Last updated 4 years ago
We're relying on humans to critique an ever growing set of proposals; how can AI provide higher quality feedback and improve results
This is the total amount allocated to AI Proposal Evaluation and Guidance.
Me: AI & Data Strategy Consultant @ Big 4 firm; 12 years experience building systems
1x Support: has AI & data strategy experience
goal: increase review throughput and quality to increase value of ideas generated and funded
proposed solution: AI trained to provide critique and recommendations to proposals,
Critique Ideas:
- completeness
- relevancy to topic
- similarity to other proposals
- complexity of implementation vs funding request
- likelihood of success
- degree of alignment to Cardano mission and values
Recommendation Ideas
- feedback received from similar successful / unsuccessful ideas (can serve as Catalyst's "memory")
- partnering opportunities with other proposals
- solution design from either relevant templates, samples or successful projects
- team members with relevant background
- tldr summary
Current Complications:
Current data collection does not support the breadth of valuable critiques and and recommendations that could be automated.
Why Now:
Proposed Deliverables For F4
- vision for proposal critique and recommendations engine
- high level data requirements
- inventory of project data available on IdeaScale and other Catalyst project related data sources
- gap analysis between data requirements and data currently available
- socialization discussions with IOG and SingularityNet teams (pending availability)
- capability roadmap for Catalyst proposal critique and review system
- Recommended initiatives
Support Needed
- coming soon
10000Me: AI & Data Strategy Consultant @ Big 4 firm; 12 years experience building systems
1x Support: has AI & data strategy experience