Artificial
intelligence (AI) has the potential to help tackle some of the world’s most
challenging social problems. To analyze potential applications for social good,
we compiled a library of about 160 AI social-impact use cases. They suggest
that existing capabilities could contribute to tackling cases across all 17 of
the UN’s sustainable-development goals, potentially helping hundreds of
millions of people in both advanced and emerging countries.
Real-life
examples of AI are already being applied in about one-third of these use cases,
albeit in relatively small tests. They range from diagnosing cancer to helping
blind people navigate their surroundings, identifying victims of online sexual
exploitation, and aiding disaster-relief efforts (such as the flooding that
followed Hurricane Harvey in 2017). AI is only part of a much broader tool kit
of measures that can be used to tackle societal issues, however. For now,
issues such as data accessibility and shortages of AI talent constrain its
application for social good.
This
article is a condensed version of our discussion paper, Notes from the AI
frontier: Applying AI for social good (PDF–3MB). It looks at domains of social
good where AI could be applied, and the most pertinent types of AI
capabilities, as well as the bottlenecks and risks that must be overcome and
mitigated if AI is to scale up and realize its full potential for social
impact. The article is divided into five sections:
1) Mapping
AI use cases to domains of social good
2) AI
capabilities that can be used for social good
3) Overcoming
bottlenecks, especially around data and talent
4) Risks to
be managed
5) Scaling
up the use of AI for social good
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