Advancing AI Research to Help Policymakers Affordably Improve Life’s Starts and Finishes
Understanding grows about childhood experiences occurring primarily in lower and middle class homes that limit fulfillment of children’s’ developmental potential. Simultaneously nations and US state governors face rising demand for costly institutional care that many seniors’ dread. In the United States, the cost of long-term care would more than double from 1.3% of US GDP in 2010 to 3% of US GDP in 2050 if the rate of functional limitations among those age 65 and older remains constant (Congressional Budget Office, 2013). These two trends confront policy-makers with painful fiscal trade-offs. The prior watershed decade was the first in which Medicaid funding demands fueled by institutional spending for seniors’ care exceeded state funds available to fund children’s’ education. Rapid advances in the capability and affordability of in-home AI systems may enable policymakers to more affordably and effectively serve these two vulnerable populations during life’s starts and finishes. Effective, scalable uses of prior generations of cyber systems have improved value-for-money in other service sectors such as airlines and banking. However, use of modern AI capabilities to improve the value of more intimate interpersonal human services is fraught with hope and fear for seniors, families, health professionals, educators and policymakers seeking to serve them cost-effectively. Both emotions are well-founded. Stanford faculty, fellows, and students from its schools of engineering and medicine seek to formulate and test psychologically nuanced applications of AI in order to increase policy-makers' and industry's understanding of how modern AI systems can more affordably and effectively (1) enable care planners to select in-home care plans that will generate the largest gains in seniors’ self-care capabilities; and (2) boost non- affluent parents’ contribution to the physical, mental and social development of children.
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