Category: Ingenesist

While engineers, scientists, and technologists are critical in mitigating risks, they are still categorized as liabilities rather than assets on global balance sheets. This misclassification is a fundamental flaw in how markets operate today.

It is essential to recognize that risk management is at the core of economic decision-making. Financial markets thrive on balancing risk and return, but there is an inherent contradiction when those who actively reduce risks—by innovating and solving complex problems—are undervalued.

By classifying these professionals as expenses, we fail to acknowledge their role in creating long-term value. This misalignment discourages investment in critical areas like climate change mitigation, public health, and infrastructure resilience.

The Boomspace approach to reorganizing these professions using game theory, blockchain, and artificial intelligence offers a promising solution. By leveraging these technologies, we can reframe how engineers, scientists, and technologists are valued—shifting them from liabilities to assets.

This shift would not only incentivize innovation but also unlock new financial resources for addressing global challenges.

The video concludes with the claim that if engineers, scientists, and technologists reorganize themselves, then the financial system will likewise reorganize itself seeking risk mitigation. This is a very powerful position for the professions if they should take it.

Risk and Return

As the saying goes, money makes the World go around. This may not be entirely true.

Where risk is high, the cost of money is high. Where risk is low, the cost of money is low.

Engineers, scientists, and technologists specialize in removing risk from complex systems.  So, why is there never enough money to mitigate the world’s most pressing risks?

Fortunately, all we need to do is reorganize engineers, scientists, and technologists and the money will surely follow

The Ingenesist Project uses game theory, blockchain technology, and Artificial Intelligence to reorganize the engineering and scientific professions. 

Join The Ingenesist Project

Analysis

This video poses a legitimate question. If there is money to be made by mitigating risk, why are Engineers, Scientists, and technologists classified as expenses (liabilities), and not assets on global balance sheets?

It’s amazing how vested we are in this staggering little flaw in market Capitalism.

Key Phrase: Risk and Return

From Money-Backed Innovation to Innovation-Backed Money

The traditional debt-based economic model where money is backed by future productivity presents significant limitations in our rapidly evolving world. This system constrains innovation by tethering it to conventional financial metrics that fail to capture the true value of human potential and creativity.

Current Limitations

The existing financial framework moves too slowly and inadequately represents the actual productivity of society’s diverse contributors – from parents and educators to engineers and scientists. This disconnect creates a fundamental gap between innovation potential and available capital, limiting our ability to solve future challenges at the required pace.

The Innovation Standard

A revolutionary approach emerges when we inverse the relationship between money and innovation. Instead of innovation being backed by money, currency could be directly backed by the true value of innovation itself[1]. This transformation would create a more dynamic and responsive economic system.

Mechanics of Innovation-Based Currency

The implementation of this new economic model relies on three key technological pillars:

• Game theory to establish value metrics
• Blockchain for transparent tracking
• Artificial Intelligence for asset conversion

These technologies work in concert to transform intangible innovative potential into tangible economic value.

Future Economic Implications

An Innovation Bank would fundamentally differ from traditional banks by issuing currency directly backed by innovation value rather than future productivity promises. This system would:

• Accelerate problem-solving capabilities
• Better represent true human productivity
• Create more immediate connections between innovative solutions and resource allocation
• Enable faster response to emerging challenges

The key to this transformation lies in developing new measurements and metrics for human productivity and innovation potential[1]. By redefining how we measure value, we can create an economic system that more accurately reflects and rewards the true innovative capacity of human society.

The Innovation Standard: The Ingenesist Project

Solving the problems of the future will require humans to innovate at an astonishing rate… … far greater than anything our existing economic system can support.

In order to achieve this, there must be a fundamental shift in how knowledge assets are measured, curated, and exchanged.

Today, a traditional bank distributes money backed by your promise of FUTURE productivity.

Innovation is also a promise backed by FUTURE productivity. Two currencies backed by the same underlying asset are readily convertible.

In the future, an Innovation Bank, would issue currency backed directly by the true value of innovation. All we need to do is measure ourselves differently. 

The Ingenesist Project uses game theory, blockchain, and Artificial Intelligence to convert intangible assets into a more tangible form.

Join The Ingenesist Project

Analysis

Money as we know it just does not move fast enough. It does not represent the true productivity of Moms and Dads, soccer coaches, engineers, Scientists, teachers, and event organizers. Money needs to be produced as thenet sum of productive human behaviors. People know what problem needs to be solved next and if you give them the tools to fix things, they will.

Nature reveals a profound truth: collaboration often surpasses competition in creating sustainable, innovative solutions. Graph Neural Networks (GNNs) exemplify this principle by demonstrating how interconnected systems can preserve and enhance collective intelligence rather than eliminating potential contributors

The Limitation of Competition

Traditional competitive models require the cultivation of many losers to produce a single winner, which inherently wastes valuable knowledge and innovation potential

This approach, while seemingly efficient, actually diminishes the overall pool of wisdom and creativity that could benefit future solutions.

GNNs: A Model of Collaborative Intelligence

Graph Neural Networks demonstrate remarkable resilience and adaptability through their collaborative structure. Unlike competitive systems, GNNs can dynamically adjust to changes, preserve knowledge across nodes, and maintain functionality even when individual components are added or removed2. This inherent fault tolerance makes them particularly unsuitable for winner-take-all competition, but ideal for collaborative problem-solving.

Knowledge Preservation and Growth

The power of GNNs lies in their ability to:

• Process complex relationships between multiple agents simultaneously4
• Learn and adapt without requiring pre-programmed behaviors2
• Preserve and utilize information across the entire network5

Natural Collaboration in Action

GNNs mirror nature’s preference for collaboration over competition. Just as biological systems thrive through interconnected relationships, GNNs excel by:

• Creating dynamic, self-organizing networks that enhance collective intelligence
• Enabling multiple agents to work together while preserving individual contributions
• Building upon shared knowledge rather than eliminating alternatives

Through this collaborative approach, GNNs demonstrate how we can observe, measure, and curate knowledge assets more effectively than traditional competitive hierarchies. This allows organizations to mine talent, creativity, and wisdom continuously, leading to more robust and innovative solutions over time

Competition is one way of arriving at the optimal solution to a problem.

Some call it the “Law of Nature”, survival of the fittest – where the  final score can only be One to Zero.

Unfortunately, in order to feed the winner, we must cultivate suitable losers.  Evolution is slow and inefficient as a business optimization tool.   

The laws of Nature provide infinitely more examples of collaboration than competition. 

Even if one player does not win today, their capacity to innovate remains to continuously improve the game for everyone later … if we let them. 

The Ingenesist Project uses game theory, blockchain, and artificial intelligence to convert intangible assets into a more tangible form.   Join The Ingenesist Project

The Value of Networks

In the realm of innovation and technological advancement, the true value of human connections often goes unrecognized. However, as we’ve seen with network platforms like Uber, Google, and Airbnb, the power of connectivity can create trillions of dollars worth of “value’ without traditional assets

In fact, Facebook, Google, Alibaba, AirBnB, et al, could not exist if they were valued according to their physical replacement cost. Imagine what amazing works of engineering, science, and innovation do not exist today only because they are valued incorrectly.

Now, imagine applying this principle to a Graph Neural Network (GNN) of engineers, scientists, and technologists within Boomspace.

The Exponential Potential of Collaborative Genius

Unlike conventional social networks, a GNN of technical professionals represents a powerhouse of knowledge, creativity, and problem-solving capabilities. Each node in this network isn’t just a user; it’s a highly skilled individual with the potential to spark groundbreaking innovations

Synergistic Value Creation
When these brilliant minds interconnect, the value generated isn’t merely additive—it’s exponential. Every connection formed between experts from diverse fields opens up new possibilities for interdisciplinary breakthroughs.

Rapid Problem Solving
In this network, complex challenges that once took years to solve could be addressed in mere weeks or days. The collective intelligence of the network can be harnessed to tackle global issues, from climate change to healthcare crises.

The Boomspace Advantage

Boomspace’s GNN goes beyond simple connectivity. It leverages advanced AI to optimize collaborations, predict emerging trends, and identify complementary skill sets. This intelligent matchmaking of talent and ideas creates a fertile ground for innovation that far surpasses traditional R&D models.

Monetizing Intangible Assets
By quantifying the value of these connections and the intellectual property they generate, Boomspace transforms intangible assets into tangible wealth. Patents, research papers, and groundbreaking methodologies born from this network become invaluable commodities in the knowledge economy.

In essence, Boomspace’s GNN of technical professionals isn’t just a network—it’s an innovation accelerator with limitless potential. As Metcalfe’s Law suggests, the value of this network will grow exponentially with each new connection, making it an asset of immeasurable worth in the future of technological advancement and economic growth.

Video Transcript:

Network Effects: The Ingenesist Project

To borrow from a famous quote:  “Uber, owns no vehicles… Google and Facebook create no content… Alibaba holds no inventory… Airbnb owns no real estate….” But they have a combined value of almost 3 Trillion dollars. This is very interesting.

Whereas most companies are priced according to strict financial performance, Network platforms provide a virtual bridge that connects people to each other. They are priced proportional to the square of the number of human connections they serve.

This is known as Metcalfe’s Law of Network Value. If network platforms create a virtual bridge connecting people, why can’t we value real bridges using Metcalfe’s law?  Why can’t we value roads, airports, buildings and all manner of engineering, scientific, and technological infrastructure as proportional to the connections they serve? 

The Ingenesist project uses game theory, blockchain, and artificial Intelligence to convert intangible assets into a more tangible form. Join The Ingenesist Project

Unlocking Comprehensive Sustainability

In the intricate web of economic development, three key players form a powerful, albeit unorganized, alliance: banks, insurance companies, and engineers. This alliance, is identified in Boomspace as Virtuous Circle of Economic Development, is the cornerstone of sustainable growth and innovation.

An Interconnected Triad

At the heart of this circle lies a delicate balance:

• Banks provide crucial financing for engineering projects
• Insurance companies mitigate risks, making projects viable
• Engineers create tangible value through innovation and construction

When these elements work in harmony, they create a self-reinforcing cycle of progress. However, if any component falters, the entire system can grind to a halt.

Rethinking Value Creation

Traditionally, we’ve viewed money as the primary asset. But in reality, it’s merely a representation of the true value created by engineers, scientists, and technologists. The tangible assets—the innovations, infrastructure, and technologies—are the real drivers of economic growth.

The Vicious Circle: A Modern Challenge

Unfortunately, our current economic landscape often resembles a vicious circle rather than a virtuous one. The good news? This predicament is solvable.

The Ingenesist Project: A Revolutionary Approach

Enter the Ingenesist Project, a groundbreaking initiative leveraging three powerful tools:

1. Game Theory: To incentivize positive behaviors
2. Blockchain: To ensure transparency and trust
3. Artificial Intelligence: To optimize decision-making and resource allocation

This innovative approach aims to reverse the vicious circle, restoring the virtuous cycle of economic development.

A Call to Action

The challenges of the future demand rapid innovation—far beyond what our current financial systems can support. Traditional methods like venture capital are ill-equipped to handle the speed and complexity of technological change.By joining the Ingenesist Project, you can be part of the solution. Together, we can create a more efficient, responsive, and equitable economic system that serves global citizens and drives sustainable development.Are you ready to revolutionize economic development? Join the Ingenesist Project today and help shape a brighter future for all.

A bank won’t lend money to a project that is not insured. An insurance company will not underwrite a project that is not properly engineered. Engineering projects need to be financed to cover the cost of design and construction.

This is the Virtuous Circle of economic development. If any part of this cycle is broken, incomplete or corrupted, economic development fails.  

Financial institutions simply issue paper receipts called “Money” to represent the actual things that engineers, scientists, and technologists create.

Money is, in fact, the intangible asset and engineering is the tangible asset! We’ve gotten it backwards.

When a virtuous circle reverses itself, it becomes a vicious circle. This is where we are today Fortunately, this is an easier problem to solve.

The Ingenesist Project uses Game Theory, Blockchain, and Artificial Intelligence to reverse this vicious circle. 

Join The Ingenesist Project.

Technology Risk

Engineers, scientists, and technologists remove risk from complex systems.

It’s our superpower.

Risk is called “systemic” when  one risk impacts another risk resulting in a cascading network of failures.

This is compounded where the same technology created to decrease risk, can also be used to increase risk.    

However, the technology itself is not to blame. 

It is the people who have access to the technology who may introduce systemic risk.   

Engineers, Scientists, and Technologists have both, an obligation and an opportunity, to safeguard the application of our mutual creations.

The Ingenesist Project uses game theory, blockchain, and artificial intelligence to convert intangible knowledge assets to this more tangible form.

Join The Ingenesist Project

As an engineer and entrepreneur looking to create an EITL (Engineer-in-the-Loop) application for AI systems in financial and insurance markets, here are some business ideas based for removing risk from complex economic systems, inspired by this video above on technology risk:

AI-Augmented Risk Assessment Platform

Develop an AI-powered platform with EITL to assess and mitigate systemic risks in financial markets. This system would:

• Analyze market trends, economic indicators, and interconnected risks
• Employ engineers to oversee AI decision-making and provide expert insights
• Offer real-time risk assessments to financial institutions and regulators

Insurance Verification System

Create a decentralized insurance verification system using blockchain and AI, with EITL safeguards:

• Implement smart contracts for automated policy verification and claims processing
• Use AI to detect fraudulent claims and assess risk factors
• Incorporate engineers to review complex cases and improve system accuracy

Systemic Risk Modeling Tool for Regulators

Design a comprehensive modeling tool to help regulators identify and address systemic risks:

• Simulate various economic scenarios and their potential impacts
• Use EITL to ensure accurate interpretation of results
• Provide a collaborative platform for regulators, economists, and engineers

AI-Driven Investment Risk Management System

Develop an AI-powered investment risk management system with EITL for institutional investors:

• Analyze market data, economic indicators, and company-specific information
• Employ engineers to oversee risk assessments and provide expert insights
• Offer personalized risk management strategies

Cybersecurity Risk Assessment Platform for Financial Institutions

Create a specialized cybersecurity risk assessment platform with AI and EITL:

• Continuously monitor and analyze potential cyber threats
• Employ cybersecurity engineers to validate AI findings and develop mitigation strategies
• Provide real-time threat intelligence and customized security recommendations

These startup ideas leverage EITL to address systemic risks in complex financial systems while maintaining crucial human expertise in the decision-making process.

In today’s interconnected world of innovation, the traditional CV falls woefully short in capturing the true essence of engineers, scientists, and technologists. These professionals thrive on collaboration, cross-pollination of ideas, and the ability to tackle complex, multidisciplinary challenges.

A Graph Neural Network (GNN)

The GNN approach to representing their skills and connections offers a far more powerful and nuanced alternative. GNNs excel at modeling complex relationships and can capture the intricate web of collaborations, shared projects, and knowledge transfer that define the careers of technical professionals. By representing each individual as a node and their interactions as edges, a GNN can reveal patterns and potential synergies that a static CV could never hope to convey.

Predictive and prescriptive

This network-based approach aligns perfectly with the nature of scientific and technological work. It can highlight not just an individual’s skills, but also their role within larger ecosystems of innovation. A GNN could easily identify key connectors, bridge-builders between disciplines, and those with complementary skill sets for specific projects. Most importantly, the GNN could predict likelihood of future yet unknown outcomes.

Moreover, the dynamic nature of GNNs allows for real-time updates as professionals acquire new skills, complete projects, or forge new collaborations. This adaptability is crucial in rapidly evolving fields where traditional CVs quickly become outdated.

For hiring managers and project leaders, a GNN-based system would be transformative. It could suggest optimal team compositions, identify potential mentors, or flag rising stars in emerging fields. The ability to visualize and query this network would provide unprecedented insights into the collective capabilities of an organization or industry.

Ecosystem of talent

By embracing a GNN approach, we move beyond the limitations of two-dimensional representations. We create a living, breathing ecosystem of talent that truly reflects the collaborative and interconnected nature of modern scientific and technological endeavors. This shift isn’t just an improvement – it’s a necessary evolution to unlock the full potential of our collective mind and drive innovation forward.

Transcript:

The Resumé must Die – The Ingenesist Project

Knowledge is stored, transferred and applied by unique people with unique experiences in dimensions of space, time, context…  and the 6 known natural senses.

The resumé attempts to convey this complex asset by reducing it down to 2 dimensions to fit on a PDF file.

A computer reduces the resumé to imperfect keywords before passing it through filters for upload to the hiring team.

This isn’t how people are found, this is how they are lost.

The problems of the future can only be solved by diverse and strategic combinations of knowledge assets.

The Ingenesist Project uses game theory, blockchain, and artificial intelligence to convert intangible assets to a more tangible form. So that people can find each other. 

Join The Ingenesist Project

The WIKI-D algorithm, as described in the video, provides a structured approach to measuring intangible assets by leveraging the mathematical concept of derivatives. This is precisely how each “intangible” element of human capital – Wisdom, Innovation, Knowledge, Information, and Data – can be measured indirectly into a “tangible” existence:

Data: While data itself is tangible, its true value often lies in its volume, variety, velocity, and veracity. However, its qualitative worth can be inferred through the rate of change in how it is processed, stored, or analyzed. For instance, the increase in the number of data points processed per second can indicate the system’s ability to handle more complex data sets, which indirectly measures the efficiency and effectiveness of data management.

Information: Information’s value is derived from the aggregation, organization, and contextualization of data. The rate of change in data processing can serve as a proxy for the rate of change in information synthesis. By observing how quickly new information is generated or how effectively existing information is refined, one can gauge the system’s capacity to produce knowledge.

Knowledge: Knowledge, being a higher-order construct, cannot be directly measured. Instead, knowledge may be expressed proportional to the rate of change in information, which can be measured. Knowledge growth can be assessed by looking at how frequently new insights or updates are made to databases, knowledge graphs, at conferences, or expert systems. This rate of change reflects the system’s ability to learn and adapt, thereby quantifying knowledge indirectly.

Innovation: Innovation is proportional to the rate of change of knowledge. Here, the rate at which new products, services, or solutions are developed or improved upon can serve as a proxy for measuring innovation. The frequency and impact of academic papers, product releases, or significant updates to existing products indicate the rate of innovation within the system.

Wisdom: Wisdom, the culmination of the WIKI-D progression, is perhaps the most abstract. However, it can be measured indirectly by observing the rate of change in innovation. Wisdom can be inferred from the frequency and depth of systemic changes or paradigm shifts within the ecosystem, reflecting the integration of knowledge into a comprehensive understanding that leads to sustainable innovation.

By thinking of human capital as simple calculus, particularly the concept of derivatives, one can quantify the seemingly unquantifiable. Each derivative in the WIKI-D chain represents a change in the value of the previous layer, creating a clear path from raw data to ultimate wisdom. This approach allows for:

• Transparent Measurement: By focusing on the rate of change, we can quantify the velocity of progress in each tier of the value creation process.
• Fair Resource Allocation: Understanding where value is being generated helps in allocating resources efficiently.
• Collaborative Innovation: Measuring the rate of change promotes collaboration as it becomes clear where contributions are having the most impact.
• Reduced Ethical Concerns: A consensus-driven approach ensures that the development of wisdom is inclusive and ethical.

In conclusion, the WIKI-D algorithm, through its application of calculus, provides a practical framework for measuring intangible assets by focusing on their rate of change. This not only addresses the challenge of quantifying abstract concepts but also fosters a transparent, inclusive, and sustainable path to wisdom in the digital age.

Video Transcript

The WIKI-D Algorithm – The Ingenesist Project

The Ingenesist Project WIKI-D stands for Wisdom, Innovation, Knowledge, information, and Data.

The WIKI-D algorithm is also a series of Derivatives.

A derivative is something whose value is DERIVED from the value of something else.

The value of Information is derived from the value of our Data.

The value of Knowledge is derived from the value of our Information.

The value of Innovation is derived from the value of our Knowledge.

The value of Wisdom is derived from the value of our Innovations.

Together, this forms the WIKI-D algorithm – without which we cannot achieve Wisdom in the modern era. 

The Ingenesist Project uses game theory, blockchain, and artificial intelligence to convert intangible assets to a more tangible form.

Join the Ingenesist Project.