AI systems can be biased against older workers during hiring. Why tackling this is crucial

T he integration of AI into various sectors has transformed the way we work and interact with each other , offering unprecedented opportunities for efficiency and innovation. However, this rapid technological advancement also poses significant challenges, particularly concerning age bias and workforce inclusivity. The urgency of age-proofing AI stems from two converging trends.

According to the UN, by 2050, over 2 billion people will be aged 60 or older, more than double the total in 2017 . At the same time, AI tools are increasingly being used to streamline hiring processes, automate decision-making and enhance employee productivity. Companies that bring varied perspectives to problem-solving can unlock the untapped potential of their intergenerational workforce .



In doing so, they will be better positioned to navigate demographic shifts and technological advancements. So, age-proofing AI is not just a moral imperative but a strategic business necessity. As AI continues to transform industries and sectors, its integration into workplaces raises urgent questions about fairness and inclusivity.

One of the most pressing concerns when it comes to the use of AI in the workplace is its potential to perpetuate systemic biases, including ageism. Despite the focus on race and gender biases, age bias remains largely overlooked, posing significant risks for social equity in ageing societies . For example, AI systems can inadvertently discriminate against older workers during the hiring process, favouring younger applicants.

This oversight can lead to further marginalization of older employees in the workforce, exacerbating existing social inequalities. Recent high-profile cases have highlighted the legal and reputational risks companies face if the AI systems they deploy have unchecked biases. For instance, the Equal Employment Opportunity Commission (EEOC) settled a lawsuit with iTutorGroup for employing AI software that discriminated against older applicants .

Such incidents underscore the need for inclusive practices in AI deployment. Another challenge in integrating older workers into an AI-powered workplace is the persistence of myths surrounding their adaptability to new technologies. Companies often assume that older workers are resistant to change or less willing to adapt to new technologies.

As leaders look to integrate Generative AI tools and AI agents, a common belief is that younger workers will be better equipped to seamlessly incorporate these new tools into their workflows. However, recent research, including Generation’s “Age-Proofing AI” study , suggests this view may be unfounded. According to previous Generation research from 2023 , when hiring managers were asked to assess the job performance of the mid-career and older workers they already employ, a striking 89% reported that experienced workers performed as well, if not better, than their younger peers.

This data contradicts the assumption of technological ineptitude and underscores the valuable contributions of older workers. With AI tools evolving at an unprecedented rate, organizations must act swiftly to integrate these technologies into their various operations and processes. If business leaders fail to adapt quickly enough, they risk losing competitiveness and the unprecedented opportunities for efficiency that come with AI implementation .

This urgency necessitates that leaders not only promote AI use but also ensure that older workers are being offered adequate training opportunities and psychologically safe environments where they feel encouraged to upskill without risking job security. With the right training and support system in place, mid-career and older workers can fully harness the power of AI , bringing a level of strategic thinking and contextual understanding that can significantly enhance AI deployment for any organization. Therefore, it is imperative for businesses to invest in tailored training programmes that address the specific needs and learning styles of mid-career and older professionals.

A crucial aspect of age-proofing AI is ensuring that workers, particularly older ones, understand the value of AI and are equipped with the necessary skills. As AI becomes increasingly integral to various sectors, its potential to transform workplaces by lowering barriers to skill acquisition and enhancing productivity is significant. However, this transformation must be accompanied by a commitment to fairness and inclusivity to ensure that older workers are not left behind .

The demographic shift towards an ageing workforce underscores the need for organizations to prioritize age diversity in their diversity and inclusion initiatives. Despite this imperative, many companies overlook age diversity, and consequently, they don’t fully harness the capabilities and experiences of older workers . Addressing age bias in AI systems is imperative not only for promoting social equity and preventing discrimination but also for enhancing organizational performance and innovation through a diverse workforce .

Consequently, age-proofing AI is not just a moral imperative but a strategic necessity for companies around the world. This article is republished from the World Economic Forum under a Creative Commons license. Read the original article .

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