Unpacking Value Tensions in Older Adults’ Engagement with Generative AI

Abstract Generative artificial intelligence (GAI) refers to AI systems that create new content—such as text, images, audio, or video—based on patterns learned from large datasets. Unlike traditional digital technologies that are task-specific and predictable, GAI systems support flexible, open-ended interaction. However, this flexibility introduces several challenges, including unpredictable outputs (e.g., hallucinations), ambiguous authorship, and humanlike interactions, especially in conversational tools. We used a value sensitive design approach and reflexive thematic analysis to examine how community-dwelling older adults engage with GAI. Semi-structured interviews with twelve U.S.-based older adults (median age = 64; median CFI = 2.5) explored their perceptions, experiences, and concerns. Participants (n = 8) who used tools like Copilot or ChatGPT described using them for small, routine tasks such as finding information and editing text (“for the little things”; “find out things that I’ve forgotten”) and appreciated their ease of use (“I could tell it more precisely what I wanted”; “answers me back in detail”; “pretty simple to use”). However, both users and non-users expressed value tensions, particularly around trust (“It’s functional, but I think part of it is I don’t trust it”), lack of accountability (“I mean who’s giving you those answers?”), absence of informed consent (“an excuse to legitimize thievery”), algorithmic bias (“there’s so much misinformation out there”), and broader concerns about societal harm (“it scares me about what human nature will do with AI”). Notably, even frequent users demonstrated critical engagement rather than overtrust, pointing to the need for design practices that engage with—not undermine—users’ healthy skepticism.

Authors

Institutions

Publication Details

Journal
Innovation in Aging
Published
2025-12-01
DOI
https://doi.org/10.1093/geroni/igaf122.4041
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Unpacking Value Tensions in Older Adults’ Engagement with Generative AI

Debaleena Chattopadhyay, Tasneem Mubashshira
Innovation in Aging
Artificial Intelligence in Healthcare and Education
article

Unpacking Value Tensions in Older Adults’ Engagement with Generative AI

Debaleena Chattopadhyay, Tasneem Mubashshira
article en

Abstract

Abstract Generative artificial intelligence (GAI) refers to AI systems that create new content—such as text, images, audio, or video—based on patterns learned from large datasets. Unlike traditional digital technologies that are task-specific and predictable, GAI systems support flexible, open-ended interaction. However, this flexibility introduces several challenges, including unpredictable outputs (e.g., hallucinations), ambiguous authorship, and humanlike interactions, especially in conversational tools. We used a value sensitive design approach and reflexive thematic analysis to examine how community-dwelling older adults engage with GAI. Semi-structured interviews with twelve U.S.-based older adults (median age = 64; median CFI = 2.5) explored their perceptions, experiences, and concerns. Participants (n = 8) who used tools like Copilot or ChatGPT described using them for small, routine tasks such as finding information and editing text (“for the little things”; “find out things that I’ve forgotten”) and appreciated their ease of use (“I could tell it more precisely what I wanted”; “answers me back in detail”; “pretty simple to use”). However, both users and non-users expressed value tensions, particularly around trust (“It’s functional, but I think part of it is I don’t trust it”), lack of accountability (“I mean who’s giving you those answers?”), absence of informed consent (“an excuse to legitimize thievery”), algorithmic bias (“there’s so much misinformation out there”), and broader concerns about societal harm (“it scares me about what human nature will do with AI”). Notably, even frequent users demonstrated critical engagement rather than overtrust, pointing to the need for design practices that engage with—not undermine—users’ healthy skepticism.

Innovation in AgingVol. 9(Supplement_2)
University of Illinois Chicago (US), University of Chicago (US)
Openalex Percentile: Top 36%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Unpacking Value Tensions in Older Adults’ Engagement with Generative AI — Debaleena Chattopadhyay, Tasneem Mubashshira · Innovation in Aging (2025) | TGRS Research Map | TGRS