Selection, Optimization and Compensation: Analyzing Older Adults’ Use- Intention of AI-based Devices
Location
Hilton Waikoloa Village, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
7-1-2025 12:00 AM
End Date
10-1-2025 12:00 AM
Description
Older adults are affected by the digital divide as they use less IT and with lower efficiency. Emerging technologies, namely artificial intelligence (AI), hold the potential to improve or keep up the quality of life for older adults. In the aging process, behavioral patterns change as older adults compensate for age-related losses through targeted selection and behavior optimization. The selection and optimization with compensation (SOC) theory offers a contextualized theory that we applied to explain older adults’ usage behavior towards AI-based devices. We examined the SOC processes of older adults towards their intention to use AI-based devices with a survey of N=210 people aged 65 years and older. Our results show that established constructs such as effort expectancy have limited applicability for older adults, indicating that their age-related adaptation strategies significantly influence their intention to use AI-based devices.
Recommended Citation
Kniepkamp, Sophie; Wortmann, Theresa; and Kroenung, Julia, "Selection, Optimization and Compensation: Analyzing Older Adults’ Use- Intention of AI-based Devices" (2025). Hawaii International Conference on System Sciences 2025 (HICSS-58). 2.
https://aisel.aisnet.org/hicss-58/da/age_and_generational_aspects/2
Selection, Optimization and Compensation: Analyzing Older Adults’ Use- Intention of AI-based Devices
Hilton Waikoloa Village, Hawaii
Older adults are affected by the digital divide as they use less IT and with lower efficiency. Emerging technologies, namely artificial intelligence (AI), hold the potential to improve or keep up the quality of life for older adults. In the aging process, behavioral patterns change as older adults compensate for age-related losses through targeted selection and behavior optimization. The selection and optimization with compensation (SOC) theory offers a contextualized theory that we applied to explain older adults’ usage behavior towards AI-based devices. We examined the SOC processes of older adults towards their intention to use AI-based devices with a survey of N=210 people aged 65 years and older. Our results show that established constructs such as effort expectancy have limited applicability for older adults, indicating that their age-related adaptation strategies significantly influence their intention to use AI-based devices.
https://aisel.aisnet.org/hicss-58/da/age_and_generational_aspects/2