To follow its mission to allow anyone, anywhere, to benefit from the possibilities that AI can provide, the organization is focused on delivering on its mission via collaborative initiatives in three directions: Connect and Collaborate, Build and provide shared resources, and Scale for impact.
AI Commons Repository is a common repository of trained ML/AI models along with their training data sets that have been used for AI For Good solutions to serve as a resource for all communities of practice to advance applications of ML/AI techniques for AI For Good purposes.
Connecting problem owners to problem solvers is important to identify how real challenges on the ground that can be addressed using AI. Living and learning labs around the world acting as AI community hubs help matching problems solvers with problem owners, identify data sources and help build solutions that can be immediately used locally. Here are some of the active AI Community Hubs
In this challenge, participants develop an algorithm that can generate a character profile when provided the name of a prominent female in history, science, technology, or culture including folklore and myth. The result of the challenge is contributed to AI Commons to be used globally and incentivize for more diverse and women focused inspiration on innovation.
The Global Data Commons (GDC) aims at proposing models to support the creation of data commons on a global basis, and providing mechanisms for rules-based access to data and help leveraging the revolution in advanced analytics and Artificial Intelligence to support the achievement of the UN Sustainable Development Goals (SDGs).
To help all problem solvers work on real cases with problem owners, model AI sandbox are open “Safe environments” to be used for collaboration and solution evaluation. These sandboxes incorporate AI/ML algorithms, training data sets, and cloud and compute resources, and help anyone to start evaluating real life solution evaluation.
ImpactNet is an AI for Impact benchmark database. This initiative will produce model datasets and model AI solutions. Datasets will allow more researchers to use their models on new areas that will have an impact on helping achieve AI for Good. AI solutions will allow problem solvers to adopt validated AI for good solutions to scale those solutions in areas of SDGs to accelerate impact.