The central theme of all human endeavors is cooperation. Throughout history, most endeavors were forced upon entire populations at the whim of people with power. Even today, a fraction of the population manipulates how the rest of the world lives and less than a hundred families own more than half the wealth. At the same time, twenty-thousand children die of hunger every day, while the war industry caters to the will and politics of a few individuals at the top.
The concept of what we know today as “nation” is built on ideas inherited from monarchy. There is always a central government with a head of the state backed by a centralized bank with an army and police force to enforce the will of the central authority with hierarchical power structures. The fundamental nature of socio-economic law, even in a democracy with periodic shifts in political power, continues to manifest the inherited centralized hierarchical concept. Various democratic models, established via manual processes, are limited to the state they are in.
The emergence of technologies that provide humanity with tools to self-govern in a flat world-order are increasing. This discussion paper presents a paradigm shifting socio-economic model oriented on emerging technologies. It proposes a future state model where the world is a self-organizing and self-correcting conglomeration of interdependent co-operations of individuals. Subsequently, it shows a transition plan from the contemporary state to the future state in a continuously evolving process. The plan addresses the hierarchical social order that has been embedded in the human psyche for millennia, as well as the dark side of the human psyche that strives for power and wealth at the cost of all else which is an obstacle to cooperation.
This discussion includes new concepts such as economic-gravity, decision-equivalency, and a crypto-currency-based intelligent financial system and shows that it is neither capitalism nor socialism. The model incentivizes the entrepreneurial spirit while enabling the minimum human rights of every individual and maximizes their wellbeing. Additionally, the model facilitates the mining of human potential via transparent and intelligent co-operation engines.
Natural Language Originated Smart Contract for a P2P Society
A NL to FL Translator: Combining Blockchain and Artificial Intelligence
The new paradigm brought forward in the Blockchain technology framework with the use of cryptography appears to be a proven secure and powerful, decentralized computing resource. However, each of the composing sub-systems, including Bitcoin, is a singleton with a unique purpose operating in a shared-state.
To generalize the approach, Ethereum and similar emerging solutions, enabled various users of the paradigm to have a distinct state and the ability to weave unique logic to establish smart contracts (SC) via formal languages (FL) using peer to peer messaging. While SCs are revolutionary, they require writing code in a cryptic FL (e.g. Solidity, Serpent) as well as a deep understanding of complex network protocols and related tools.
This ‘discussion paper’ generalizes the Ethereum journey a step further by implementing a translator solution that enables people to author and publish SCs and other digital artifacts in a natural language (NL), such as English, while leveraging an evolving taxonomy provided by a knowledge management hub. The intention is to usher in a true peer-to-peer (P2P) society where two or more people, or entities, can forge contracts between or among themselves without any knowledge or exposure to underlying technologies or programming languages. The proposed translator converts a Humanoid Contract (HC) into a SC while generating ancillary components and propagating the resulting assets into a Web3 (DApp) that has the ability to learn and evolve in real-time as new contracting needs arise between users of the DApp of the larger community of contract users.
Dynamic Co-op Chemistry Score (DCCS)
Computable solution using AI, IA, IoT, & Blockchain technologies
Trust, a primary human ingredient for cooperation, is binary in nature; who is trusting whom? While this ‘trust-ingredient’ is a psychological state between individuals or between collective-entities, it is also an outcome of direct or indirect interactions. Interactions enable people to know each other. Trust is very important in intra or inter cooperative (co-op) organizations.
The lexical definition of wellbeing is the state of being happy, healthy, or prosperous. The general perception of wellbeing is that it is a desired state of living.
The assertion for this discussion paper is that quality-of-life, wellbeing, for most people is enhanced through cooperative life-endeavors. The dynamic global socio-economic environment increasingly demands a greater need for cooperation among strangers. The paradox is that trust which is an outcome of prolonged interactions, is needed for the initiation of a cooperative endeavor.
A person’s cooperation and/or inclusion is dependent on reputation. Reputation is a reflection of a person or an entity. However, in today’s world, it is difficult and time-consuming to get to know one another with a high-degree of trust.
This discussion proposes a mechanism to substantiate the authenticity of the above claim that wellbeing is enhanced by cooperative endeavors and introduces a metric, dynamic co-op chemistry score (DCCS), that speeds up the trusting process by uniquely identifying an entity through multiple dimensions. Life is a continuous sequence of agreements that require trust. DCCS will facilitate by enabling people to know each other in ways that would otherwise take a lifetime. We will also discuss the how-factor such that this measurement can be implemented as a service and as a continuous associate of one’s being.
Immutable Neural Softchain of P2P Smart Contracts
Augmentation Natural Language based Smart Contract via AI & Blockchain
The Blockchain technology framework has demonstrated that this paradigm, on top of cryptography, is a secured, powerful, decentralized computing resource. However, each of the systems currently in Blockchain, including Bitcoin, is a singleton with a unique purpose and a shared-state.
The Ethereum layer introduced plurality by enabling the programming of Smart Contracts (SC). However, each contract stands by itself. In the real world, agreements are subject to amendments, they are referenced and/or replaced and, over time, they form a morphing interconnected socio-economic memory chain. The present SC scenario does not address amendments or other such chaining mechanisms.
The Softchain concept, introduced in this paper, is an augmentation to the prior paper that discusses authoring of SCs using natural language. Softchain allows a SC authored in a P2P (peer-to-peer) network scenario to be immutably soft-chained to a prior contract. Softchain provides the ability to link amendments of a contract together with reference to prior contracts of the same context, and/or amend digital-asset references in the same contract with history, if needed. This feature enables a historical representation of the immutable chain of agreements mimicking human behavior.
Softchain provides a memory structure to the roots of immutable memory-block composition, implemented via Blockchain (Ethereum or similar solutions) technology for representing socio-economic interconnectedness oriented on a holistic relational neural memory model. This discussion covers the mechanism to achieve collective memory via Softchain.
In this discussion, we present nuances associated with inter-human interaction and communication based on linguistics, personality, culture, emotion, context etc. We establish the difference between formal language (FL) that machines use and natural language (NL) that humans use. We introduce conduits that contemporary machines possess to perceive the world and the individuals it is interacting with along with stochastic detection of human emotions invoked via the subtle changes perceived using these conduits (sentiment from texts, speech, tone, vision etc.).
We then propose process; components and mechanisms for a machine to emulate a NL based conversation with an individual using statistical tools, machine language (ML) tools, artificial neural network (ANN), and other tools to accomplish the humanoid interaction experience. That is, the computer detects the personality and culture of an individual via interaction similar to a psychologist. The computer learns to understand and use individual-specific language that consists of mixed language, expressions, incorrect grammar, accent variations, geo-location-based connotations, etc. In this humanoid interaction, the machine reflects a persona back to the user to enhance the interaction.
Lastly, we present ways for machines to sense, measure, monitor and enhance an individual’s personalized experience and trends (e.g. trust, confidence, needs, perceptions etc.) evoked due to the machine enabling a humanoid user experience.