Since its founding in 2007, Project for Awesome has become a pillar of collective action, mobilizing large numbers of donors to address global poverty and support an array of charities. Led by popular online brothers John and Hank Green, the initiative combines online participation, transparent governance and community voting to allocate funds to various charities and nonprofits. Project for Awesome has become a key example of how participatory fundraising models can strengthen trust in nonprofits, generate measurable outcomes and engage new generations of donors.

Collective Action Explained

Global poverty is one of the most persistent challenges and one that nonprofits and charities often target directly and indirectly. Traditional donation models often rely on large institutional donors and centralized decision-making, which can limit public engagement and transparency about where donors’ money is going. Collective models, by contrast, emphasize shared responsibility, participation and trust. Project for Awesome, headed by YouTubers and authors John and Hank Green, follows this model. Through community voting and digital engagement, Project for Awesome has changed the charity landscape and shown how collective giving can produce significant and measurable impacts.

The Structure of Project for Awesome

Project for Awesome is a branch of the larger nonprofit Foundation to Decrease World Suck. Project for Awesome works as follows: each year, participants submit videos nominating nonprofits and community members vote to determine how and where funds are allocated.

This allows viewers to learn about various charities and vote for those that resonate with them and the causes they want to support worldwide. Donations can also earn supporters perks such as keepsakes and exclusive podcast episodes or content from John or Hank Green. Each year, Project for Awesome holds a livestream to help determine which charities receive donations. This event is central to its fundraising efforts and, due to John and Hank Green’s online reach, is often a large success.

In 2025, Project for Awesome recorded 169,384 votes and raised $3,739,917.69 in total donations. According to reports, 50% of the 2025 funds went to Save the Children and Partners in Health, and the remaining 50% was split among charities chosen by the Project for Awesome community.

Project for Awesome Reduces Global Poverty

Independent media coverage reinforces the credibility and impact of Project for Awesome. Reporting by Good Good Good confirmed that the 2025 event raised more than $3.7 million in a single weekend, making it the largest fundraising total in the project’s history.

The article further noted that all funds directed to Partners in Health in 2025 supported tuberculosis treatment and prevention efforts, a disease closely linked to poverty and inadequate health care infrastructure. Save the Children similarly used funds to provide humanitarian aid, nutrition support and emergency relief in crisis-affected regions. These outcomes demonstrate that collective giving is not merely symbolic. It translates directly into services, medical treatment and material support for vulnerable populations.

Looking Ahead

Project for Awesome illustrates how collective giving can function as an effective tool for addressing global poverty. By combining digital participation, community voting and transparent allocation of funds, John and Hank Green and Project for Awesome reduces poverty by mobilizing hundreds of thousands of donors and directing millions of dollars to poverty-focused interventions. The 2025 results demonstrate that participatory fundraising models can strengthen trust in nonprofits, support global and local anti-poverty efforts and engage new generations in sustained philanthropy. By framing poverty alleviation as a shared responsibility, collective giving offers nongovernmental organizations (NGOs) a proven and scalable model for impact.

– Mollie Skogen

Mollie is based in London, UK and focuses on Celebs and Politics for The Borgen Project.

Photo: Flickr