Underserved communities: Leveraging AI to improve health and social services in low-resource areas – ImpactAlpha (registration)

Jessica Pothering

Jessica is a business and finance writer, focusing on impact investing, social entrepreneurship and economic development. She previously reported for financial publications covering the global private equity, real estate and insurance markets.

AI see, AI do.

Among the risks in using data-driven AI in low-resource or at-risk communities is that the algorithms will magnify systemic biases.

Care must be taken to prevent AI systems from reproducing discriminatory behavior, such as machine learning that identifies people through illegal racial indicators, write researchers from the Stanford One Hundred Study on Artificial Intelligence.

This week, ImpactAlpha is extracting nuggets from Stanfords century-long effort to understand AIs long-term possibilities and dangers. Theres already an update to yesterdays #2030 segment on self-driving cars: Ford recently announced a $1 billion investment in software for autonomous fleets.

The researchers found AI could be a money-saving lifeline for budget-strapped local and state governments.

Illinois Department of Human Services, for example, is using predictive data modelling to improve prenatal care to high-risk pregnant women.

Cincinnati is using AI to identify and inspect properties that arent up to code.

AI also has potential for developing low-cost community health campaigns, which are otherwise difficult to target and expensive to implement.

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Photo credit: Scienceofsingularity.com

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Underserved communities: Leveraging AI to improve health and social services in low-resource areas - ImpactAlpha (registration)