Executive Summary
Four main themes emerged from the analysis that intersect with older women’s engagement with the digitalised labour market. First, employment gaps constrain older women’s access to employment later in life; second, older women experience digital ageism in a youth-oriented market; third, women’s accrued cultural capital is undervalued; fourth, the increasing use of AI in recruitment is a constraining factor in women’s access to employment.
Women’s life course constrains their access to employment
Women’s life course creates employment gaps
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There are significant knock-on effects from women’s life course that often leads to gaps in their employment, and which affect their employability later in life.
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For this cohort, career roles were not accommodating of marriage or motherhood, and had often resulted in women leaving their professional careers when starting a family.
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Employment gaps essentially become ‘technology gaps’
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Being unemployed, working part-time, or in non-standard roles limits women’s opportunities to keep up-to-date with advancing workplace technologies.
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As such these ‘employment gaps’ essentially become ‘technology gaps’ creating an additional barrier for women wishing to resume mainstream work after fifty.
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This is exacerbated by the rapid evolution of digital technologies.
Women experience digital ageism
The Age Gap
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Women experienced a significant age gap within many workplaces, and this was doubly problematic when applying for jobs as they believed recruiters were often too young to understand the value of their past education and work experience. They therefore believed age to be a primary barrier to finding employment despite existing antidiscrimination law.
Digital Ageism
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Age and gender discrimination are compounded by a stereotyping of older women as ‘less digitally savvy’ than their younger co-workers, adding an additional barrier when seeking new employment.
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Digital skill criteria requirements for jobs discouraged many from applying.
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The increasingly complex digital skill requirements listed on job advertisements prevented many women from applying. This was especially the case for those who had been unemployed, or self-employed for any length of time.
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Digital upskilling later in life can be costly and did not guarantee a return on this investment
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The time and cost of attaining digital skills was a disincentive for many.
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Women did not believe that digital upskilling as a mature worker necessarily led to improved employment opportunities or remuneration.
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Some women claimed that there was increasing digital complexity at work, but this was not accompanied by an increase in pay.
Women experience diminishing cultural capital in the labour market as they age
‘Current or ‘recent’ experience was valued more highly than accrued cultural capital
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Women attempting to re-enter mainstream employment were often rejected by recruiters as not having the right ‘current’ or ‘recent’ work experience.
Digital skills prioritised
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Older women believed their earlier work experience and qualifications were undervalued while youthful digital skills were sought after and prioritised.
Gaining more education later in life did not guarantee more satisfying well-paid work
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Obtaining further mid-life qualifications did not necessarily improve women’s employment outcomes later in life. Women often reached a point where they believed they were overqualified and that organisations did not want to pay for their accrued experience and qualifications.
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Professional women finding limited opportunities for advancement as they aged sought more qualifications to shift into consulting work, but this was not always well remunerated.
Older women’s agency diminished within the context of AI-assisted recruitment
Exclusionary technological design - LinkedIn and AI assisted talent acquisition tools
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The use of AI tools in the recruitment process is problematic, as these can replicate existing age and gender biases. For instance, women claimed their employment gaps were amplified by labour market platforms such as LinkedIn.
Low Awareness of AI-assisted Recruitment Processes
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Women had a low awareness of AI-assisted recruitment tools effectively reducing their agency in the job search process and ultimately their access to employment opportunities.
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Few women interviewed understood how AI-assisted tools such as Applicant Tracking Systems (ATS) and Recruitment Marketing Systems (RMS) or screening and biometric analysis could impact their access to employment opportunities.
Most women had not attempted to build digital capital in the labour market
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Most women were cautious about public participation on social media and were resistant to the notion that they build a personal brand on LinkedIn.
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Most women were not using job platforms like LinkedIn to build digital capital and were therefore less visible to AI processes (ATS and RMS) that source passive candidates.