AI Inequalities: Age

Should your age matter for getting and keeping a job? For a long time, we have regarded age as a protected category that should not be taken into consideration when employers decide who to hire and fire. But with the growing use of Artificial Intelligence (AI), there are many ways for age to suddenly matter in who is selected for a job, what kind of work they might do, or how a worker is managed.

Research shows that both younger and older workers are disproportionately negatively impacted by the use of AI in the workplace. Young workers tend to be more exposed to and impacted by AI both because AI is more used in the hiring and management of entry-level jobs, and because young workers tend to dominate in more precarious work, such as platform work and warehouse work, where so-called algorithmic management is more established.  Often this involves increased levels of surveillance and work intensification that undermine fair working conditions, creating feelings of unfairness and disorientation.

At the same time, older workers experience exclusion and harmful impacts with uses of AI as they are either unable to access employment or are ‘managed out’ through algorithmic management techniques. This can happen even if data about age is not explicitly collected but other data stand in as proxy, like the e-mail account that someone uses when applying for jobs, or the way that job adverts are targeted at specific groups based on behavioural data that would likely exclude older workers, like membership of particular social media groups. 

Once in work, research has shown how new technologies, including tracking devices and wearable technologies, are used to set targets that are often not reachable for older bodies, such as routes and delivery times, and are therefore used to replace such workers with younger workers. Although these kinds of data-driven techniques are more entrenched in precarious sectors linked to the gig economy that have an overrepresentation of younger workers, with the rapid advancements in AI technologies these kinds of practices are migrating to more standard forms of employment, including in postal work and hospitality, where the workforce has traditionally been more diverse.    

We might think that AI is actually something that is more prevalent in white collar work amongst ‘prime-aged’ workers, and although engagement with AI is most prevalent amongst such workers, research shows that they tend to be better positioned in terms of finding such tools complimentary to existing skills rather than requiring upskilling or potential replacement. They are therefore more likely to be in a position to exploit the opportunities of AI rather than finding them threatening to their work.

Such divisions look set to be widening with the uptake of generative AI by workers declining with age, with only 34% of women and 42% of men in the age group 55-65 say that they use generative AI tools at least once a week in comparison to 71% of men and 59% of women in the age group 18-24 according to a global survey carried out in 2024 by the World Economic Forum with 25,000 working adults. Research also shows that older workers are much more likely to experience emerging technologies as negative or harmful and feel at risk from the widespread adoption of generative AI because they lack adequate skills.  

So what is being done to address the inequalities relating to AI and age? Efforts within the EU and elsewhere have been made to advance more age-sensitive design for work environments and calls have been made in the UK to account better for older workers in digital inclusion policies and to provide more digital skills education for younger people. This includes consideration for how both older and younger workers can be better prepared for AI-driven workplaces and to ensure that policies are in place to safeguard workers who are particularly vulnerable to the harmful impacts of AI across the labour market. 

Workers themselves have also been actively resisting harmful uses of AI in the workplace, both with and without union support, particularly in the gig economy where we have seen young workers, including Deliveroo couriers and Uber drivers, fight for better protections against algorithmic management techniques and entitlements to full workers’ rights. However, outside these focused actions on particular platforms, it is worth remembering that union membership amongst young workers remains significantly lower than other age groups, and that their experiences are therefore not always fully considered in union strategies, despite their disproportionate exposure to AI in the workplace. Adequately addressing AI inequalities relating to age therefore remains a significant challenge.

TUC Cymru is campaigning for all workers to be protected against the risks of AI.  If you’re a younger or older worker and concerned about these issues, raise them at your trade union branch.  TUC Cymru has successfully negotiated guidance on the use of AI in the public sector.  Use it and adapt it for your workplace.  

TUC is campaigning for additional legal protections against the threats of AI and has produced a range of materials to assist reps and officers.  

The AI Inequalities at Work report is published on the Data Justice Lab’s website.