Ageism and Artificial Intelligence: Protocol for a Scoping Review

Charlene H Chu^{1

2

3}, Kathleen Leslie^{4

5}, Jiamin Shi^{1

6}, Rune Nyrup⁷, Andria Bianchi^{3

6

8}, Shehroz S Khan^{3

9}, Samira Abbasgholizadeh Rahimi^{10

11

12}, Alexandra Lyn⁴, Amanda Grenier^{2

13

14}

Affiliations

¹ Lawrence S Bloomberg Faculty of Nursing, University of Toronto, Toronto, ON, Canada.
² Institute for Life Course and Aging, University of Toronto, Toronto, ON, Canada.
³ KITE Research Institute - Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada.
⁴ Faculty of Health Disciplines, Athabasca University, Athabasca, AB, Canada.
⁵ Canadian Health Workforce Network, Ottawa, ON, Canada.
⁶ Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
⁷ Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, United Kingdom.
⁸ Department of Clinical and Organizational Ethics, University Health Network, Toronto, ON, Canada.
⁹ Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada.
¹⁰ Department of Family Medicine, McGill University, Montreal, QC, Canada.
¹¹ Mila - Quebec AI Institute, Montreal, QC, Canada.
¹² Lady Davis Institute for Medical Research, Herzl Family Practice Centre, Jewish General Hospital, Montreal, QC, Canada.
¹³ Factor-Inwentash Faculty of Social Work, University of Toronto, Toronto, ON, Canada.
¹⁴ Baycrest Hospital, Toronto, ON, Canada.

PMID: 35679118
PMCID: PMC9227654
DOI: 10.2196/33211

Ageism and Artificial Intelligence: Protocol for a Scoping Review

Charlene H Chu et al. JMIR Res Protoc. 2022.

. 2022 Jun 9;11(6):e33211.

doi: 10.2196/33211.

Authors

Affiliations

¹ Lawrence S Bloomberg Faculty of Nursing, University of Toronto, Toronto, ON, Canada.
² Institute for Life Course and Aging, University of Toronto, Toronto, ON, Canada.
³ KITE Research Institute - Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada.
⁴ Faculty of Health Disciplines, Athabasca University, Athabasca, AB, Canada.
⁵ Canadian Health Workforce Network, Ottawa, ON, Canada.
⁶ Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
⁷ Leverhulme Centre for the Future of Intelligence, University of Cambridge, Cambridge, United Kingdom.
⁸ Department of Clinical and Organizational Ethics, University Health Network, Toronto, ON, Canada.
⁹ Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada.
¹⁰ Department of Family Medicine, McGill University, Montreal, QC, Canada.
¹¹ Mila - Quebec AI Institute, Montreal, QC, Canada.
¹² Lady Davis Institute for Medical Research, Herzl Family Practice Centre, Jewish General Hospital, Montreal, QC, Canada.
¹³ Factor-Inwentash Faculty of Social Work, University of Toronto, Toronto, ON, Canada.
¹⁴ Baycrest Hospital, Toronto, ON, Canada.

PMID: 35679118
PMCID: PMC9227654
DOI: 10.2196/33211

Abstract

Background: Artificial intelligence (AI) has emerged as a major driver of technological development in the 21st century, yet little attention has been paid to algorithmic biases toward older adults.

Objective: This paper documents the search strategy and process for a scoping review exploring how age-related bias is encoded or amplified in AI systems as well as the corresponding legal and ethical implications.

Methods: The scoping review follows a 6-stage methodology framework developed by Arksey and O'Malley. The search strategy has been established in 6 databases. We will investigate the legal implications of ageism in AI by searching grey literature databases, targeted websites, and popular search engines and using an iterative search strategy. Studies meet the inclusion criteria if they are in English, peer-reviewed, available electronically in full text, and meet one of the following two additional criteria: (1) include "bias" related to AI in any application (eg, facial recognition) and (2) discuss bias related to the concept of old age or ageism. At least two reviewers will independently conduct the title, abstract, and full-text screening. Search results will be reported using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) reporting guideline. We will chart data on a structured form and conduct a thematic analysis to highlight the societal, legal, and ethical implications reported in the literature.

Results: The database searches resulted in 7595 records when the searches were piloted in November 2021. The scoping review will be completed by December 2022.

Conclusions: The findings will provide interdisciplinary insights into the extent of age-related bias in AI systems. The results will contribute foundational knowledge that can encourage multisectoral cooperation to ensure that AI is developed and deployed in a manner consistent with ethical values and human rights legislation as it relates to an older and aging population. We will publish the review findings in peer-reviewed journals and disseminate the key results with stakeholders via workshops and webinars.

Trial registration: OSF Registries AMG5P; https://osf.io/amg5p.

International registered report identifier (irrid): DERR1-10.2196/33211.

Keywords: age-related biases; ageism; algorithms; artificial intelligence; ethics; gerontology; health database; human rights; search strategy.

©Charlene H Chu, Kathleen Leslie, Jiamin Shi, Rune Nyrup, Andria Bianchi, Shehroz S Khan, Samira Abbasgholizadeh Rahimi, Alexandra Lyn, Amanda Grenier. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 09.06.2022.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

**Figure 1**
Main concepts included in the search strategy. AI: artificial intelligence.

See this image and copyright information in PMC

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Ageism and Artificial Intelligence: Protocol for a Scoping Review

Affiliations

Ageism and Artificial Intelligence: Protocol for a Scoping Review

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Grants and funding

LinkOut - more resources

Full Text Sources