This document outlines the requirements for a web application designed to assist underserved voters, particularly residents of Detroit, by providing personalized civic information. The application aims to bridge the information gap faced by these voters, enhancing their engagement in the democratic process. By leveraging a human-in-the-loop AI system, the platform will offer tailored voting information, enabling users to navigate civic issues effectively. The project will be funded through government sources, ensuring sustainability while maintaining high standards of compliance, security, and user trust. The Minimum Viable Product (MVP) will focus on a demo use case that showcases the application’s core functionality, emphasizing user feedback and iterative improvement. Success will be measured through user engagement metrics and the accuracy of AI-generated summaries.

The problem of underserved voters is particularly pronounced in urban settings like Detroit, where residents often lack access to personalized and relevant civic information. Many potential voters are unaware of their rights, upcoming elections, and the positions of candidates on issues that directly affect their communities. This lack of information contributes to lower voter turnout and civic engagement. The proposed web application addresses this gap by providing tailored voting information that meets the unique needs of Detroit residents. This solution is not only timely but essential in fostering a more informed electorate. The targeted approach to deliver personalized information based on user demographics and interactions ensures that the platform is aligned with the specific challenges faced by these communities, ultimately contributing to a more equitable democratic process.

The primary users of the application are Detroit residents, particularly those who belong to underserved demographics, including low-income households and individuals with disabilities. User personas will be developed to capture the diverse needs and preferences of these residents. Core use cases include accessing personalized voting information, which allows users to understand their voting rights and upcoming election details based on their specific ZIP code. Additionally, city staff will utilize a content management system to curate and manage civic information, ensuring that it remains relevant and up-to-date. Auditors will review data integrity and sources to maintain trust in the information provided. The application will also facilitate user feedback, allowing for continuous improvement of the AI recommendations, thereby enhancing the user experience and engagement.

The functional requirements for the web application encompass a range of features designed to provide personalized civic information effectively. Key features include personalized voting information tailored to user demographics, enabling residents to receive relevant updates based on their specific needs. Integration with third-party data sources will provide real-time information from government databases, enhancing the accuracy and relevance of the content delivered. The human-in-the-loop feedback mechanism will allow users to contribute their insights, refining AI-generated summaries for improved accuracy. A robust content management system will facilitate easy updates, while a user dashboard will serve as the central hub for accessing personalized information and resources. The application will also implement intuitive navigation and accessibility features to ensure a seamless user experience across all devices.

The AI and intelligence architecture of the web application will focus on enhancing user engagement through personalized issue summaries and candidate position classification. Utilizing advanced machine learning models, the application will generate tailored summaries of civic issues based on user-selected topics and demographic data. The goal is to achieve a minimum accuracy of 90% in matching summaries to user interests. Additionally, the system will classify candidates' positions on selected civic issues with at least 85% precision, providing clear insights to users. A feedback loop system will continuously refine AI-generated summaries based on user interactions, targeting a 20% improvement in accuracy within three months post-launch. The architecture will also incorporate data integrity monitoring and provenance tracking to ensure transparency and build user trust.

Non-functional requirements are critical for ensuring the web application's reliability, security, and overall user experience. High availability and reliability are paramount, as the application will be publicly accessible and must support a diverse user base. Fast response times are essential for user queries to maintain engagement and satisfaction. Data security measures, including encryption of user data, will be implemented to safeguard privacy and comply with relevant regulations. The application will adhere to performance metrics that ensure quick loading times and responsiveness, especially on mobile devices. Additionally, accessibility features will be integrated to comply with WCAG 2.1 AA standards, ensuring that all users, including those with disabilities, can access the information seamlessly.

The technical architecture of the web application will leverage a cloud-based infrastructure to ensure scalability and reliability. This infrastructure will support the integration of mocked data APIs for the demo, allowing for a realistic simulation of the application’s capabilities. The data model will be designed to accommodate user profiles, including demographic information, preferences, and interaction history, enabling personalized content delivery. The architecture will also include a model training pipeline for automating the training of recommendation models, ensuring that the system continuously learns and improves. Continuous integration practices will be employed to facilitate automatic testing and deployment, enhancing the development workflow. Performance monitoring tools will be integrated to track application performance in real-time, ensuring that any issues can be promptly addressed.

Security and compliance are critical components of the web application’s design, particularly given the sensitivity of user data involved. The application will comply with NIST and SOC 2 Type II standards to ensure robust security practices. Data encryption will be implemented to protect user information from unauthorized access, and a comprehensive privacy policy will be established to adhere to relevant regulations regarding user data privacy. The application will also incorporate mechanisms for user trust, including transparency in data sourcing and integrity monitoring. Regular audits will be conducted to ensure compliance with established security protocols and to identify any potential vulnerabilities. This proactive approach to security and compliance will be essential in fostering user trust and maintaining the integrity of the application.

To gauge the effectiveness and impact of the web application, a set of success metrics and key performance indicators (KPIs) will be established. User engagement rates among underserved residents will be a primary metric, measuring the extent to which users interact with the application and utilize the personalized information provided. The accuracy of AI-generated summaries post-human review will also be tracked, aiming for a minimum accuracy threshold that reflects the quality of the information presented. User trust will be assessed through feedback and audit logs, providing insights into user satisfaction and perceived reliability of the content. Additional metrics will include click-through rates on recommended civic engagement activities, with a target of achieving a 60% click-through rate, as well as user satisfaction rates regarding content relevance, aiming for a 70% satisfaction rate in follow-up surveys.

The roadmap for the web application outlines a phased delivery approach, starting with the development of the MVP focused on a demo use case. Initial phases will prioritize the implementation of core features such as personalized voting information and third-party data integration. Subsequent phases will expand on the human-in-the-loop feedback system and enhance the content management capabilities for city staff. The roadmap will also include plans for user testing and iterative feedback loops to continuously refine the application based on user needs. As the project progresses, additional features such as dynamic content adaptation and legislative action forecasting will be introduced. This phased approach will ensure that the application evolves in alignment with user expectations and community needs, ultimately fostering greater civic engagement among Detroit residents.

Implementation guide for 13 selected Claude-compatible skills/tools: MCP Slack Server, MCP PostgreSQL Server, MCP Browser Automation, MCP Google Drive Server, MCP Docker Server, Web Search, Data Analytics & Reporting, Multi-Channel Notification Hub, Content Generation Engine, Encryption & Data Protection Toolkit and 3 more. Covers installation, configuration, and usage patterns.