AI Assistant for Governance: Empowering Team-Based dReps

[GENERAL] Name and surname of main applicant

[GENERAL] Are you delivering this project as an individual or as an entity (whether formally incorporated or not)

[GENERAL] Please specify how many months you expect your project to last (from 2-12 months)

[GENERAL] Please indicate if your proposal has been auto-translated into English from another language

[GENERAL] Summarize your solution to the problem (200-character limit including spaces)

Photrek will develop an AI Assistant that empowers Team-Based dReps, analyzes proposals, assesses their impact across Cardano, and guides decisions aligned with the community & the constitution.

[GENERAL] Does your project have any dependencies on other organizations, technical or otherwise?

[GENERAL] If YES, please describe what the dependency is and why you believe it is essential for your project’s delivery. If NO, please write “No dependencies.”

No dependencies.

[GENERAL] Will your project’s output/s be fully open source?

[GENERAL] Please provide here more information on the open source status of your project outputs

Project will be fully open source.

Photrek utilizes a GNU GPL 3.0 license for other projects, which requires users of the software to maintain their code as open source. We will consider if this is the appropriate license to use for the dRep AI Assistant.

[SOLUTION] Please describe your proposed solution

Photrek's Expertise in Action: Empowering dReps through AI

Photrek, a team with proven experience in machine learning, AI development, and risk intelligence, is actively involved in the SingularityNET community. This involvement showcases our alignment with cutting-edge advancements in AI and our commitment to responsible AI development principles. We propose an AI Agent designed to function as an assistant within Sociocratic dRep Circles, leveraging our expertise in decentralized governance to empower Team-Based dReps.

A Multi-Phased Approach:

This proposal outlines the first phase of a comprehensive plan to integrate AI into dRep decision-making. We aim to conduct a series of increasingly complex experiments, with each stage building upon the successes of the previous one.

Phase 1: AI Assistant for dReps (Funded by this Proposal)

• LLM-powered AI Assistant : We will develop an LLM-powered AI Assistant specifically trained on a comprehensive dataset tailored for Cardano's governance environment. This data will include:
• Cardano Improvement Proposals (CIPs): Past and present proposals to understand the scope and nature of governance issues.
• Community Discussions: Forum discussions, social media conversations, and other channels where the Cardano community debates proposals and governance.
• Cardano Constitution: To ensure the AI Assistant operates within the legal framework.
• Historical Data (if available): Past voting records, dRep decisions, and data on the impact of implemented proposals to provide context for future decision-making.
• Data Quality & Labeling: We will prioritize high-quality, unbiased data and consider labeling specific elements (e.g., key arguments, sentiment analysis) to guide the LLM's learning process.
• Technical Considerations: The LLM will be built on a robust and scalable architecture, leveraging advancements in machine learning to ensure efficient processing and analysis of large datasets.
• Circle Discussions & Analysis: This AI Assistant will act as a valuable asset within dRep Circles, assisting with discussions by:
• Summarizing key points of proposals.
• Identifying potential impacts (economic, social, technical, and environmental if Photrek's experience is applicable).
• Highlighting relevant sections of the Cardano constitution.
• Analyzing the proposed organizational design of the project: The AI Assistant can leverage its understanding of successful governance models and historical data on Cardano to assess the strengths and weaknesses of proposed team structures. It can provide insights into:
• Team size and composition: Whether the proposed team has the necessary expertise and resources to effectively execute the project.
• Decision-making processes: Are the proposed decision-making procedures aligned with Cardano's governance framework and efficient for the team's size and goals?
• Incentive structures: Does the proposed design create a fair and motivating incentive structure for team members?
• Providing data-driven insights and recommendations to guide informed decision-making.

This initial phase lays the groundwork for future advancements, empowering dReps with a powerful AI tool to navigate Cardano's evolving landscape.

Future Phases (Not Funded by this Proposal):

• Integration as a dRep Circle Peer: Building upon Phase 1, we envision a future where the AI Agent seamlessly integrates as an equal peer within Sociocratic dRep Circles. This will involve advanced functionalities for:
• Proposing plans of action.
• Raising paramount objections.
• Engaging in discussions and collaboratively resolving objections.
• Multi-Agent Sociocratic Circles: The ultimate vision is a network of AI Agents forming self-governing Sociocratic Circles, capable of independent decision-making within the framework of Cardano's governance.

By leveraging Photrek's expertise and this phased approach, we propose a groundbreaking solution that empowers dReps, fosters informed decision-making, and strengthens Cardano's decentralized governance structure.

[IMPACT] Please define the positive impact your project will have on the wider Cardano community

Impact of AI Assistant on the Cardano Community

The proposed AI Assistant has the potential to significantly enhance Cardano's Governance by empowering dReps, strengthening decision making processes, and increasing accessibility for the wider Cardano community. Here's a breakdown of the key benefits:

Empowering dReps:

• Informed Decision-Making: The AI Assistant equips dReps with data-driven insights and comprehensive analysis of proposals, leading to more informed decisions that benefit the Cardano ecosystem.
• Improved Efficiency: By automating tasks like proposal summarization and impact assessment, the AI Assistant frees up dRep time, allowing them to focus on collaborative decision-making and strategic discussions.
• Enhanced Collaboration: Features like shared workspace and discussion forums foster better communication and collaboration within dRep teams, leading to more effective governance.

Strengthening Governance:

• Increased Voter Confidence: Transparent and data-driven decision-making processes supported by the AI Assistant bolster voter confidence in the governance system.
• Improved Representation: By empowering dReps with better tools and resources, the AI Assistant indirectly contributes to improved representation of voter needs within the Cardano ecosystem.
• Reduced Risk of Errors: The AI Assistant's ability to identify potential issues and analyze proposals against the Cardano constitution minimizes the risk of errors in governance decisions.

Expanding Accessibility:

• Lowering Entry Barrier: The AI Assistant simplifies complex governance topics, making participation in dRep voting and discussions more accessible for the broader Cardano community.
• Multilingual Support (if applicable): Future iterations of the AI Assistant could offer multilingual support, facilitating participation from a wider global audience.
• Knowledge Dissemination: The AI Assistant can serve as a knowledge repository, providing historical data and insights on past governance decisions for the community to learn from.

Overall Impact:

By funding this proposal, you empower the Cardano community to become a true leader in AI governance. The knowledge and experience gained will not only benefit Cardano but also contribute to the responsible development and deployment of AI for decentralized systems worldwide.

[CAPABILITY & FEASIBILITY] What is your capability to deliver your project with high levels of trust and accountability? How do you intend to validate if your approach is feasible?

Photrek is a team with a proven track record in machine learning, AI development, and risk intelligence. We are in the process of successfully implementing the Project Catalyst Fund 11 proposal 1100261 Sociocratic dReps: A Representation Framework for Democratic Pluralism , which has further strengthened our expertise in decentralized governance structures and dRep processes.

Leveraging Existing Large Language Models

Our approach focuses on leveraging a pre-existing Large Language Model (LLM) and specializing it to function as an effective AI Assistant for dReps. This strategy offers several advantages:

• Reduced Development Time and Cost: By utilizing an existing LLM foundation, we can significantly reduce the development time and resources needed compared to building an LLM from scratch. This allows us to focus our efforts on customizing the model for the specific needs of dReps.
• Proven Capabilities: Existing LLMs possess a vast knowledge base and strong language processing abilities. This provides a solid foundation for building an AI Assistant that can understand complex proposals and provide relevant information to dReps.

Specialization for dReps

We will leverage our team's expertise in machine learning and AI to fine-tune the chosen LLM for the dRep domain. This specialization will involve:

• Data Curation: We will curate a comprehensive dataset specific to Cardano governance, including proposals, legal documents, community discussions, and voter sentiment data. This data will be used to train the LLM to understand the nuances of Cardano governance and dRep decision-making.
• Task-Specific Training: We will train the LLM on specific tasks relevant to dReps, such as:
• Summarizing complex proposals
• Identifying key legal considerations
• Analyzing potential ecosystem impacts
• Gauging evolving voter sentiment

Validation and Refinement

Similar to the previous approach, we will employ a data-driven and iterative development process to ensure the effectiveness of the AI Assistant:

• Internal Testing: Rigorous internal testing will identify and address technical shortcomings.
• Pilot Testing with dReps: Pilot deployments with selected dReps will gather feedback on usability and effectiveness.
• Community Feedback: We will establish open communication channels to collect feedback from the broader Cardano community throughout development.

Project Management and Delivery

Photrek utilizes established project management methodologies to ensure efficient development, clear communication, and adherence to project timelines and milestones.

Benefits of NERC Membership

Photrek’s membership in the New England Research Cloud (NERC) provides access to high-powered computing resources at significantly lower costs. This allows us to focus more resources on data curation, training, and refinement of the AI Assistant. Additionally, NERC offers collaboration opportunities with researchers from MIT, Harvard, UMASS, BU and other New England Universities.

By leveraging an existing LLM, specializing it for dReps, and utilizing a data-driven development approach, Photrek is well-positioned to deliver a valuable and effective AI Assistant that empowers dReps within the Cardano ecosystem.

[PROJECT MILESTONES] What are the key milestones you need to achieve in order to complete your project successfully?

Outline tool requirements (1 month)

Milestone output:

Create a roadmap and list of tasks and actions for the AI Agent.

Acceptance criteria:

Roadmap created detailing all the tasks and actions that the AI Agent will assume

Evidence of milestone completion:

Specifications document outlining the roadmap.

Choose LLM Model to use, collect data (1 month)

Milestone output:

• Explore existing open source AI models and evaluate and select the appropriate model for this use case. 
• Collect data that will be used to configure the agent to have the correct knowledge base.

Acceptance criteria:

• Different AI models are compared and one or more is selected
• Data relevant to dRep responsibilities 

Evidence of milestone completion:

Written document with comparison analysis of different open source AI models and which one will be used, and list of relevant data sources that will be used to configure the model.

Configure V1 of the LLM (2 months)

Milestone output:

Configure the agent’s capabilities to perform the first level of support services as designated in the roadmap.

Acceptance criteria:

AI Agent is able to successfully complete at least one task in a controlled environment.

Evidence of milestone completion:

Demo of initial prompts and outputs in video format. 

Fully Configure the LLM (2 months)

Milestone output:

Complete the configuration of the AI model to fulfill all functions as outlined in the specification document.

Acceptance criteria:

AI Agent is able to successfully complete at least 80% of the tasks in a controlled environment as laid out in the roadmap.

Evidence of milestone completion:

Full demo video showcasing AI Agent’s capabilities.

Testing and Close-out (2 month)

Milestone output:

Test the process of integrating the AI agent as a full member of our working circle framework. 

Acceptance criteria:

AI Agent is integrated into working circles (real world environment) and feedback is given on the process.

Evidence of milestone completion:

• Written report outlining the feedback from circle members on the success and usefulness of the AI agent as well as reflections on the overall process
• Video presentation

[RESOURCES] Who is in the project team and what are their roles?

This project is led by Photrek, a team with extensive experience in complex decision systems and blockchain governance. Jose Miguel De Gamboa serves as the Principal Investigator, leveraging his expertise in governance, community building, and blockchain education. Dr. Kenric Nelson and Juana Attieh provide crucial guidance as advisors on governance, technology, and strategy. The technical development is spearheaded by Igor Oliveira, an algorithm developer. Inés Gaviña collaborates on product design, communication, and content creation. Together, this team offers a well-rounded skill set to design, develop, and implement a valuable AI Assistant for the Cardano ecosystem.

Photrek Team:

Jose Miguel De Gamboa Management, Economics and HR strategic management from CESA, University of W. Sydney and Cornell University. He is an experienced professional with 25 years in the corporate world specializing in culture and catalytic leadership. He currently teaches blockchain at CESA. In the Cardano community, he serves on Intersect’s Governance Advisory board and in the Civics committee where he is currently collaborating to write Cardano's constitution first draft. He's also a founding member of the Latam Cardano Community, has contributed to Catalyst as Challenge team member/leader and Community reviewer since fund 7 and has co-authored several governance related papers. His work aims to capture collective intelligence at the service of common growth. 

https://www.linkedin.com/in/jose-miguel-de-gamboa/

Juana Attieh product lead at Photrek, and lead of Photrek’s SNET circle. Co-founder of Cardano MENA and LALKUL Stake Pool. Interim chair at the Membership and Community Committee at Intersect. Advisor at AMLOK.tech. Juana is committed to fostering decentralized governance and contributing towards optimal solutions for self-organizing systems. With her work, Juana seeks to reimagine societies, unlock untapped potential, and provide inclusive opportunities to those who need them most.

https://www.linkedin.com/in/juanaattieh/

Dr. Kenric Nelson is Founder and President of Photrek, LLC which is developing novel approaches to Complex Decision Systems, including dynamics of cryptocurrency protocols, sensor systems for machine intelligence, robust machine learning methods, and novel estimation methods. He served on the Cardano Catalyst Circle governance council and is leading a revitalization of Sociocracy for All’s work circle. Prior to launching Photrek, Nelson was a Research Professor with Boston University Electrical & Computer Engineering (2014-2019) and Sr. Principal Systems Engineer with Raytheon Company (2007-2019). He has pioneered novel approaches to measuring and fusing information. His nonlinear statistical coupling methods have been used to improve the accuracy and robustness of radar signal processing, sensor fusion, and machine learning algorithms. His education in electrical engineering includes a B.S. degree Summa Cum Laude from Tulane University, a M.S. degree from Rensselaer Polytechnic Institute, and a Ph.D. degree from Boston University. His management education includes an Executive Certificate from MIT Sloan and participation in NSF’s I-Corp. 

https://www.linkedin.com/in/kenric-nelson-ph-d-7495b77/

Technical Team:

Igor Oliveira

Igor Oliveira serves as an algorithm developer and collaborative partner at Photrek while concurrently conducting research in Socio Econophysics, quantum computing, and evolutionary dynamics at the University of pernambuco and Federal University of Pernambuco. He graduated summa cum laude with a Bachelor of Science in Materials Physics. His research explores the dynamics and intricate mathematical principles governing interacting complex systems within complex networks and collective phenomena.

https://www.linkedin.com/in/igorgibernoot/

Collaborators:

Inés Gaviña Product Ideation and Designer, Research, Lead Writer and content producer | Leading marketing and communications at Energia Social. Currently growing the SingularityNET LATAM Community. 

https://www.linkedin.com/in/in%C3%A9s-gavi%C3%B1a-57425a56/

[BUDGET & COSTS] Please provide a cost breakdown of the proposed work and resources

Total Budget: ₳ 156,000

Milestone 1: ₳ 18,000

Milestone 2: ₳ 17,000 

Milestone 3: ₳ 36,000

Milestone 4: ₳ 36,000 

Final Milestone: ₳ 49,000

Project costs are broken into the following categories as referenced in the table below:

Engineering 

• Salaries to developers and consultants

Customer Engagement 

• Compensation for community outreach work

Participants

• Incentives for dRep circle members

Computing resources

• Hosting services 
• Other computing costs

Program management

• Project reporting
• Meeting time
• Project coordination

Contingency

[VALUE FOR MONEY] How does the cost of the project represent value for money for the Cardano ecosystem?

The cost of this project represents exceptional value for the Cardano ecosystem by delivering a powerful AI Assistant that streamlines governance processes, empowers dReps, and fosters informed decision-making. Here's a breakdown of the cost-benefit relationship:

• Reduced Decision-Making Costs: The AI Assistant minimizes the time dReps spend analyzing proposals, leading to faster and potentially more cost-effective decision-making within the governance system.
• Improved Proposal Quality: By providing comprehensive analysis and highlighting potential issues, the AI Assistant can contribute to higher quality proposals being implemented, leading to long-term cost savings for the Cardano ecosystem.
• Enhanced Voter Confidence: Transparent and data-driven governance processes supported by the AI Assistant bolster voter confidence, potentially increasing voter participation, a crucial aspect of a healthy decentralized system.
• Reduced Risk of Errors: The AI Assistant's ability to identify potential problems and ensure proposals align with the Cardano constitution minimizes the risk of costly governance mistakes.
• Scalability and Future Benefits: The knowledge and expertise gained through this project lay the foundation for future iterations of the AI Assistant, potentially extending its functionalities and value proposition within the Cardano ecosystem.
• Cost-Effectiveness: Our focus on leveraging a pre-existing LLM significantly reduces development costs compared to building one from scratch. Furthermore, by utilizing resources like NERC's high-powered computing infrastructure, we optimize resource allocation.
• Long-Term Investment: Funding this project represents an investment in Cardano's future. The developed AI Assistant will empower dReps, strengthen governance, and position Cardano as a leader in responsible AI integration within decentralized systems. The knowledge gained can benefit not only Cardano but also contribute to the broader development of AI for positive impact within other decentralized communities.

By considering the cost savings, improved decision-making, and long-term benefits for the Cardano ecosystem, the proposed project provides exceptional value for the requested budget.

Towards that end, Photrek utilizes competitive pricing methods that provide the highest value to our customers and support our team members with fulfilling lives. Our rates are based on self-employment in the US & Canada. The rates take into account the employment overheads of the resources contracted. The amounts are calculated for each milestone based on the hours to complete. For example the chart for engineering and scientific salaries in the Commonwealth of Massachusetts is provided here: https://www.mass.gov/guides/salary-and-compensation.