New Commons Challenge 2025 | Win $100,000


Are you a young changemaker looking for an opportunity to address critical issues on any international platform? If yes then the application are open for the New Commons Challenge 2025 for Global Changemakers. This international challenge is an initiative taken by the Open Data Policy Lab, which is a collaboration between Microsoft and The GovLab. It is supported by its partners, DirectRelief/CrisisReady, the Harvard Institutional Data Initiative, and UNESCO. Individuals from across all backgrounds and fields are eligible to apply for this international challenge.

The New Commons Challenge 2025 is open to nonprofit organizations, start-ups, academic institutions, and development organizations. Applicant must be affiliated with any established organization. The international challenge addresses different critical issues, such as limited access to diverse and high-quality datasets, which is important for AI to reach its full potential. Data commons are collaboratively governed data ecosystems that provide responsible access to diverse, high-quality datasets, through which the gap in AI development can be filled.

The New Commons challenge looks to create new data commons to make sure that AI benefits everyone; it focuses on priority areas such as Strengthen Disaster Response and Enabling Localized Decision-Making. The objectives of this international competition are reimagining the ways to expand responsible access to diverse datasets, including new and existing data sources, demonstrate how data commons can be utilized, managed, and maintained, and show real-world impact by creating tangible benefits for end users. All work conducted must be for the public benefit. This paid competition will select 2 winners and will provide them with a prize of $100,000 each. This is an amazing mentorship opportunity, so don’t skip this article and read it till the end to get more details.

More Details About the New Commons Challenge 2025:

Priority Areas:

  • Strengthen Disaster Response
  • Enabling Localized Decision-Making





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