Chan, S. W. T., Liu, A. R., Ostrowski, A. K., Vaidya, M., Brady, S., Yoquinto, L., D’Ambrosio, L., Zulfikar, W., Maniar, N., Patskanick, T., Leong, J., Kosmyna, N., Coughlin, J., & Maes, P. (2024). Co-designing Generative AI Technologies with Older Adults to Support Daily Tasks. An MIT Exploration of Generative AI. https://doi.org/10.21428/e4baedd9.4f2a95fc

Abstract

The increase in life expectancy worldwide is a global success story, but along with reduced birth rates, it has resulted in a growing population of older adults and relatively fewer young adults available to provide care. Over 10% of the world’s population is over 65; by 2050, that number is expected to reach 16%. Many countries will experience a more extreme level of population aging. By 2050, the 65-plus cohort is projected to account for 35–40 percent of the populations of several industrialized countries. Countries experiencing a transition to such population structures face significant economic and social effects including potential shortages in key workforce roles driven by the retirement of older workers and increased demand for certain service categories such as professional and informal care providers and age-relevant medical services.

Many older adults prefer to live independently, hoping to stay in their own homes for as long as it is practical, but this can be made difficult and require more support due to physical and cognitive decline. While the prevalence of cognitive conditions such as dementia are decreasing, the overall numbers of cases are still rising due to the growing cohort of older adults. Finding new ways to support aging individuals and their families as they navigate age-related cognitive changes is becoming increasingly important.9 This paper reports on two co-design workshops that brought together MIT researchers, older adults, and caregivers to jointly discuss, design and prototype Generative AI (GenAI)–based solutions for assisting older adults with cognitive challenges.