A Minimalist Framework for Equitable UBI

Abstract

This paper presents a minimalist framework for implementing a Universal Basic Income (UBI) system on a decentralized network. We address the fundamental challenges of digital identity verification through a lightweight proof-of-personhood mechanism, continuous distribution of resources via a "dripping" mechanism, and prevention of wealth concentration through carefully designed economic mechanisms. The framework incorporates value preservation and native demand generation, with particular emphasis on utilizing the UBI tokens to fund decentralized access to artificial intelligence services. We outline a minimal governance model that maintains system integrity while allowing for community-driven evolution. This approach represents a novel model for digital economic exchange that prioritizes human dignity, equitable distribution, and sustainable value creation.

Table of Contents

1. Introduction: The Fundamental Challenge
2. Minimalist Proof-of-Personhood
3. Continuous UBI Distribution: The Dripping Mechanism
4. Preventing Wealth Concentration: Economic Mechanisms
5. Value Preservation and Native Demand Generation
6. AI Provider Network: Monetizing Intelligence
7. Prompt Contracts: A New Paradigm
8. The AI-UBI Flywheel
9. Minimal Governance Design
10. Conclusion: A New Model for Digital Exchange
11. References

1. Introduction: The Fundamental Challenge

The concept of Universal Basic Income (UBI) has gained significant attention in recent years as a potential solution to growing economic inequality, technological displacement of jobs, and the evolving nature of work¹. As artificial intelligence and automation continue to transform labor markets², the need for new economic models becomes increasingly urgent. Studies suggest that up to 47% of US jobs are at high risk of automation in the coming decades³, making UBI not just a social policy choice but a potential economic necessity.

However, implementing UBI at scale presents several fundamental challenges that have remained difficult to solve within traditional economic frameworks. These challenges are particularly acute as we enter what some scholars call "The Second Machine Age"³, where the rapid advancement of AI technologies both necessitates and potentially enables new approaches to economic distribution.

The primary challenges include:

1. Identity verification: Ensuring each person receives exactly one allocation without invasive surveillance or complex bureaucracy.
2. Resource distribution: Creating a sustainable mechanism for continuous resource allocation.
3. Value preservation: Maintaining the economic value of distributed resources against inflation and speculation⁴.
4. Social acceptance: Building broad public support for the system across diverse communities.

Traditional approaches to these challenges have often relied on centralized authorities, extensive bureaucracy, and invasive verification processes. These solutions introduce significant inefficiencies, privacy concerns, and barriers to adoption, particularly for the most vulnerable populations who might benefit most from UBI.

This paper proposes a minimalist framework that leverages decentralized technologies and artificial intelligence to address these challenges with greater efficiency, privacy, and scalability than previously possible. We introduce a lightweight proof-of-personhood mechanism, a continuous "dripping" distribution model, and economic mechanisms designed to prevent wealth concentration while preserving value.

Crucially, we introduce a novel approach to generating native demand for the UBI token by creating a network of AI service providers that accept the token as payment. This creates a virtuous cycle where the distributed UBI tokens maintain their utility and value through active use in accessing increasingly essential AI services. This approach aligns with recent research showing the growing importance of AI services across all sectors of the economy⁵.

By reimagining both the verification and distribution components of UBI, as well as introducing native demand mechanisms through AI services, this framework offers a path toward implementing UBI at scale with minimal centralization and maximum accessibility. The integration of AI not only provides a sustainable funding mechanism but also ensures that the benefits of automation are more equitably distributed across society.

2. Minimalist Proof-of-Personhood

The foundation of any UBI system is the ability to verify unique human identities without duplication. Traditional approaches to this problem typically involve centralized identity systems, biometric data collection, or complex bureaucratic processes—all of which present significant privacy concerns, exclusion risks, and implementation barriers.

Our framework adopts a minimalist proof-of-personhood approach that prioritizes:

1. Minimal data collection: Gathering only the information absolutely necessary to verify uniqueness.
2. Privacy preservation: Ensuring personal data remains under individual control.
3. Accessibility: Creating verification paths that work across diverse contexts and capabilities.
4. Resilience against Sybil attacks: Preventing the creation of multiple artificial identities to claim multiple UBI allocations.

2.1 Multi-pathway Verification

Rather than relying on a single verification method, our framework implements a multi-pathway approach that allows individuals to establish their uniqueness through various means:

• Social graph verification: Leveraging existing social connections to verify identity through a web of trust model.
• Lightweight biometric checks: Using zero-knowledge proofs to verify uniqueness without storing actual biometric data.
• Community attestation: Enabling local communities to verify members through consensus mechanisms.
• Periodic re-verification: Implementing lightweight, non-invasive periodic checks to maintain system integrity.

Each pathway employs cryptographic mechanisms to generate a unique identifier that cannot be connected to an individual's personal information but can be verified as belonging to a unique human.

2.2 Progressive Security Model

The verification system employs a progressive security model where:

1. Initial verification requires meeting a basic threshold of proof.
2. The security requirements increase proportionally with the amount of UBI claimed over time.
3. Suspicious patterns trigger additional verification requirements rather than immediate exclusion.

This progressive approach prevents unnecessary barriers to entry while maintaining system integrity against sophisticated attacks.

2.3 Self-sovereign Identity Integration

The framework integrates with emerging self-sovereign identity standards, allowing individuals to:

1. Control their own verification data.
2. Select which verification pathways to use.
3. Revoke access to their verification information at any time.
4. Maintain portable verification across different UBI implementations.

By employing these minimalist verification mechanisms, the framework establishes a foundation for unique identity verification that respects individual privacy and dignity while preventing system abuse.

3. Continuous UBI Distribution: The Dripping Mechanism

Traditional economic distribution systems often rely on periodic payments or complex application processes. These approaches create artificial scarcity, administrative overhead, and can lead to feast-and-famine cycles for recipients. Our framework implements a continuous "dripping" distribution mechanism that fundamentally reimagines how resources are allocated.

3.1 The Continuous Drip Model

The core of our distribution system is a continuous dripping mechanism where:

1. UBI tokens are created and allocated to verified individuals at a constant rate—for example, one token per verified person per minute.
2. Tokens accumulate in personal accounts automatically without requiring claims or applications.
3. The dripping occurs regardless of whether the recipient actively engages with the system.
4. The dripping rate is algorithmically determined and adjusts based on system-wide metrics.

This continuous distribution model eliminates administrative barriers and creates a reliable resource flow that recipients can count on without interruption.

3.2 Temporal Distribution Benefits

The temporal nature of the dripping mechanism provides several advantages:

1. Predictability: Recipients can reliably anticipate their resource flow.
2. Reduced volatility: Continuous small distributions minimize market impact compared to large periodic distributions.
3. Natural velocity: The dripping encourages regular economic activity rather than hoarding.
4. Reduced stress: Recipients don't face anxiety about payment dates or approval processes.

3.3 Implementation Through Smart Contracts

The dripping mechanism is implemented through transparent smart contracts that:

1. Verify the recipient's proof-of-personhood status.
2. Calculate the exact token allocation based on elapsed time.
3. Execute the distribution without requiring manual intervention.
4. Provide transparent audit trails of all distributions.

The continuous dripping model represents a fundamental shift from traditional distribution mechanisms, better aligning with the goals of universal accessibility and minimal administrative overhead.

4. Preventing Wealth Concentration: Economic Mechanisms

A key challenge for any resource distribution system is preventing the inevitable concentration of wealth that occurs in most economies. Without mechanisms to counter this tendency, even the most equitable initial distribution will eventually lead to high inequality. Our framework incorporates several economic mechanisms specifically designed to maintain distribution equity over time.

4.1 Demurrage: Time-based Value Adjustment

The framework implements a demurrage mechanism where:

1. UBI tokens gradually decrease in value if left unused over extended periods.
2. The demurrage rate is calculated based on system-wide distribution metrics.
3. Active circulation of tokens resets the demurrage clock.
4. The demurrage applies proportionally to larger holdings, creating a progressive effect.

This mechanism discourages excessive accumulation and encourages active participation in the economy.

4.2 Network Fee Recycling

Transaction fees within the network are designed to:

1. Increase progressively with the size of the transaction.
2. Be recycled back into the UBI distribution pool rather than going to validators or miners.
3. Effectively create a micro-tax on large transactions that directly supports the UBI system.

This recycling mechanism creates a self-reinforcing loop where economic activity, particularly at large scales, directly supports the UBI distribution.

4.3 Diminishing Returns for Accumulation

The token mechanics implement diminishing returns for accumulation where:

1. Utility value per token decreases as individual holdings increase beyond certain thresholds.
2. Network capabilities for large token holders are capped at reasonable levels.
3. The system makes accumulation beyond personal use cases economically inefficient.

These mechanisms work together to create natural economic pressures against extreme wealth concentration without requiring heavy-handed centralized intervention.

5. Value Preservation and Native Demand Generation

A critical challenge for any UBI system is maintaining the value of the distributed resource. Traditional approaches often struggle with inflation, lack of acceptance, or artificial value manipulation. Our framework addresses these challenges through mechanisms that create genuine utility and demand for the UBI tokens, with artificial intelligence services playing a central role in value creation and preservation.

5.1 Utility-First Design

The UBI token is designed with utility as its primary value driver:

1. The token serves as the native payment method for essential AI services within the network.
2. Token utility grows with AI network adoption, creating a positive value feedback loop.
3. The token is designed to be easily integrated into existing economic systems.
4. AI services create tangible economic value that backs the token's worth.
5. The growing importance of AI in the economy ensures sustained token demand.

This utility-first approach ensures the token's value is derived from actual use rather than speculative investment, with AI services providing a foundation of real economic value.

5.2 Limited Monetary Policy

The token implements a transparent and predictable monetary policy:

1. Token creation is limited exclusively to the UBI distribution mechanism.
2. The creation rate is algorithmically determined based on the number of verified participants.
3. No additional tokens can be created through mining, staking, or administrative decisions.
4. The total supply adjusts automatically to match the exact needs of the participant population.

This limited monetary policy provides predictability while maintaining flexibility to accommodate growth.

5.3 Real-World Service Integration

The framework prioritizes integration with real-world services:

1. Partnerships with essential service providers who accept the UBI token.
2. Development of token-native services that create genuine utility.
3. Open standards for third-party integration to expand the token's utility ecosystem.

These integrations create natural demand for the token beyond its initial distribution, supporting value preservation.

6. AI Provider Network: Monetizing Intelligence

A cornerstone of our demand generation strategy is the creation of a decentralized AI provider network that accepts UBI tokens as payment. This network creates a vital utility loop where distributed tokens gain value through access to increasingly essential AI services.

6.1 Decentralized AI Access Model

The AI provider network implements a decentralized access model where:

1. Multiple AI service providers can join the network and offer various services.
2. Providers set their own rates in UBI tokens for different service tiers.
3. Users can access these services directly using their UBI tokens.
4. A standardized API allows seamless integration across different providers.
5. AI services contribute a portion of their revenue to the UBI pool, creating a sustainable funding mechanism.
6. Network effects drive both token utility and AI service quality improvements.

This open marketplace approach allows for competitive pricing and service diversity while maintaining the core token as the payment medium. The model creates a positive feedback loop where increased AI usage directly supports UBI sustainability.

6.2 Service Categories and Implementation

The network supports multiple AI service categories:

1. Text generation and analysis: Including writing assistance, translation, and information extraction.
2. Image and media creation: Enabling creative production without specialized skills.
3. Data analysis and insights: Providing valuable interpretation of complex information.
4. Personal AI assistants: Offering productivity and decision-making support.
5. Specialized domain expertise: Delivering professional-level guidance in fields like healthcare, education, and legal services.

Each category creates specific utility value for token holders, directly linking their UBI allocation to capabilities that would otherwise require significant financial resources.

6.3 Provider Incentive Structure

The provider network implements incentives for service providers through:

1. Access to a growing user base with guaranteed UBI token flow.
2. Reduced customer acquisition costs through network integration.
3. Simplified payment processing without traditional financial intermediaries.
4. Optional staking mechanisms that provide additional benefits to committed providers.

These incentives attract diverse AI service providers, creating a robust ecosystem where UBI tokens maintain constant demand and utility.

6.4 Democratizing AI Access

Beyond creating token utility, the AI provider network serves the social purpose of democratizing access to increasingly valuable AI capabilities:

1. UBI recipients can access cutting-edge AI services without additional financial resources.
2. The knowledge gap between those who can afford AI services and those who cannot is significantly reduced.
3. Universal access to AI capabilities creates broader economic opportunity and reduces technological inequality.

This democratization represents a powerful use case for UBI that directly addresses emerging technological divides in society.

7. Prompt Contracts: A New Paradigm

Traditional smart contracts, while powerful, often require complex programming knowledge and can be vulnerable to bugs and exploits⁶. Our framework introduces the concept of "prompt contracts" - a novel approach that leverages natural language processing and AI to create and execute agreements.

7.1 Natural Language Agreements

Prompt contracts allow users to:

1. Define agreements in natural language
2. Have AI interpret and formalize the terms
3. Execute actions based on AI-verified conditions
4. Resolve disputes through AI-mediated arbitration
5. Create complex economic arrangements without coding knowledge
6. Automatically enforce agreements while maintaining human understanding

This approach makes complex digital agreements accessible to all UBI recipients, regardless of technical expertise, while maintaining the rigor and automatability of traditional smart contracts.

7.2 AI-Powered Verification

The verification process utilizes:

1. Large language models for intent interpretation and term formalization
2. Multi-model AI for evidence verification and condition monitoring
3. Federated learning for contract pattern recognition and risk assessment
4. Zero-knowledge proofs for privacy preservation
5. Automated compliance checking against regulatory requirements
6. Continuous monitoring of contract execution and performance

This creates a more intuitive yet secure alternative to traditional smart contracts⁷, with AI systems ensuring both accessibility and reliability.

7.3 Integration with UBI Distribution

Prompt contracts enhance the UBI system by:

1. Automating conditional distributions based on natural language criteria
2. Enabling community-driven initiatives and mutual aid networks
3. Facilitating peer-to-peer exchanges without technical barriers
4. Creating new opportunities for economic coordination
5. Supporting flexible governance mechanisms
6. Enabling dynamic resource allocation based on community needs
7. Facilitating transparent and automated dispute resolution
8. Creating programmable money accessible to all users

7.4 Security and Trust

The prompt contract system maintains security through:

1. Multi-layer Verification: Multiple AI models verify contract interpretation
2. Human Oversight: Optional human review for high-stakes agreements
3. Risk Assessment: AI-powered evaluation of contract terms and conditions
4. Automated Auditing: Continuous monitoring of contract execution
5. Fallback Mechanisms: Clear procedures for edge cases and disputes
6. Version Control: Transparent history of contract evolution and amendments

7.5 Economic Implications

Prompt contracts create new economic possibilities by:

1. Reducing Barriers: Making programmable money accessible to all
2. Enabling Innovation: Supporting new forms of economic coordination
3. Improving Efficiency: Automating complex agreements without coding
4. Increasing Transparency: Making contract terms universally understandable
5. Supporting Flexibility: Allowing for dynamic and adaptive agreements
6. Democratizing Finance: Making complex financial instruments accessible

8. The AI-UBI Flywheel

The relationship between AI services and UBI distribution creates a powerful positive feedback loop that benefits both systems.

8.1 AI Funding UBI

AI services contribute to UBI sustainability through:

1. Revenue Generation: A percentage of AI service fees flows back to the UBI pool
2. Value Creation: AI services create tangible value that backs the UBI token
3. Network Effects: Growing AI utility attracts more service providers and users
4. Efficiency Gains: AI automation reduces system operational costs

8.2 UBI Democratizing AI

UBI distribution enhances AI adoption by:

1. Universal Access: Every verified person can access AI services
2. Innovation Incentives: Guaranteed income enables experimentation with AI tools
3. Data Quality: Diverse user base improves AI training data
4. Market Creation: UBI creates a reliable customer base for AI services

8.3 Synergistic Growth

The combination creates unique advantages⁸:

1. Economic Inclusion: AI benefits are widely distributed
2. Sustainable Funding: AI revenue supports UBI sustainability
3. Innovation Acceleration: Universal AI access speeds development
4. Social Impact: Reduced inequality in the AI economy

9. Minimal Governance Design

Effective governance is essential for any distributed system, but traditional governance models often become bureaucratic, captured by special interests, or disconnected from community needs. Our framework implements a minimal governance design that maintains system integrity while avoiding unnecessary centralization.

9.1 Limited Governance Scope

The governance system has deliberately limited scope, focused exclusively on:

1. Verification mechanism updates and security improvements.
2. Distribution rate adjustments based on predetermined metrics.
3. Economic parameter fine-tuning within predefined ranges.
4. Critical security responses to emerging threats.

All other aspects of the system operate according to transparent algorithmic rules without requiring governance intervention.

9.2 Multi-stakeholder Representation

The governance structure includes balanced representation from:

1. Verified recipients who receive the UBI allocation.
2. Service providers who accept the token for payments.
3. Technical contributors who maintain and improve the system.
4. Community representatives who advocate for diverse needs.

This balanced representation prevents capture by any single interest group.

9.3 Proposal and Implementation Process

The governance process follows a streamlined flow:

1. Transparent proposal submission visible to all participants.
2. Community discussion period with structured feedback.
3. Simulation of proposed changes in test environments.
4. Graduated implementation with automatic rollback mechanisms if predefined risk thresholds are triggered.

This process allows for system evolution while maintaining stability and predictability.

9.4 Governance Minimization Path

The governance system is designed to progressively minimize its own scope:

1. Initial governance handles a wider range of parameters during system stabilization.
2. As the system matures, more parameters become fixed or algorithmically determined.
3. The ultimate goal is a system that requires minimal active governance beyond security maintenance.

This minimization path aligns with the overall philosophy of reducing unnecessary centralization and complexity.

10. Conclusion: A New Model for Digital Exchange

The minimalist framework for equitable UBI presented in this paper represents a fundamental rethinking of how resources can be verified, distributed, and utilized in digital economies. By addressing the core challenges of identity verification, continuous distribution, wealth concentration, and value preservation, this framework offers a viable path toward implementing UBI at scale.

Several key innovations distinguish this approach:

1. The minimalist proof-of-personhood mechanism that verifies uniqueness without sacrificing privacy or accessibility.
2. The continuous dripping distribution model that eliminates administrative barriers and creates reliable resource flow.
3. The economic mechanisms that naturally prevent wealth concentration without heavy-handed intervention.
4. The AI provider network that creates genuine utility and demand for the UBI tokens while democratizing access to advanced technologies.

Together, these components create a self-reinforcing system where:

• Verification enables equitable distribution
• Distribution provides universal resource access
• Economic mechanisms maintain system equity
• The AI network creates token utility and value
• Minimal governance ensures system adaptability and security

This framework demonstrates that with thoughtful design, decentralized technologies can address complex socioeconomic challenges that have traditionally required extensive centralization and bureaucracy. By minimizing unnecessary complexity while maximizing individual agency, the system offers a new model for digital economic exchange that prioritizes human dignity, equitable distribution, and sustainable value creation.

As artificial intelligence continues to transform economic and social systems, this framework provides a mechanism to ensure that the benefits of these technologies are widely distributed. Rather than allowing AI advances to exacerbate existing inequalities, the UBI-AI integration creates a path toward more equitable technological progress.

The implementation of this framework represents not just a technical achievement but a reimagining of how resources can be shared within digital communities. It offers a concrete step toward economic systems that recognize the inherent dignity and value of each person while creating sustainable mechanisms for resource distribution in an increasingly automated world.

11. References

Footnotes

1. Standing, G. (2020). Battling Eight Giants: Basic Income Now. I.B. Tauris. ↩

2. World Economic Forum. (2020). The Future of Jobs Report 2020. World Economic Forum. ↩

3. Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W. W. Norton & Company. ↩ ↩²

4. Buterin, V. (2017). On Medium-of-Exchange Token Valuations. Retrieved from https://vitalik.ca/general/2017/10/17/moe.html ↩

5. Rolnick, D., et al. (2019). Tackling Climate Change with Machine Learning. arXiv preprint arXiv:1906.05433. ↩

6. Atzei, N., Bartoletti, M., & Cimoli, T. (2017). A Survey of Attacks on Ethereum Smart Contracts. Principles of Security and Trust, 164-186. ↩

7. Brown, T. B., et al. (2020). Language Models are Few-Shot Learners. arXiv preprint arXiv:2005.14165. ↩

8. Zhang, B. (2019). The Age of Artificial Intelligence: The Promise and Limitations of AI-Driven Growth. MIT Technology Review. ↩