Philanthropy as Risk Capital: Shaping Trust and Learning at the Speed of AI

As artificial intelligence rapidly reshapes society, philanthropy is increasingly called to act as "risk capital" for the public good. But risk alone is not enough. Without rigorous, field-wide learning, philanthropy's bold bets may remain isolated and short-sighted, failing to catalyze the systemic change this moment demands. This article draws on three sources of learning at Omidyar Network—an evaluation of The Tech We Want initiative, external strategy consultations with 29 stakeholders, and early learnings from a generative AI portfolio—to identify how philanthropy can uniquely "de-risk" AI innovation for collective benefit. Through trust-based partnerships, ecosystem infrastructure support, and narrative change, these learning opportunities revealed that philanthropy must show up beyond funding, signaling what works, sharing lessons openly, and creating enabling conditions for others to act. This article identifies four critical insights for how philanthropy can use learning to unlock collaboration, shift public narratives, and equip the field to act with both urgency and wisdom in shaping AI's trajectory toward shared power, prosperity, and possibility.

Authors

Publication Details

Journal
The Foundation Review
Published
2025-12-01
DOI
https://doi.org/10.9707/1944-5660.1770
Primary Topic
Innovation, Sustainability, Human-Machine Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Philanthropy as Risk Capital: Shaping Trust and Learning at the Speed of AI

Clara Bennett, Nina Sabarre, Laura Chavez-Varela
The Foundation Review
Innovation, Sustainability, Human-Machine Systems
article

Philanthropy as Risk Capital: Shaping Trust and Learning at the Speed of AI

Clara Bennett, Nina Sabarre, Laura Chavez-Varela
article en

Abstract

As artificial intelligence rapidly reshapes society, philanthropy is increasingly called to act as "risk capital" for the public good. But risk alone is not enough. Without rigorous, field-wide learning, philanthropy's bold bets may remain isolated and short-sighted, failing to catalyze the systemic change this moment demands. This article draws on three sources of learning at Omidyar Network—an evaluation of The Tech We Want initiative, external strategy consultations with 29 stakeholders, and early learnings from a generative AI portfolio—to identify how philanthropy can uniquely "de-risk" AI innovation for collective benefit. Through trust-based partnerships, ecosystem infrastructure support, and narrative change, these learning opportunities revealed that philanthropy must show up beyond funding, signaling what works, sharing lessons openly, and creating enabling conditions for others to act. This article identifies four critical insights for how philanthropy can use learning to unlock collaboration, shift public narratives, and equip the field to act with both urgency and wisdom in shaping AI's trajectory toward shared power, prosperity, and possibility.

The Foundation ReviewVol. 17(3)
Partnerships for the goals
Openalex Percentile: Top 16%
Innovation, Sustainability, Human-Machine Systems
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