A Study on the Current Status and Improvement Strategies of Algorithmic Literacy among Older Adults—A Case Study of Zhenjiang China
- DOI
- 10.2991/978-2-38476-323-8_58How to use a DOI?
- Keywords
- Algorithmic Literacy; Older Adults; Digital Environment; Algorithmic Bias; Critical Evaluation
- Abstract
This study investigates the algorithmic literacy of older adults in Zhenjiang, focusing on their understanding of algorithmic knowledge, usage skills, critical evaluation abilities, privacy and security awareness, and recognition of the social and ethical impacts of algorithms. The widespread use of algorithms in smart and digital environments offers convenient services like intelligent recommendations but also presents risks, including algorithmic bias and manipulation. The research aims to assess older adults' adaptability to these algorithm-driven environments, identifying strategies to enhance their algorithmic literacy. The goal is to help older adults become active participants in the digital ecosystem and promote a healthy, positive digital culture.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Qin Xiao AU - Yongwei Zhang AU - Mimi Chen PY - 2024 DA - 2024/12/23 TI - A Study on the Current Status and Improvement Strategies of Algorithmic Literacy among Older Adults—A Case Study of Zhenjiang China BT - Proceedings of the 2024 7th International Conference on Humanities Education and Social Sciences (ICHESS 2024) PB - Atlantis Press SP - 486 EP - 498 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-323-8_58 DO - 10.2991/978-2-38476-323-8_58 ID - Xiao2024 ER -