Initiatives

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.

Connect

Connecting problem owners and problem solvers is at the core of creating communities that work together towards sustainable solutions and share in a trusted and safe way their mutual knowledge. Our initial and first effort is to collectively work towards making the knowledge and approaches to problem solving with AI benefit anyone -and especially those who need it the most.

AI Repository

Program
Shared Resources
Year
2020

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.

Members:
Alexandre Cadain
Director of Development
Anna Bethke
AI for Good Projects
Maria Axente
Director of Outreach
Julien Cornebise
Director of Research
Ramesh Raskar
MIT Media Labs
Alpesh Shah
IEEE Standards
Uyi Stewart
Executive Director
Tara Chklovski
Technovation
Partners:
XPrize, District 3, ITU, Mila, Sahara Ventures, Fondation Botnar,

AI Community Hubs

Program
Community
Year
2019

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

Members:
Ramesh Raskar
MIT Media Labs
Xavier Herve
Concordia University
Myriam Côté
University of Montreal
Gilles Fayad
Director of Development
Kenny Chen
Partnership to Advance Responsible Technology (PART)
Sydney Swaine-Simon
Concordia University
Mathilde Forslund
Director of Development
Jumanne Rajabu
Sahara Ventures
Uyi Stewart
Executive Director
Eric Espinosa
Cities and Community Impact
Tara Chklovski
Technovation
Partners:
District 3, Sahara Ventures, PWC, Swissnex, Fondation Botnar, The Future Society,

Build

A commons become a reality when shared resources are made available and rules of access defined, along with governance to manage those rules. At minimum, having access to tools and expertise as well as computing and data resources in an open environment will allow for a democratized opportunity to allow participation by anyone.

Storytelling Challenges

Program
Shared Resources, Challenges
Year
2019

Dataset Challenge

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.​

Members:
Davar Ardalan
IVOW
Nishan Chelvachandran
Aprajita Mathur
Partners:
Ivow AI, IACrowd, ANIMA,

Global Data Commons

Program
Shared Resources
Year
2019

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).

Members:
Alexandre Cadain
Director of Development
Cyrus Hodes
Data Initiatives
Nicolas Miailhe
AI Governance
Julien Cornebise
Director of Research
Alpesh Shah
IEEE Standards
Yolanda Lannquist
Data and AI Governance
Dana Griffin
Partners:
XPrize, Ocean Protocol, ITU, The Future Society, IEEE Standards,

AI Collaboration Sandbox

Program
Community
Year
2019

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.

Members:
Amir Banifatemi
Sean McGregor
Research and Technology Lead
Anna Bethke
AI for Good Projects
Julien Cornebise
Director of Research
Alpesh Shah
IEEE Standards
Uyi Stewart
Executive Director
Nishan Chelvachandran
Tara Chklovski
Technovation
Yale Fox
Partners:
ITU, Mila, PWC, Pontifical Academia, CHAI, IEEE Standards,

Scale

Finally, to help scale AI solutions, a standardized framework for problem scoping and readiness for scaling will facilitate funding and support by both investment groups and governments locally.

ImpactNet

Program
Shared Resources, Scaling AI
Year
2020

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.

Members:
Amir Banifatemi
Sean McGregor
Research and Technology Lead
Hamed Alemohammad
Data Science and ML for Earth Observation
Trent McConaghy
Technology and project lead
Laure Delisle
Research and project lead
Tara Chklovski
Technovation
Partners:
XPrize, Ocean Protocol, Mila, Radiant Earth Foundation, Fondation Botnar, Pontifical Academia, CHAI, IEEE Standards,