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Funding Data and AI That Serve the Social Sector
Five ways for funders to think about investing in data and AI that would put ownership of responsible data and AI squarely in the hands of the social sector.
Five ways for funders to think about investing in data and AI that would put ownership of responsible data and AI squarely in the hands of the social sector.
Philanthropy focused on place helps leverage resources and empower communities. SSIR publisher Michael Voss speaks with Gina D. Dalma of the Silicon Valley Community Foundation, Peggy Davis of the Chicago Community Trust, and Chris Boyce of Schwab Charitable about what a place-based approach to philanthropy looks like. A sponsored podcast developed with the support of DAFgiving360.
In the last two years, this five-cylinder engine has propelled funders to break through historic barriers to change.
To cure the social sector’s metric monomania, we must get comfortable with complexity.
To do as much good as possible with limited resources, funders should look to woefully underfunded protest movements.
Funders are calling for more program evaluation, but nonprofits are often collecting dubious data, at great cost to themselves and ultimately to the people they serve.
Large-scale social change requires broad cross-sector coordination, not the isolated intervention of individual organizations.
For NGOs, impact comes in different forms and to track the cycles of social change work, we must think across the tangibility and the speed of emergence of change.
With an understanding of these 10 funding models, nonprofit leaders can use the for-profit world's valuable practice of engaging in succinct and clear conversations about long-term financial strategy.
Fair Trade-certified coffee is growing in sales, but strict certification requirements are resulting in uneven economic advantages for coffee growers and lower quality coffee for consumers.