tangible” assets, thereby creating a new asset class significantly more valuable than traditional assets.
A Straightforward Solution
The Ingenesist Project, a nonprofit professional network, is developing a platform designed to measure intangible assets and render them more tangible. Through the utilization of game theory, blockchain technology, and artificial intelligence, credible individuals make claims about the physical state of the world, which are then validated by other participants on the professional network. This dynamic process creates a validated and easily measurable large language graph, from which valuable AI business intelligence can be derived. Participants receive electronic tokens for contributing to this immutable native blockchain. The global insurance and finance industry can access this powerful network graph by purchasing tokens on a third-party clearinghouse from those seeking to sell them, with token value determined by market supply and demand.
Vast Consequences
By introducing this innovative framework, a new set of incentives can be established, making truth more profitable than fiction, at scale. The barriers that have traditionally separated engineers and scientists will no longer obstruct the curation of information essential to the insurance industry for crafting effective and socially impactful insurance products. This platform operates under a set of rules that apply equitably to all participants, eradicating corruption and unnecessary friction. Crucially, it provides the insurance industry with a reliable baseline of data to train AI models accurately, ensuring they operate in the right place, at the right time, and at the right price.
Visionary Leaders
The Ingenesist Project seeks sponsors to expedite the development of the “Innovation Bank.” Additionally, directorships and governance positions are available for visionary leaders in the insurance and engineering fields who recognize the potential of this groundbreaking initiative.
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.
In the ever-evolving landscape of technology, artificial intelligence (AI) plays a crucial role in enhancing the effectiveness and efficiency of various systems. The Value GameTM, powered by The Innovation Bank™, is no exception. By incorporating AI algorithms and machine learning capabilities, these groundbreaking platforms from The Ingenesist Project can further revolutionize the way we establish trust, verify claims, and combat fraud in real life systems that sustain civilization.
Patterns of Fact
AI can be employed in multiple stages of The Value Game to strengthen its integrity. Firstly, AI algorithms can assist in the initial claim recording process by automatically cross-referencing the information provided with existing databases, verifying its accuracy and authenticity. This reduces the burden on human validators and enhances the speed and accuracy of claim validation. Furthermore, AI can analyze patterns and detect any inconsistencies or red flags in claims, providing an additional layer of security and fraud detection.
Patterns of Fraud
As The Value Game accumulates a vast amount of data on claims and validations, AI algorithms can continuously analyze this information to identify trends and anomalies. By learning from past instances, AI can identify potential fraudulent behavior, detect patterns of collusion, and even predict future attempts at deceit. This proactive approach allows the system to stay one step ahead of attackers, making it increasingly challenging for them to exploit the platform.
Network of Trust
Moreover, AI can contribute to the ongoing curation of claims and validations. By analyzing the data collected, AI algorithms can identify correlations between different claims, validators, and professions. This analysis helps build a comprehensive network of trust, providing participants with a broader context and enabling them to make more informed decisions when validating claims. AI-powered insights can guide participants in identifying outliers and potential risks, fostering a more secure and reliable environment.
Transaction of Records
Additionally, AI algorithms can assist in assessing the reputation and credibility of participants within The Value Game. By analyzing historical data and interactions, AI can assign reputation scores to individuals based on their track record of accurate validations or fraudulent claims. These reputation scores can serve as an additional factor in evaluating the credibility of a claim or a validator, further strengthening the overall trustworthiness of the system.
Things that get better with age
With the integration of AI, The Value Game becomes a dynamic and self-improving ecosystem. As more data is collected and analyzed, AI algorithms continuously refine their models, improving the accuracy of fraud detection and claim validation. This iterative process enhances the system’s resilience and adaptability, enabling it to keep up with emerging tactics employed by attackers.
Adapting diverse datasets
The incorporation of AI into The Value Game also extends its applicability beyond traditional fields and professions. While initially focused on STEM professionals, the AI-powered platform can expand to cover a broader range of domains. By training the AI models on diverse datasets from various fields, the system can adapt to accommodate claims and validations across different industries, thus maximizing its impact and relevance.
A sophisticated and resilient platform
In conclusion, by harnessing the power of AI, The Value Game evolves into a sophisticated and resilient platform that effectively combats fraud and deception in real life systems. AI algorithms contribute to the initial claim validation, continuous curation, fraud detection, and reputation assessment, enhancing the overall trustworthiness and reliability of the system. With AI as its ally, The Value Game becomes a powerful tool that empowers individuals, safeguards authenticity, and enables trust to flourish in an increasingly interconnected world.
An engineer’s role is to mitigate risks in complex systems. Activities like flying through the sky, transplanting organs, and fiddling with energy are very risky indeed. The primary output of an engineer is the removal of these risks. It’s a straightforward concept: Engineers remove risk from complex systems.
A firefighter is worth a million dollars per hour safeguarding life and property – when there is a fire. The value of the firefighter is easily measured by severity of the fire. A fire protection engineer can design thousands of buildings that will never burn. Unfortunately, in the absence of a fire, there is no way to measure the true economic value of the engineer?
Reflecting on the complex global challenges that civilization faces: Are we fighting fires or solving fires?
Unless we accurately assess the economic value of engineers and incorporate it into our monetary system, it will always be more profitable to allow the world to burn.
Engineers remove risk from complex systems – this idea is easy to understand and the solution is actually quite simple – we have the technology and analysis tools to accomplish this with relative ease.
Please lend your support to The Ingenesist Project by contacting us directly for full specifications of this project, or by pitching in with the PayPal link above. If we don’t fix it, who will?
The process is so simple, it defies the imagination.
Countless words have been written about the nature of money and its role in society. Ultimately, money serves as a representation of human productivity, as people work and produce goods and services in exchange for it. The creation of money is based on the things we produce, allowing us to measure its value.
Banks address the time gap between production and payment by creating an asset called “future productivity.” This asset enables them to generate money before the actual goods or services are produced. It takes the form of debt.
However, innovation also represents future productivity, as it brings forth useful things that have not yet been created. In fact, approximately 80% of economic growth can be attributed to technological advancements. So, why can’t engineers adopt a similar approach to banks and measure money into existence? This would serve as a means of bridging the time gap and funding the substantial amount of innovation necessary to sustain our world.
Although it may seem like a straightforward idea, it is challenging to comprehend. The issue lies not in a broken world but in a broken monetary system. The solution lies in fixing this system.
To address these challenges and promote innovative solutions, please lend your support to The Ingenesist Project. We literally make money.
A bank will not lend money to a project unless it is insured. An insurance company will not insure a project unless it is well engineered. Engineering cannot be well done without a bank to cover soft costs. Together, this forms the virtuous circle of modern civilization.
While the banking and insurance piece seems straight forward, very few economic journals discuss the role of engineers, scientists, and technicians in this manner. Their role is to produce material fact:
1. Identify the risk exposure,
2. calculate the probability that risk will manifest,
3. review and assess consequences in the event that the peril does manifest.
Done correctly, finance, insurance, and engineering can sustain the indefinite peaceful habitation of the world.
The War on Facts:
If any of these three pieces are missing, distorted, or corrupted, the economics collapses, projects fails, and things blow up.
A material fact is a fact, the suppression of which would reasonably result in a different decision.
Wikipedia
As we increasingly endure a polarized society where disinformation is spread with precisely the intention of distorting material facts, nothing could be more important than a means for securing material facts. This is a simple idea.
There is the further disadvantage that technology itself vastly favors the cheap creation and distribution of misinformation – at scale – while securing material facts must be committed in a certain sequence, standard of proof, and immutable record. This is a simple problem to solve.
The Innovation Bank curates and integrates validated material fact across a range of physical conditions prior to the peril of disinformation occurring. Such a powerful gauntlet may provide a sieve through which disinformation must survive in order to establish credibility. The value of such a “disinformation filter” amounts to the value of our economy at large. This is simple. This is serious. This is something that we can build today.
Please contact and contribute to The Ingenesist Project for more information about The Innovation Bank projects.
The Innovation Bank is a novel method of business related to the integration and capitalization of knowledge assets. The Innovation Bank is an application of game theory, actuarial math and a simple native “proof-of-stake” blockchain. The system aims to unify the global engineering and scientific disciplines by incentivizing individual practitioners to form knowledge asset networks among each other by producing claims and validations related to physical, measurable, and observable facts. Each claim and associated validation forms a node in a network for which each participant is awarded a cryptographic token memorializing earned stake (equity) in the system. A secure, validated, and decentralized knowledge repository and access management system is secured by a simple native blockchain. Revenue is generated through the liquidation of earned tokens on an external market to third parties seeking access to network metadata for business intelligence. The intrinsic value of the network grows as the number of participants increases. As participation increases, the quantity and quality of the transaction records also increases. Third-party buyers may include banks, insurance companies, and private enterprise.
In the United States, the term “Engineer” is regulated by licensure boards, which means it refers to a person who is registered and licensed to practice engineering in the country. However, for everyone else, there is no clear definition.
The elusive nature of the term “Engineer” raises questions. Does it refer to someone licensed to practice in a specific jurisdiction? Or is it someone who has completed four or five years of university education? Does it encompass those who operate complex machinery like locomotives, sound boards, or building systems?
Considering that the engineering profession is responsible for nearly 80% of economic growth, it becomes crucial to establish a precise, measurable, and actionable definition. Without a rigorous definition, it is difficult to effectively manage the profession. These gaps in definition are significant oversights.
Given the lack of a suitable synonym for “Engineer,” we introduced the term “Ingenesist” with the following explanation:
The Latin word for engineer is “Ingeniator,” which is derived from two other Latin words: “ingenaire” (to conceive or derive) and “ingenium” (cleverness). The suffix “-ist” implies someone or something characterized by a specified quality. Combining these elements, an Ingenesist can simply be defined as a “creator of useful things.”
This straightforward definition is superior in describing the essence of engineering and its problem-solving nature. It can be put into action from an economic, political, or legal perspective, as there are rigorous definitions for what is considered useful and what is not. Importantly, this definition does not contradict existing conventions or institutions. It includes licensed and unlicensed professionals, as well as those from international backgrounds or those who rely on intuition rather than formal education in understanding the laws of nature. The term “Ingenesist” encompasses artists, craftsmen, technologists, and more.
Most importantly, the concept of an Ingenesist is inclusive rather than exclusive. It is accessible to anyone who chooses to be productive in a useful manner. Differentiating between what is useful and what is not comes naturally when using the term Ingenesist. It acknowledges the innate creative nature of our species.
The World is grasping for an “Easy Pill” to combat global systemic risk. What if such a thing actually existed, would we embrace it?
Image by PIRO4D from Pixabay
Imagine if there was a small and almost imperceptible flaw in modern capitalism that could be easily rectified. This single flaw might be the root cause of all the other problems we struggle to solve individually. The remarkable thing is that this flaw could be corrected without dismantling the entrepreneurial spirit, technological advancements, or the functioning institutions that already exist. Moreover, this correction wouldn’t require policy makers and business leaders to fundamentally change their ways.
Would you invest in a team that could address this flaw?
Let’s explore the flaw:
In order for economic growth to occur, technological change must always precede it. However, we currently approach the business of civilization as if economic growth can come before technological change. We have it backwards.
Consider this: the wheel, the wedge, and the lever were invented long before the establishment of international trade agreements. Somewhere along the line, we lost our way. Innovation is not derived from money; instead, money arises from innovation. Although it may seem trivial, this tiny flaw exerts control over almost every aspect of our lives.
Economics did not start with someone discovering $300 trillion in box somewhere. All money came into existence as a measurement of useful things that people have created since the beginning of time. By simply altering how we measure things, we can effect the value and distribution of money. Nowadays, when you ask a venture capitalist to define “innovation,” they might respond with something like, “I know it when I see it.” While this might be a valid measure for them, it holds little value for anyone else. What we truly need is a way to identify and measure innovation before it even happens. Surprisingly, this is a problem that can be easily solved.
Risk is the common thread that binds us all.
Risk is an inherent part of every decision we make, whether we’re venture capitalists, corporate executives, government policymakers, or members of the general public. In fact, risk heavily influences the premier corporate valuation tool, CAPM (Capital Asset Pricing Model). Risk is the true currency of our lives. For example, the value of a firefighter is determined by the severity of the fires they combat, yet a fire protection engineer can design 1000 buildings that will never burn. Our economy measures the fire itself, rather than the absence of fire.
Engineers exist to mitigate risk in complex systems such as airplanes, wastewater management, and medical procedures. Measuring risk is a relatively straightforward task. The insurance industry, for instance, consolidates various risks into sharing networks and assigns a “value/premium” to expected losses.
In contrast, engineers are currently organized in disconnected silos, subject to arcane jurisdictions and academic jargon. However, if engineers were organized in networks using a common ontology, similar to how systemic risk itself is structured, an immense amount of value could be measured into existence. This value can then be monetized equitably and on a large scale.
Introducing the Innovation Bank:
The Innovation Bank serves as the mirror image of a traditional bank. Its goal is to organize the engineering, scientific, and technology professions in a slightly different manner. By employing a combination of Game Theory, Blockchain Technology, actuarial math and Artificial Intelligence, the Innovation Bank facilitates the curation of innovation using a common ontology. Nothing else changes. Everything we currently know remains intact. The outcome is the ability to finance the removal of the risks that control us.
This solution is astonishingly simple, defying our imagination. Will we have the courage to embrace it?
The essence of a network lies in connecting people.
We invite you to join The Ingenesist Project. Your knowledge, experience, and creativity are invaluable in building this platform correctly. If you’re pressed for time, you can participate by making a donation of any size.
Please review our partial publication record listed below. We have published at the forefront of our industry, founded numerous start-ups, and our past participants have emerged as prominent voices in the new value movement. The Ingenesist Project has spent two decades maintaining an online presence, representing extensive research and collaboration involving over 120 researchers, engineers, and scientists from some of the most influential corporations and institutions worldwide. Help us unify the global engineering and scientific communities. Help us unite the world.
“A lie can spread halfway around the world before the truth even has a chance to put its pants on,” as the saying goes. This kind of leverage is not limited to lies alone. Take, for instance, the case of the shoe bomber, whose actions led to millions of people having to remove their shoes at airports for the past 20 years. Law enforcement faces the burden of being right countless times, while an attacker only needs to be right once. Despite the immense cost and loss of civil liberties, we still struggle to distinguish between fraud and fiction. It is imperative that we solve this problem as if our lives depend on it. Behind every instance of fraud lies a mountain of truth waiting to be curated.
But what if we could reverse this leverage? What if the attacker had to be right a thousand times while the target only needed to be right once?
Introducing the Value Game, a feature of The Innovation Bank™. This game applies game mechanics to address this challenge. Here’s how it works: When a person makes a claim about something in the physical world, such as their education or a toxic spill, that claim is recorded on a blockchain, timestamped, and made immutable. The player then seeks another player to validate their claim by stating, “I validate that this claim is true.” The claimant and validator are permanently linked on the blockchain. All these claims and validations are combined in the community. Participants are rewarded with digital tokens that can be converted to cash. Problem solved!
Let’s see how this game plays out in a scenario. Imagine a super villain named Max Mallory who wants access to a nuclear reactor for his nefarious plans. However, he lacks the necessary education and experience as a nuclear engineer. Using The Innovation Bank, Mallory makes a claim that he is a nuclear engineer. But he struggles to find another engineer to validate his claim. So he pays his sidekick Carl to validate it instead. Both receive tokens as a reward. So far, so good!
Max Mallory’s Sidekick, Carl
Mallory then attempts to enter the reactor gate but is denied. His transaction record doesn’t match that of a typical nuclear engineer. Mallory tries to fill in the gaps by consulting Wikipedia, but the blockchain doesn’t allow for going back in time. Mallory would need to complete high school before going to college. The Innovation Bank registers Mallory’s unvalidated claim (a fancy term for a lie) and Carl’s validation as a “dead head claim” (a fancy term for incompetence).
If Mallory or Carl ever want to engage with the Innovation Bank in the future, such as for job applications, loans, or social media comments, they will face increasing difficulty in finding validators. Their only option would be to start over with a new profile from t=0.
In the long run, a successful attacker would need to be an accomplished professional nuclear engineer with a long record validated by many colleagues, mentors, publications, and institutions, all in a specific sequence and over a significant period of time. The reward from the attack would have to outweigh the attacker’s potential losses, as they would likely be identified, caught, and prosecuted. However, it’s more likely that they would be thwarted at an earlier stage with an unvalidated claim for a less critical offense.
In general, there is no incentive to cheat in this system. Aiding and abetting cheaters is also discouraged. Both claimants and validators face future consequences if they are careless with facts and associations. The costs of cheating far outweigh the benefits of engaging in illicit activities. As a result, routine operations of power plants do not incur punitive costs.
As the Value Game unfolds, with millions of claims and validations across various professions and fields, the likelihood of encountering fraud or incompetence becomes exceedingly small, approaching zero, particularly for higher order claims. The aggregate database of truthfully interacting STEM professionals and beyond trains the algorithm to identify outlier behaviors. The more truth stored in this database, the more valuable it becomes in separating fact from fiction and increasing the value of digital tokens. As the tokens gain value, the network’s security improves.
Now, the truth can travel halfway around the world before the lie even has a chance to put its pants on.
The Innovation Bank is much more efficient than attempting to unravel anonymous rumors spread on the internet. It is also more efficient than having to validate each claim individually. Everything is pre-validated, minimizing prohibitive punitive costs and controls. This “judicial system” is self-funding and self-correcting. The process of curating claims and validations forms the social fabric upon which we all rely. Every participant is incentivized to collaborate and gain stake in the system. Meanwhile, there is no incentive to exploit or corrupt the system. Forensics are performed before failures occur, ensuring a reliable and trustworthy environment.
