@inproceedings{bbd76c5e64414cd79ae5ce4b110c2c02,
title = "Examining Age-Bias and Stereotypes of Aging in LLMs",
abstract = "Large Language Models (LLMs) are increasingly being used across applications, ranging from content generation to decision-making, raising concerns about biases embedded in them. While biases related to gender, race, and culture have been studied extensively, understanding age-bias and stereotypes of aging in LLMs remain underexplored. This study analyzes LLM-generated responses to prompts related to aging, revealing stereotypical biases about aging pertaining to technology proficiency, cognitive and physical decline, and job roles. We noted that even responses without explicit age bias also had mentions of ageist stereotypes. We discuss considerations for involving older adults' perspectives through human-in-the-loop methodologies yet exercising caution about aspects like internalized ageism.",
keywords = "Age bias, Ageism, LLMs, older adults",
author = "Sherwin Dewan and Ismail Shaikh and Connie Shaw and Abhilash Sahoo and Akshita Jha and Alisha Pradhan",
note = "Publisher Copyright: {\textcopyright} 2025 Copyright held by the owner/author(s).; 27th International ACM SIGACCESS Conference on Computers and Accessibility, ASSETS 2025 ; Conference date: 26-10-2025 Through 29-10-2025",
year = "2025",
month = oct,
day = "22",
doi = "10.1145/3663547.3746464",
language = "English (US)",
series = "ASSETS 2025 - Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility",
publisher = "Association for Computing Machinery, Inc",
editor = "Kristen Shinohara and Bennett, \{Cynthia L.\} and Martez Mott and Kane, \{Shaun K.\}",
booktitle = "ASSETS 2025 - Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility",
}