Preference-Aligned Options from Generative AI Compensates for Age-Related Cognitive Decline in Decision Making

Abstract

Older adults often experience increased difficulty in decision making due to age-related declines particularly in contexts that require information search or the generation of alternatives from memory. This study examined whether using generative AI for information search enhances choice satisfaction and reduces choice difficulty among older adults. A total of 130 participants (younger, n = 56; older, n = 74) completed a music-selection task under AI-use and AI-nonuse conditions across two contexts: previously experienced (road trip) and not previously experienced (space travel). In the AI-nonuse condition, participants generated candidate options from memory; in the AI-use condition, GPT-4o presented options tailored to individual preferences. Cognitive functions, including working memory, processing speed, verbal comprehension, and perceptual reasoning, were assessed. Results showed that AI use significantly reduced perceived choice difficulty across age groups, with larger benefits in unfamiliar contexts. Regarding cognitive function, among older adults, lower cognitive function was associated with fewer recalled options, higher choice difficulty, and lower satisfaction in the AI-nonuse condition; these associations were substantially attenuated when AI was used. These results demonstrate that generative AI can mitigate age-related cognitive constraints by reducing the cognitive load associated with information search during decision making. While the use of AI reduced perceived difficulty, choice satisfaction remained unchanged, suggesting that autonomy in decision making was preserved. These findings indicate that generative AI can support everyday decision making by compensating for the constraints in information search that older adults face due to cognitive decline.