Can Machine Learning Double Your Social Impact?
A look at what it takes to successfully deploy machine learning tools for social good and the most exciting opportunities ahead.
A look at what it takes to successfully deploy machine learning tools for social good and the most exciting opportunities ahead.
Five insights about social mobility and the role of big bet philanthropy.
Without bringing more rigor and resources to scaling impact efforts, the do-good industry will never make the exponential leaps needed to bring social innovations to millions of people.
Philanthropy is poised for a grand transformation, but it will require a lot of investment, capacity building, and experimentation to get it right.
The former chief innovation officer at USAID outlines a way for social sector organizations and funders to build innovation into their DNA.
Since 1970, more than 200,000 nonprofits have opened in the U.S., but only 144 have reached $50 million in annual revenue. They got big by doing two things: They raised the bulk of their money from a single type of funder. And just as importantly, these nonprofits created professional organizations that were tailored to the needs of their primary funding sources.
A decade of applying the collective impact approach to address social problems has taught us that equity is central to the work.
How do innovations move from the edges to the core of what an organization does? For maximum impact, innovations must cease to be innovative and become institutionalized and normalized.
Impact evaluations are an important tool for learning about effective solutions to social problems, but they are a good investment only in the right circumstances.
Scaling requires not only fidelity to core processes and programs, but also constant adjustments to local needs and resources.