In today's rapidly evolving technological landscape, the automation and integration of artificial intelligence (AI) is increasing in prevalence in various industries. As these transformations continue to become normalised, concerns arise regarding their potential impact on the workforce, particularly for older workers.
Older adults are more vulnerable to the negative distributional impacts of automation, digitalisation, and AI across societies and in labour markets, than any other age group. Digital vulnerability, in this case, consists of difficulties in accessing digitalised healthcare and social and public services, and the impact of increased digitalisation on the sustainability of their later working lives. Data suggests that older workers are at a higher risk of exposure to AI-related job threats, across job hierarchies in the EU and the US. Some of the disproportionate impacts older workers face from rapid technological innovation and transformation include:
- Age-related bias in recruitment. Here AI may eliminate older workers from candidate pools;
- High-level job insecurity. Due to the automation of work, whereby older workers are usually slower to adapt to new practices, making them more vulnerable to redundancies;
- Inadequate/outdated policy frameworks. These mean older workers are not protected from automation-related threats in the labour market.
In the post-Covid era, organisations are changing their workforce strategies at a faster pace. This includes automating jobs by replacing manual or routine tasks with robots, introducing new jobs that require high-level digital skills, and digitalising existing workflow processes. These changes are becoming more common, meaning older workers are now required to re-skill or upskill to remain in labour markets.
However, processes of upskilling and re-skilling are not straightforward for older workers–existing evidence shows that older adults struggle more to catch up with digitised processes than their younger counterparts. Despite the potential benefits of increased earnings, cheaper goods, improved communication, time-saving, and higher employability, the numbers of internet non-users are highest amongst older age groups, especially those who are economically inactive or living alone. Such evidence indicates that stereotyping all older adults as unwilling to engage with digitised systems and environments is unhelpful. This is due to the significant differences in geographic location, socio-economic status, education, and lifestyle choices that determine the extent of their interest, engagement, and skills within digital environments. Older people’s lack of digital engagement, leading to the grey digital divide, may be viewed as a form of ageism as it prevents them from being fully integrated into mainstream digital society and workplaces.
Whether it is through choice or compulsion, disengagement from digital environments impacts active and healthy ageing. For example, digital disengagement can lead to feelings of disconnection and isolation from younger loved ones who are usually more digitally connected. It can also result in a lack of economic activity, due to forced withdrawal from heavily digitised labour markets. Overcoming ageist stereotypes and biases, while promoting a culture of inclusivity and continuous learning, is essential for older workers to be able to age actively and embark on future AI-driven careers.
There are ethical and policy-based implications regarding older people’s digital dis-connectivity. For instance, older adults often end up being ignored or lumped together with other age groups by policymakers (see for example the UK’s digital inclusion charter). Furthermore, research remains divided regarding the age threshold used to account for the digital divide among older populations. Here, there are potentially two groups; those below and those above retirement age. Needless to say, existing ‘active ageing’ policies and frameworks are not fit for purpose in the AI-powered digital era. In such a period, digital economy regulations and other regulatory structures need to be updated and complemented by ‘age-sensitive’ digital frameworks and ageing strategies, to guide fair and ethical digital practices at social and institutional levels. To ensure older adults’ labour market readiness, there is a need to understand:
- How diverse groups of older workers can prepare themselves for future AI-driven workplaces and organisations;
- What organisational human resource strategies are needed for older workers to sustain their later working lives in the digital economy;
- Which employment policies and labour market regulations will safeguard vulnerable older workers from the adverse impacts of AI transformation/machine learning in the labour market.
While extended working life policies are crucial for addressing challenges related to ageing populations, the emergence of AI technologies presents new challenges and opportunities. By aligning extended working life policies with changing skill requirements, addressing digital data bias, promoting digital upskilling, and fostering age-inclusive digital practices, organisations and policymakers can harness the potential of AI for older workers to successfully participate in the AI-driven future workforce. In other words, we will need an institutionally active ‘digital’ ageing framework. This may involve a three-dimensional approach. First, understanding the steps to digital integration, for example, how this is impacted by older adults’ lifestyle choices, perceptions, attitudes, and motivations. Second, responding to the barriers to digital participation, such as a lack of digital skills or connectivity. And third, redesigning the trigger factors in employment, for example, algorithm-based age-biases in recruitment processes and/or digital skills training management systems suitable for older workers.
Through understanding the factors that influence older adults’ digital literacy, and how this impacts their ability to continue working, we will be able to identify any intra-group differences. This knowledge may be employed by organisations to create industry-specific transitional digital workplace strategies and employment systems that are well-informed and effective.
Finally, the integration of AI into the workplace is a transformative process that impacts employees of all ages. While older workers face specific challenges in adapting to an AI-driven or digitised work environment, they also possess valuable skills and experience that can contribute to the successful implementation and utilisation of these technologies. By providing targeted training, fostering a culture of continuous learning, and embracing intergenerational collaborations, organisations can ensure that older workers are prepared for the AI takeover at work.
About the Author
Dr Sajia Ferdous is Visiting Academic in the Institute on Ageing Population. She is a Lecturer in Organisational Behaviour at Queen’s Management School, Queen’s University Belfast. Before joining Queen’s, Sajia held teaching positions at The University of Manchester. She completed her PhD in Business and Management from Alliance Manchester Business School, The University of Manchester.
Opinions of the blogger is their own and not endorsed by the Institute
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