Meeting Overview

• Date: January 23, 2025
• Attendees: All Teams, Client
• Purpose: Establish the foundation of the project.

Goals

• Team introduction to the client.
• Review team’s knowledge of project current state.
• Gather feedback from the client on requirements.

Action Items

Kickoff Action Items

Notes

Key Discussion Points:

1. Project Overview and Introductions:
   • Brinley Murphy Reuter outlined the mission of Science to People, emphasizing accessibility, understanding, and cultural relevance.
   • Team introductions included Gelon (Lead PM), Spencer and Egona (PM Apprentices), Amir (Strategy Co-lead), and Kata and Chen Yi introduce themselves as Apprentices in Product Strategy.
   • Yelena, Danni, Sydney, Yihyoungli, Sampada, and Rachel introduce themselves as Co-Leads and Apprentices in the Design team.
   • Phillip and Oana introduced themselves as UXR Co-Leads for the Research team along with Tommy, one of their Apprentices.
2. Project Goals and Success Criteria:
   • Objectives: Refining the MVP, leveraging UX research, and developing scalable frameworks.
   • Success Metrics:
     • 20% creator adoption during beta.
     • 15% misinformation reduction.
     • Onboarding underserved creators and ensuring scalability with client validation.
3. Project Plan and Timeline:
   • Week 1–2: Initiation (project charter, team charter, risk plan).
   • Week 3–4: Research & Plan (research reports, personas, journey maps).
   • Week 5–7: Design & Prototype (wireframes, prototypes, usability reports).
   • Week 8–10: Development (final design assets, MVP backlog).
   • Week 11: Handoff.
4. Roles and Responsibilities:
   • PM team: Collaboration, resolving roadblocks, agile coaching.
   • Product strategy: Aligning with Science to People goals, prioritizing requirements.
   • UX/UI and research teams: Prototyping, usability testing, and end-user feedback.
5. Tools and Communication Plan:
   • Tools: Notion, Figma, Google Drive, Discord.
   • Communication: Email for formal communication, Discord for quick updates, Google Meet for meetings.
6. Risk Analysis and Mitigation:
   • Risks include misinformation, low adoption, user learning curves, and legal concerns.
   • Mitigation strategies: Verification systems, multilingual localization, user-friendly tutorials, and rigorous content validation.
7. Client Feedback:
   • Brinley Murphy-Reuter:
     • Emphasized the importance of integrating cultural relevance into all deliverables to align with their mission.
     • Reiterated the need for tools and prototypes to be accessible especially for underserved creators.
     • The team is also exploring a multi-agent chatbot system to provide expertise in different areas of health.
   • Pablo Flores:
     • Highlighted the importance of data-driven insights from pilot programs to inform scalability.
     • Requested a detailed roadmap for integrating feedback loops into content creation workflows.
   • Rajeshwari:
     • Raje shares the results of the initial survey indicating high excitement and time savings for creators.
     • Shared enthusiasm for the AI-powered platform’s potential in reducing misinformation but emphasized simplifying the user experience for non-technical audiences.
8. Questions and Answers (Detailed):
   • Amir's Question:
     • What data is available on the current Play Lab prototype for user interactions and survey results?
       • Response (Brinley): User interaction metrics and survey data are available. She offered to provide back-end access for a deeper analysis.
         • The total addressable market is estimated to be around 20,000 health-specific creators and 50 to 70 enterprise clients.
   • Yelena's Question:
     • What design decisions were made for MVP2 based on user research?
       • Response (Brinley): MVP2 was shaped by feedback from initial prototypes, which revealed creators’ preferences for simplified workflows and audience engagement features.
         • Key insights led to the prioritization of simplified workflows to improve usability and audience engagement.
         • The platform’s features were tailored to address common pain points, such as the need for streamlined content creation, robust fact-checking tools, and evidence-based recommendations.
         • This user-centered approach ensured the design aligns with the creators’ expectations for an intuitive and impactful tool.
   • Amir's Follow-Up:
     • How does the system integrate user feedback for continuous improvement?
       • Response (Pablo): The system uses a feedback ecosystem where users can provide real-time suggestions, shaping future iterations of modules for content creation.
   • Yelena's Second Question:
     • What is the validation process for the product's relevance in the content creation sector?
       • Response (Brinley): Initial research from Harvard and direct feedback from creators confirmed the platform's value, citing significant time savings and increased audience reach.
   • Amir's Final Question:
     • Are there plans for third-party integrations to enhance scalability and reliability?
       • Response (Pablo): Current integration includes Semantic Scholar, with future plans to expand partnerships with organizations like the National Academies of Science and Story MD.
   • Rajeshwari's Question:
     • How will the platform address linguistic and cultural barriers in a global rollout?
       • Response (Brinley): Multilingual support and cultural adaptation are high priorities, and the platform’s framework is designed to integrate localization easily.
   • Phillip’s Question:
     • Can you walk me through your vision for Verizon's feedback ecosystem from how low location specific health guidelines are handled to how user feedback shapes the system?
       • Response (Pablo): Pablo explained the vision for VeriSci's feedback ecosystem, emphasizing its role in handling location-specific health guidelines and incorporating user feedback.
         • He mentioned that in the current Play Lab prototype, users can flag content as inappropriate, not factual, or another predefined category.
         • This feedback informs content validation and refinement processes. For the ecosystem’s development, the approach aligns with what is outlined in their Figma product design, focusing on empowering creators to generate accurate content.
         • The system analyzes elements like tone and factual accuracy, providing creators with actionable insights to enhance their content. Pablo noted that Brinley could elaborate further on this process.
       • Response (Brinleigh): Outlined the four core pathways envisioned for VeriSci’s feedback ecosystem:
       1. Content Creation: Helping users develop content from an initial idea, ensuring it aligns with evidence-based practices.
       2. Script Refinement: Assisting creators in enhancing existing scripts by adding evidence, citations, and references to improve credibility.
       3. Visual Content Creation: Offering tools akin to Canva, enabling users to create charts, graphs, infographics, and branded templates for social media or other communication channels.
       4. Fact-Checking: Allowing users to verify external content from the internet and providing recommendations for corrections or responses.
   • Phillip’s Question: