TLDR: Artificial intelligence (AI) systems are increasingly reinforcing ageism, leading to the exclusion of older adults from digital advancements. This issue stems from biases in data collection, historical societal prejudices embedded in algorithms, and design flaws that overlook the specific needs and preferences of older populations. Experts highlight the urgent need for inclusive AI development and policy changes to ensure equitable access and benefits for all age groups.
Artificial intelligence (AI) systems, while offering transformative potential across various sectors, are increasingly being identified as a significant factor in perpetuating ageism and excluding older adults from the burgeoning digital future. This concern, highlighted in recent discussions and research, points to a systemic issue where AI technologies inadvertently marginalize older generations.
The root of this digital ageism lies primarily in the data used to train AI algorithms. Older populations are often underrepresented in data collection efforts, leading to systems that are trained on unrepresentative datasets. Consequently, these algorithms may not accurately reflect the diverse needs, behaviors, or preferences of older individuals. Furthermore, AI systems’ reliance on historical data means they can replicate and amplify existing societal biases and patterns of exclusion against older people.
Dr. Heidrun Mollenkopf, President of AGE Platform Europe, emphasized this challenge, stating, “We have a lot of experience with older persons using the technologies, including artificial intelligence in several projects. And from those projects, we know that older persons are not against technologies or any use of artificial intelligence, but it is difficult for them to use it and to understand it and to be sure and certain about its use.” This sentiment underscores that the issue is not a lack of willingness from older adults to engage with technology, but rather a barrier created by the technology itself.
Research indicates that ageism in AI manifests in several interconnected forms, including biases within algorithms and datasets, age stereotypes held by AI developers, the invisibility of older age in AI discourse, discriminatory effects on various age groups, and the outright exclusion of older persons as users of AI technology. Rebecca Chu, a researcher at the University of Toronto, describes this as a series of “cycles of injustice” that implicitly bake bias into technology’s function, disproportionately excluding older adults. She also notes that ageism is often the “most socially accepted bias” despite its universal eventuality.
Design flaws further exacerbate the problem. Many applications developed for older adults tend to focus narrowly on chronic disease and healthcare management, neglecting aspects of pleasure or leisure. This biomedical lens often overlooks normal aspects of aging, such as differences in motor function or perception, leading to technologies that are not user-friendly for this demographic.
The World Health Organization (WHO) has also voiced concerns that unchecked AI technologies could perpetuate existing ageism and undermine the quality of health and social care for older people. Addressing these challenges requires a critical examination of age-related bias in AI systems and a concerted effort to foster inclusivity. Multi-stakeholder events, such as “Harnessing Artificial Intelligence for All Ages: Addressing Ageism” held in Brussels in May 2025, bring together policymakers, industry leaders, academics, and civil society to identify gaps in AI design and regulation, promote inclusive practices, and incentivize the creation of age-inclusive products.
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Ultimately, expanding the understanding of inclusion and exclusion in AI to explicitly incorporate age is crucial. The goal is to steer the design of AI systems towards greater fairness and ensure that the benefits of digital advancements are accessible and equitable for all, regardless of age.
