Teams must demonstrate the following in their pitches:
Convincing framing of problem (20%)
Teams need to demonstrate that the problem is specific and well-defined, with evidence or research supporting its importance.
- Is the specific social issue and pain point clearly defined?
- What evidence or research demonstrates this problem’s significance and scope?
- Who are the stakeholders affected by this problem, and how?
- What existing solutions have been attempted and why have they been ineffective?
- Does the project address the root causes rather than just symptoms?
- Why does this problem deserve attention now?
Prototype/ demo (20%)
Team must demonstrate a functional prototype or demo illustrating the proposed solution in action.
- Does the demo effectively showcase the solution’s core functionality?
- How complete is the prototype (what works vs. what’s simulated)?
- Can the prototype handle realistic test cases?
- How intuitive is the user interface/experience?
- Has the prototype been tested with potential users?
Appropriate technical component (20%)
Teams must show that GenAI technology is effectively and appropriately used for the problem.
- How specifically does the solution leverage GenAI capabilities?
- Why is GenAI particularly suited for addressing this problem?
- Which specific GenAI models or techniques are being implemented?
- How does this approach improve upon non-AI alternatives?
- What technical limitations exist, and how have they been addressed?
- How efficiently does the implementation use computational resources?
Feasibility and impact (20%)
Teams must convincing argue that the solution is realistic to implement and likely to make a meaningful social impact.
- What is the business model or pla
- Is the solution practically implementable given real-world constraints?
- How will target users access and adopt the solution?
- What metrics will measure impact?
- What is the potential scale of impact (number of beneficiaries)?
- What implementation challenges are anticipated?
- Has the team developed a realistic timeline for deployment?
Sustainability and ethics (20%)
Teams must show the solution is designed for long-term sustainability and state its ethical implications.
- Does the business model or plan support this solution long-term.
- Is the solution scalable, adaptable, or has potential for integration with existing systems or processes
- How will this project be financially sustained?
- What potential ethical concerns (e.g. bias, privacy, and accessibility, unintended consequences) exist with this GenAI implementation?
- How has feedback from affected communities been incorporated?
- Does the solution empower users rather than creating dependencies?