The Human Data Rights (HDR) Initiative aims to establish a global AI governance standard ensuring ethical AI, data ownership, and decentralized fairness. This project will develop the HDR Standard, integrating IPTO’s micro-licensing framework and Create Protocol’s Creative Agents to enable fair data and content usage for AI models. By leveraging SingularityNET’s AI marketplace, we will create human-first AI solutions while expanding community-driven AI governance through policy advocacy, content, and the HDR agent development based on Benvolent AGI framework. public drive: https://drive.google.com/drive/folders/1kaBrq272voujCOi1Dvfzn-wwgezL7kbN?usp=drive_link
How Our Project Will Contribute To The Growth Of The Decentralized AI Platform
Directly supports the BGI mission by establishing a Human Data Rights (HDR) Standard and integrating it into the Benevolent AGI Framework for ethical AI governance. Through IPTO’s micro-licensing and Create Protocol’s Creative Agents, we enable fair compensation and ethical AI content use. A global awareness campaign, AI compliance tools, and SingularityNET integration will drive human-first AI adoption, with Japan positioned to lead global AI governance standards.
Our Team
The team behind this proposal consists of experienced technologists and entrepreneurs: Abhishek Krishna, a serial technologist (abhishekkrishna.com), Dipankar Sarkar, a researcher with 60+ patents (dipankar.name); Noriko Shakti, a Japanese artist and entrepreneur (norikoshakti.com); Mochizuki Sumio, former MD at Mizuho Bank; and Warren Sauto, Ex Discovery, NGC and Singapore government; Vasu Madaan, SingularityNet Ambassador and Mindplex with an evergrowing list of contributors and advisors.
The Textual Emotion Recognition service helps the Human Data Rights (HDR) initiative by analyzing emotions in text to monitor online platforms for hate speech and harmful content analyze public sentiment on AI ethics and data privacy and enhance user interactions by detecting frustration or distress. This enables better moderation informed advocacy and empathetic engagement ensuring AI serves human well-being and protects data rights.
Speech Emotion Recognition service enhances the Human Data Rights (HDR) campaign by detecting emotional tones in voice data. It helps identify harmful speech (hate speech manipulation) analyze public sentiment on AI ethics and data rights enhance AI interactions by ensuring empathetic responses and monitor AI bias in voice applications. This ensures ethical AI-driven communication and supports responsible AI-human interactions.
The Philosophic Text Generation service can enhance the Human Data Rights (HDR) campaign by generating AI-driven reflections on ethics justice and human rights inspired by timeless philosophical thought. By connecting historical wisdom to modern AI challenges it helps frame data rights privacy and AI ethics in a broader moral and philosophical context fostering deeper public discourse and awareness on AI’s role in shaping human values and society.
IPTO: Intellectual Property Token Ownership
Type
New AI service
Purpose
IPTO ensures ethical AI data usage by allowing creators researchers and data owners to register track and monetize their intellectual property in AI training datasets. It supports transparent decentralized AI training while preventing unauthorized data exploitation. By integrating blockchain verification IPTO enhances AI fairness data rights and creator compensation in the AI-driven economy.
AI inputs
IPTO receives digital assets (text images music datasets) and verifies ownership using blockchain-based registration. Users can set usage permissions licensing terms and pricing models to control how their data is used in AI models while ensuring compliance with human data rights.
AI outputs
IPTO provides verified ownership records microlicense and smart contract-based monetization models for AI training datasets. Users receive traceability reports and compensation from AI companies compliant with ethical AI standards and transparency in AI data governance.
Create Protocol: Creative Agents
Type
New AI service
Purpose
Create Protocol: Creative Agents enables artists musicians designers and content creators to collaborate with AI-driven creative tools while maintaining ownership and monetization rights. It provides AI-generated content assistance ensures fair attribution and uses blockchain verification to protect intellectual property. The service supports ethical AI use in creative industries preventing data exploitation in AI training models.
AI inputs
The service takes creative inputs such as text music images or videos and processes them using AI models to assist in content generation enhancement and transformation. Users can define creative parameters licensing terms and ownership metadata ensuring data integrity and fair use policies.
AI outputs
Helps generates AI-assisted content including music visuals animations and written works while embedding ownership metadata and licensing details. Users receive verified IP protection usage tracking and monetization options ensuring creators retain control over AI-generated works.
The core problem we are aiming to solve
The rapid rise of AGI presents one of the most pressing socio-economic challenges of our time. Personal data is often harvested for AI training and for profit use without consent, traceability, stripping individuals of their rights and control. Meanwhile, human creativity and intellect, essential to AI’s progress, are undervalued, leaving contributors uncompensated. This imbalance results in the concentration of AI’s economic benefits in the hands of a few, exacerbating inequality and marginalizing the majority. This is not just a technological issue but a deep-rooted human rights challenge in the AI era making it a critical issue for future societies.
Our specific solution to this problem
The Human Data Rights (HDR) Initiative is creating a global HDR Standard to ensure ethical AI development, data ownership, and fair compensation for contributors of human-generated data. This framework enforces transparency, accountability, and compliance in AI governance.
Key integrations include IPTO’s micro-licensing system, which enables trackable, fair compensation for data contributors, and Create Protocol’s Creative Agents, ensuring ethical AI-driven content generation while preserving creator rights.
The Human Data Rights Agent further strengthens this ecosystem by helping companies and AI developers evaluate and enhance their AI and data workflows, identifying risks, ensuring HDR compliance, and offering automated recommendations for responsible data use. By integrating with SingularityNET’s AI marketplace, the agent helps certify AI models and organizations as HDR-compliant, promoting trust and ethical AI adoption.
Through these solutions, HDR fosters a decentralized, fair AI economy, leveraging Singularity Finance empowering businesses, developers, and individuals to adopt human-first AI governance while ensuring AGI evolves with ethical data rights at its core.
Project details
Detailed Description of the Project
Introduction
The rapid advancement of Artificial General Intelligence (AGI) presents one of the greatest socio-economic challenges of our time—ensuring AI development remains ethical, transparent, and beneficial to humanity. AI models are trained on vast amounts of human-generated data, creativity, and interactions, yet individuals receive no control, recognition, or compensation for their contributions. The concentration of AI’s economic benefits among a few corporations is increasing inequality, leaving independent creators, developers, and the general public excluded from the value they help generate.
To address these challenges, HumanDataRights.org is leading the development of a global Human Data Rights (HDR) Standard, which will provide a clear governance framework for AI systems to ensure that human data, content, and intellectual contributions are ethically handled and fairly compensated. This initiative integrates IPTO’s micro-licensing system, Create Protocol’s Creative Agents, and a new Human Data Rights Agent to establish practical, technology-driven solutions for AI governance, compliance, and ethical data management.
Key Problems We Aim to Solve
1. Data Exploitation & Lack of Ownership
AI systems extract and process vast amounts of human-generated content—personal data, online interactions, creative works—without consent or compensation. Individuals should have the right to own, control, and benefit from the data they generate, ensuring privacy, security, and fair use.
2. Undervaluation of Human Creativity
AI-generated media, art, and music are trained on human-created content without licensing or payment. Voice actors, musicians, artists, and writers have protested against AI companies exploiting their work without fair compensation. Without clear governance and legal protections, AI threatens to devalue human creativity and labor.
3. Economic Disparity in AI Value Creation
The AI economy is highly centralized, benefiting a handful of corporations and investors while excluding the wider public. AI tools disrupt industries and automate jobs without creating fair redistribution models to support affected workers and creators. The wealth generated by AI must be more equitably shared.
4. Lack of AI Governance & Ethical Standards
Most AI systems operate as black boxes, making critical decisions without transparency, accountability, or ethical oversight. Without global AI governance frameworks, AI can reinforce bias, deepen inequality, and violate privacy at an unprecedented scale.
Our Solution & Strategic Approach
1. Establishing the Human Data Rights Standard
To ensure AI serves humanity rather than exploits it, we are developing the Human Data Rights (HDR) Standard, a Benevolent AGI integrated framework focused on:
Legal protections for data ownership, ensuring individuals can control, license, and monetize their data.
Fair AI training dataset policies, requiring AI models to transparently document data sources and compensate human contributors.
Economic models for AI value distribution, enabling royalties, licensing, and compensation models for those whose data fuels AI advancements.
Integration into global governance frameworks, advocating for HDR adoption within AI policy and Benevolent AGI framework.
This open-source standard will provide clear compliance guidelines for companies, developers, and AI organizations to ensure AI models are trained, deployed, and monetized ethically.
2. IPTO’s Micro-Licensing & Data Rights Integration
A core part of this initiative is the integration of IPTO’s micro-licensing technology, which enables:
Transparent, trackable AI training data licensing, allowing individuals to retain control over their contributions.
Fair compensation for human data contributors, ensuring monetary and attribution rights are built into AI models.
AI-generated content monetization, helping artists, musicians, and developers license and sell their work to AI models in a fair and trackable way.
With IPTO, AI developers and corporations will be able to legally and transparently acquire licensed data, ensuring ethical compliance while supporting decentralized AI value distribution.
3. Create Protocol’s Creative Agents for Ethical AI
The Creative Agents developed by Create Protocol provide a decentralized, AI-driven content generation ecosystem that:
Protects the rights of creators using blockchain-powered licensing models.
Ensures that AI-generated media respects original human contributions.
Enables decentralized AI ownership, allowing creators to retain control over AI-assisted content production.
This system prevents AI from becoming a tool for content exploitation and ensures that human creators remain central in AI-driven media production.
4. Human Data Rights Agent: Ensuring Ethical AI Compliance
The Human Data Rights Agent is an AI-powered compliance tool designed to help companies, developers, and AI organizations implement HDR-aligned ethical AI workflows.
Data Compliance Audits: Evaluates AI data collection and usage against HDR principles.
Transparency & Risk Detection: Identifies potential ethical risks in AI decision-making.
Automated Compliance Recommendations: Suggests improvements for aligning AI models with HDR policies.
Micro-License Integration: Works with IPTO and Create Protocol’s licensing models to ensure that AI data contributors are fairly compensated.
SingularityNET Integration: Certifies AI models within SingularityNET’s marketplace as HDR-compliant, ensuring decentralized AI ethics adoption. Listed with SingularityNet AI Marketplace.
This agent acts as a practical tool for businesses and AI organizations to self-regulate and ensure responsible AI development.
Strategic Implementation: Awareness & Adoption
1. Global AI Governance Awareness Campaign
To drive mass adoption of the HDR Standard, we will launch a high-impact awareness campaign through:
Educational media (videos, articles, and infographics) to explain AI governance, data rights, and fair AI monetization.
Global PR and policy discussions, ensuring HDR adoption within AI industry standards.
Partnerships with AI leaders, researchers, and organizations, bringing AI governance into mainstream tech discussions.
Japan as a leader in AI ethics, working with Japanese institutions and policymakers to push forward AI regulation precedents.
The Role of SingularityNET & Strategic Partners
SingularityNET’s decentralized AI marketplace aligns with our vision for open, fair, and ethical AI ecosystems. Their support will:
Amplify HDR adoption, integrating the standard into decentralized AI governance.
Facilitate AI compliance, allowing SingularityNET AI services to integrate HDR policies.
Help drive industry adoption, ensuring AI developers and enterprises align with ethical AI guidelines.
By collaborating with leading AI organizations, Web3 developers, and policymakers, HDR will become a core framework for ethical AI worldwide.
Conclusion
The future of AI must be human-first, ensuring AI respects data sovereignty, transparency, and fair value distribution. The Human Data Rights Initiative is taking a stand to ensure that AI is developed ethically, integrating Benevolent AGI framework, micro-licensing technology, and compliance tools to enable fair AI adoption at scale.
Through:
The HDR Standard for global AI governance
IPTO’s micro-licensing for data ownership and compensation
Create Protocol’s Creative Agents for ethical AI-generated content
The HDR Agent for AI compliance and responsible governance
We are paving the way for a decentralized, fair AI economy that benefits individuals, not just corporations.
As this is a mass awareness campaign, we will run a large volunteer program engaging students, researchers, and ethical AI advocates to help with content creation, outreach, and event coordination. We seek support in media amplification, PR, and content distribution to reach a broader audience. A dedicated contact point within SingularityNET would be beneficial for aligning efforts, leveraging their network, and ensuring integration with decentralized AI initiatives. Additionally, partnerships with universities, decentralised media networks like Mindplex, and AI governance bodies will strengthen the impact of this movement.
Existing resources
We have strong partnerships in Japan with various companies, universities, and organizations that will support outreach and campaign execution. These include relationships with government and startup bodies such as Tokyo Metropolitan Government, Builders Weekend, and TAI (Tokyo AI community).
On the technology front, we will leverage solutions built by our founding team, such as:
IPTO.ai – A decentralized data and IP monetization platform that enables ethical AI data usage, which aligns perfectly with the human data rights movement.
These platforms and existing networks will support the campaign’s execution, provide real-world solutions, and amplify its impact.
Open Source Licensing
GNU GPL - GNU General Public License
Open-Source Licensing for the Human Data Rights Standard
The Human Data Rights Standard will follow a multi-license approach, ensuring that different components of the framework—governance models, AI tools, and datasets—are appropriately protected while remaining open, transparent, and accessible for global adoption.
GNU General Public License (GPL) 3.0 – For software tools, AI governance solutions, and privacy frameworks developed under this initiative. This ensures that any modifications remain open-source and cannot be privatized by corporations.
Creative Commons Attribution-ShareAlike 4.0 (CC BY-SA 4.0) – For the policy and governance framework, allowing it to be freely adopted while requiring any modifications to maintain the same open and ethical principles.
Open Data Commons Public Domain Dedication (PDDL) – For public AI datasets, ensuring they remain freely accessible for ethical AI research and development.
Links and references
Perl Programming Language: Perl is distributed under both the Artistic License and the GNU General Public License (GPL). This dual licensing offers users the flexibility to choose the terms under which they prefer to use the language, accommodating both open-source and proprietary needs.GitHub
Mozilla Firefox: Mozilla's flagship browser is released under a tri-license scheme: the Mozilla Public License (MPL), the GPL, and the Lesser General Public License (LGPL).
Placeholder for Spotlight Day Pitch-presentations. Video's will be added by the DF team when available.
Total Milestones
4
Total Budget
$50,000 USD
Last Updated
24 Feb 2025
Milestone 1 - Foundation & Awareness Activation
Description
This phase lays the foundation for Human Data Rights’s public narrative branding and awareness efforts ensuring a strong launch within AI governance discussions. Key activities include:
Finalizing the HDR Standard v1 framework defining data rights licensing models and ethical AI policies.
Creating initial educational content including 2+ short videos 2+ blog articles and infographics introducing HDR principles.
Developing outreach materials for PR and media engagement positioning HDR in AI governance ethics and Web3 discussions.
Soft-launching a social and media awareness campaign to engage AI developers researchers and policymakers.
Technical groundwork for HDR IPTO and Create Protocol integration with SingularityNET ensuring AI models comply with ethical licensing and governance principles.
Deliverables
Human Data Rights website and knowledge base.
HDR Standard v1 framework drafted covering data rights ethical AI policies and governance principles.
5+ initial content pieces produced and distributed across video blogs educational content infographics and articles explaining HDR’s significance and the ecosystem.
At least 5 key AI developers researchers or policymakers onboarded providing early feedback and adoption pathways.
Partnerships with decentralized AI organizations initiated securing early adoption.
SingularityNET onboarding roadmap finalized ensuring integration of HDR standards into AI marketplace services.
HDR Agent compliance framework outlined detailing AI auditing licensing and compliance mechanisms.
Integration plans for IPTO’s micro-licensing and Create Protocol’s Creative Agents finalized ensuring aligned Benevolant AGI framework.
Budget
$12,500 USD
Success Criterion
HDR Standard website and initial setup done.
Campaign strategy and messaging finalised.
5+ high-quality content pieces created for future rollout.
SingularityNET engagement initiated.
IPTO & Create Protocol alignment roadmap with SingularityNet.
Milestone 2 - HDR Standard Refinement & v1 for IPTO
Description
This phase focuses on rolling out the first wave of content launching the HDR Standard awareness campaign expanding industry partnerships and introducing the MVP of IPTO’s micro-licensing framework. This milestone is crucial for driving global engagement ensuring AI governance discussions and positioning HDR as a key standard in ethical AI development.
Key activities include:
Publishing 5+ videos blog articles and infographics explaining the HDR Standard AI ethics decentralized governance and human data ownership.
Launching the HDR awareness campaign promoting data rights and ethical AI governance through targeted media outreach and Web3 industry partnerships.
Engaging AI developers researchers and policymakers ensuring HDR gains adoption within SingularityNET and other AI ecosystems.
Hosting discussions and collaborations with decentralized AI projects exploring how HDR compliance can be integrated into AI and blockchain-based governance models.
Strengthening strategic partnerships expanding relationships with AI governance bodies Web3 networks and decentralized AI initiatives.
Rolling out the MVP of IPTO’s micro-licensing framework beta enabling creators and developers to track license and monetize their data ethically within AI-driven ecosystems.
Targeting PR and industry visibility securing media coverage in AI ethics Web3 governance and AI compliance discussions.
Deliverables
10+ high-quality content pieces published including explainer videos blog articles and infographics covering HDR Standard AI ethics decentralized governance and data ownership introducing HDR to AI developers policymakers and Web3 communities.
HDR awareness campaign launched distributing content across social media AI and Web3 forums newsletters and research communities ensuring broad discussion of HDR compliance and AI governance frameworks.
Strategic partnerships expanded securing collaborations with AI developers researchers and Web3 initiatives to support HDR adoption and integration into decentralized AI models including SingularityNET and AI governance bodies.
Initial industry discussions on HDR adoption engaging AI projects in forums panels and expert discussions aligning AI model development with ethical data principles.
MVP launch of IPTO’s micro-licensing framework providing a working system for creators and developers to track license and monetize their data ethically within AI ecosystems with select users testing the model.
Industry PR and media features secured increasing visibility through AI ethics publications Web3 news and governance think tanks driving awareness on ethical AI licensing and compliance frameworks like articles published in Mindplex magazine
Budget
$12,500 USD
Success Criterion
10+ content pieces successfully published like articles published in Mindplex magazine.
HDR awareness campaign launched, reaching AI and Web3 stakeholders.
IPTO MVP successfully rolled out and tested.
Human Data Rights Standard v1 draft made and opened for public discussion and refinement.
Expanding the engagement and collaborations with BGI Nexus community (50 + members).
Milestone 3 - HDR Standard Integration HDR Agent Development
Description
Building on the momentum from the HDR Standard awareness campaign and the launch of IPTO’s micro-licensing MVP this phase focuses on integrating HDR compliance mechanisms into decentralized AI ecosystems advancing IPTO adoption and beginning early-stage HDR Agent development. AI governance discussions continue to evolve and the HDR Standard is refined further with real-world insights from industry experts and AI developers.
Key activities include:
Expanding IPTO integration enabling developers and businesses to implement micro-licensing models within AI workflows ensuring ethical data monetization and fair compensation mechanisms.
Strengthening SingularityNET integration working with AI model developers to align AI services with HDR Standard compliance measures.
Publishing HDR Standard v1.5 incorporating feedback from industry leaders policymakers and AI developers based on real-world adoption experiences.
Developing the foundational architecture for the HDR Agent defining its technical specifications and AI governance capabilities.
Conducting pilot discussions and case studies with AI developers research groups and policymakers ensuring the HDR compliance model is actionable and scalable.
Producing 5+ in-depth content pieces explaining HDR’s role in AI governance how IPTO’s licensing model works and how businesses can adopt HDR compliance tools.
Deliverables
Expanded IPTO integration allowing businesses and AI developers to implement ethical micro-licensing models for AI-generated content and data use.
Refined HDR Standard v1.5 published integrating industry feedback updated governance models and ethical licensing principles.
Early HDR Agent development initiated defining technical architecture AI auditing capabilities and governance enforcement strategies for rollout in Phase 4.
SingularityNET AI model adoption expanded ensuring HDR compliance mechanisms are tested and refined in decentralized AI ecosystems.
Pilot discussions and case studies conducted providing real-world implementation insights for HDR Standard compliance.
10+ advanced content pieces published including technical deep dives policy explainers and case studies educating AI developers and businesses on HDR adoption.
Strengthened industry partnerships onboarding new AI and Web3 governance initiatives to promote HDR adoption and compliance mechanisms. Pilot discussions initiated with 5 + SingularityNet spinoff projects. (Mindplex Singularity Finance Rejuve.ai TrueAGI Zarqa).
Discussions for integration of Creative agents with JamGalaxy. Ideation and panel discussion with Singularity Finance to push the common vison for user led data economy.
Utilise the network effects with Singualrity Finance and other ecosystem partners.
Ecosystem Synergy: By focusing on various components of the AI value chain we will be able to utilise the network effects.
Budget
$12,500 USD
Success Criterion
IPTO integration expanded with real AI adoption.
HDR Standard v1.5 published with industry feedback.
Human Data Rights Agent development roadmap finalised.
Initial HDR Agent architecture defined.
SingularityNET AI models testing HDR compliance.
Pilot discussions and collaborations initiated with 5 + SingularityNet spinoff projects. (Mindplex, Singularity Finance, Rejuve.ai, TrueAGI, Zarqa, Jamgalaxy, Sophiaverse)
Milestone 4 - 12500
Description
The final phase focuses on fully deploying the HDR Standard scaling adoption launching the HDR Agent and finalizing industry integration efforts. By this stage AI developers businesses and Web3 platforms will have access to HDR-compliant governance tools ensuring ethical AI development and compliance mechanisms are widely adopted.
Key activities include:
Final release of HDR Standard v2 establishing a global benchmark for AI ethics data governance and compliance models.
Full rollout of the HDR Agent providing AI developers and businesses with compliance verification transparency tracking and automated governance tools.
Expanding integration across SingularityNET AI models allowing AI services to assess and certify compliance with HDR principles.
Finalizing IPTO micro-licensing adoption ensuring AI-generated content and data usage align with ethical compensation and governance models.
Driving widespread adoption through PR industry partnerships and developer engagement ensuring HDR becomes a widely accepted compliance standard.
Publishing 5+ high-impact content pieces demonstrating real-world applications of HDR compliance tools and AI governance frameworks.
Establishing a sustainability roadmap ensuring HDR remains a long-term evolving governance model beyond this funding phase.
Deliverables
HDR Standard v2 finalized and released integrating comprehensive AI governance principles licensing frameworks and compliance structures.
HDR Agent beta fully deployed enabling AI auditing compliance verification and transparency reporting within AI-driven ecosystems.
SingularityNET AI services fully integrated providing AI developers and businesses with HDR compliance certification mechanisms.
IPTO micro-licensing adoption expanded ensuring AI-generated content and data transactions align with HDR governance models.
5+ high-impact content pieces published detailing real-world use cases developer guides and policy recommendations for HDR adoption.
Final PR and media outreach campaign executed securing global industry recognition for HDR as a leading AI governance framework.
Sustainability roadmap published outlining long-term governance structures community involvement and future funding strategies for HDR. Creative agents alpha launched.
Budget
$12,500 USD
Success Criterion
Human Data Rights Standard v2 fully released and adopted.
HDR Agent v1 beta launched and in use for AI compliance.
SingularityNET AI models implementing HDR certification.
IPTO micro-licensing widely adopted in AI workflows.
Creative Protocol Creative Agents alpha launched.
Long term vision document for further growth of Human Data Rights movement drafted and opened for public description.
Strategic Alignment with SingularityNET and the Artificial Superintelligence Alliance (ASI) to reach benevolent AGI.
Reviews and Ratings in Deep Funding are structured in 4 categories. This will ensure that the reviewer takes all these perspectives into account in their assessment and it will make it easier to compare different projects on their strengths and weaknesses.
Overall (Primary) This is an average of the 4 perspectives. At the start of this new process, we are assigning an equal weight to all categories, but over time we might change this and make some categories more important than others in the overall score. (This may even be done retroactively).
Feasibility (secondary)
This represents the user's assessment of whether the proposed project is theoretically possible and if it is deemed feasible. E.g. A proposal for nuclear fission might be theoretically possible, but it doesn’t look very feasible in the context of Deep Funding.
Viability (secondary)
This category is somewhat similar to Feasibility, but it interprets the feasibility against factors such as the size and experience of the team, the budget requested, and the estimated timelines. We could frame this as: “What is your level of confidence that this team will be able to complete this project and its milestones in a reasonable time, and successfully deploy it?”
Examples:
A proposal that promises the development of a personal assistant that outperforms existing solutions might be feasible, but if there is no AI expertise in the team the viability rating might be low.
A proposal that promises a new Carbon Emission Compensation scheme might be technically feasible, but the viability could be estimated low due to challenges around market penetration and widespread adoption.
Desirability (secondary)
Even if the project team succeeds in creating a product, there is the question of market fit. Is this a project that fulfills an actual need? Is there a lot of competition already? Are the USPs of the project sufficient to make a difference?
Example:
Creating a translation service from, say Spanish to English might be possible, but it's questionable if such a service would be able to get a significant share of the market
Usefulness (secondary)
This is a crucial category that aligns with the main goal of the Deep Funding program. The question to be asked here is: “To what extent will this proposal help to grow the Decentralized AI Platform?”
For proposals that develop or utilize an AI service on the platform, the question could be “How many API calls do we expect it to generate” (and how important / high-valued are these calls?).
For a marketing proposal, the question could be “How large and well-aligned is the target audience?” Another question is related to how the budget is spent. Are the funds mainly used for value creation for the platform or on other things?
Examples:
A metaverse project that spends 95% of its budget on the development of the game and only 5 % on the development of an AI service for the platform might expect a low ‘usefulness’ rating here.
A marketing proposal that creates t-shirts for a local high school, would get a lower ‘usefulness’ rating than a marketing proposal that has a viable plan for targeting highly esteemed universities in a scaleable way.
An AI service that is fully dedicated to a single product, does not take advantage of the purpose of the platform. When the same service would be offered and useful for other parties, this should increase the ‘usefulness’ rating.
About Expert Reviews
Reviews and Ratings in Deep Funding are structured in 4 categories. This will ensure that the reviewer takes all these perspectives into account in their assessment and it will make it easier to compare different projects on their strengths and weaknesses.
Overall (Primary) This is an average of the 4 perspectives. At the start of this new process, we are assigning an equal weight to all categories, but over time we might change this and make some categories more important than others in the overall score. (This may even be done retroactively).
Feasibility (secondary)
This represents the user\'s assessment of whether the proposed project is theoretically possible and if it is deemed feasible. E.g. A proposal for nuclear fission might be theoretically possible, but it doesn’t look very feasible in the context of Deep Funding.
Viability (secondary)
This category is somewhat similar to Feasibility, but it interprets the feasibility against factors such as the size and experience of the team, the budget requested, and the estimated timelines. We could frame this as: “What is your level of confidence that this team will be able to complete this project and its milestones in a reasonable time, and successfully deploy it?”
Examples:
A proposal that promises the development of a personal assistant that outperforms existing solutions might be feasible, but if there is no AI expertise in the team the viability rating might be low.
A proposal that promises a new Carbon Emission Compensation scheme might be technically feasible, but the viability could be estimated low due to challenges around market penetration and widespread adoption.
Desirability (secondary)
Even if the project team succeeds in creating a product, there is the question of market fit. Is this a project that fulfills an actual need? Is there a lot of competition already? Are the USPs of the project sufficient to make a difference?
Example:
Creating a translation service from, say Spanish to English might be possible, but it\'s questionable if such a service would be able to get a significant share of the market
Usefulness (secondary)
This is a crucial category that aligns with the main goal of the Deep Funding program. The question to be asked here is: “To what extent will this proposal help to grow the Decentralized AI Platform?”
For proposals that develop or utilize an AI service on the platform, the question could be “How many API calls do we expect it to generate” (and how important / high-valued are these calls?).
For a marketing proposal, the question could be “How large and well-aligned is the target audience?” Another question is related to how the budget is spent. Are the funds mainly used for value creation for the platform or on other things?
Examples:
A metaverse project that spends 95% of its budget on the development of the game and only 5 % on the development of an AI service for the platform might expect a low ‘usefulness’ rating here.
A marketing proposal that creates t-shirts for a local high school, would get a lower ‘usefulness’ rating than a marketing proposal that has a viable plan for targeting highly esteemed universities in a scaleable way.
An AI service that is fully dedicated to a single product, does not take advantage of the purpose of the platform. When the same service would be offered and useful for other parties, this should increase the ‘usefulness’ rating.
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