Older adults want a voice in AI’s future

Older adults are being sidelined in decisions about how AI is designed, even as more systems are built specifically for aging, care, and health. According to the article, that gap is showing up both in the workforce behind AI and in the tools being deployed to older users.

Research cited in the piece says older adults are often assumed to be less tech-savvy by employers, which can cost them jobs or promotions despite having the necessary skills and experience. The AI industry, the article argues, reflects that bias: its workforce is largely made up of young men, raising the risk that age and gender bias get baked into apps and models.

That underrepresentation has practical effects. A growing body of research shows older adults are consistently left out of AI model development, making systems less accurate at recognizing or responding to their needs. One example cited is a study of AI-generated images that found pictures of older people were systematically less bright and less sharp than those of younger people.

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At Concordia University, researchers recently completed a yearlong community engagement project on aging alongside AI. Their preliminary findings suggest older adults are concerned that AI tools aimed at aging—such as fall detection and cognitive monitoring—are often created by younger developers who frame aging as something to treat, manage, or prevent.

Health care, consent, and transparency

The article points to a surge of AI tools in the health and wellness industry, many aimed at older people, their bodies, and caregivers. While these systems can help with early disease diagnosis, symptom tracking, and health promotion, older adults raised concerns about care quality and transparency.

A recent study on AI in health care decision-making found some older adults were skeptical that AI could understand complex care needs and generally preferred human interaction. They also said AI use should be transparent and based on informed consent—meaning they want control over when and where they interact with it.

Participants in Concordia’s project described similar experiences, including cases where they interacted with chatbot systems for online banking support and believed they were speaking with a real person. They said their lived experience of aging is missing both from the data used to train AI systems and from the decisions about what gets built.

Fraud and AI literacy

Fraud came up repeatedly in the community discussions. The article notes that AI-enabled scams often target older adults, partly because they are perceived as more trusting. One recent example was a fake CBC article circulated on social media showing journalist Adrienne Arsenault interviewing Galen Weston Jr., who appeared to walk out. The event never happened: the images were AI-generated, and the story pushed a fake investment platform.

Some participants said AI could also be used defensively, to help people spot fraud before they fall for it. But they felt they had not been asked how such protections should work, despite being among the main targets.

What older adults are asking for, the article says, is straightforward:

• a say in what AI gets built
• input into what data trains it
• involvement in how it is governed
• accessible ways to learn AI skills through trusted institutions such as community organizations, schools, and libraries

Several participants favored short, in-person library-based courses over more apps. The article notes that some public libraries, including the Toronto Public Library, already offer AI literacy programs alongside digital skills classes.

Older adults in the project also voiced concern for others affected by generative AI, including artists losing control of their work, and expressed a desire for people of all ages to sometimes “stay analog.” The core issue, the article argues, is not whether older adults can keep up with AI, but whether the people building and governing it are willing to include them in the room.