NEW ZEALAND | AI algorithms are being used by recruitment platforms to sort CVs and identify applicants they consider a strong match for a vacancy.
For aged care and retirement village operators and managers, that can reduce the time spent reviewing applications. But could it also push someone they would have wanted to meet further down the list?
A shortlist offers somewhere to start when recruitment sits alongside running services and covering vacancies. The concern is whether it becomes the point where the manager stops looking. Someone outside the recommended group may have experience worth exploring, even if their CV doesn't fit the brief neatly.
SEEK’s tools draw on candidate profiles, CVs, job advertisements, and millions of employers’ previous shortlisting decisions to predict who is likely to be shortlisted. SEEK states that recruitment decisions remain the employer’s responsibility. A prediction about shortlisting doesn't establish how someone will work with residents or colleagues.
The requirements entered also matter. SEEK lets employers set screening questions and choose to move applicants who fail essential requirements automatically to “Not suitable”. Making previous aged care experience compulsory for a position that allows training could exclude someone with relevant skills from another sector.
An applicant for reception, administration, or care work might bring experience handling difficult conversations, supporting people, and managing competing demands. At interview, their approach may prove well suited to residents and the team. Learning a system or procedure can be more straightforward than changing how someone treats people.
Clinical qualifications, professional registration, and specialist skills remain essential where required. There's also a distinction between fitting the team and resembling everyone already in it. Patience, judgement, and respect can come with a different background or perspective.
Research by Robert Half released earlier this year identified concerns about automated screening. Among 250 New Zealand hiring managers surveyed, 37 percent cited screening tools missing strong candidates as a challenge. Respondents worked in finance, accounting, and technology, so the finding does not measure aged care recruitment.
In the United Kingdom, the Chartered Institute of Personnel and Development’s selection guidance considers applicants’ ability to perform the role, contribute to the organisation, and develop. It also favours structured interviews and relevant skills assessments to reduce the influence of personal bias.
But what about AI bias? A system drawing on previous shortlisting decisions may repeat the preferences behind them. Managers can overlook people too, but reading beyond the recommendations gives them a chance to consider experience the ranking may not fully recognise.
That unexpected candidate may need more training but bring the manner and willingness to learn that residents and colleagues value. Whether that trade-off is worthwhile becomes clearer when they have the opportunity to explain their experience. The question is whether the first AI screening leaves room for that conversation.
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