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Employers are undermining trust in their use of AI in hiring
Editorial by Christian Saint Cyr
National Director / Canadian Job Development Network
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The use of artificial intelligence is active in many parts of our lives and where it gets a lot of attention is in searching for and evaluating job candidates. While this is becoming common place, many job seekers are uncomfortable with its use and in many cases passing judgement on employers that use it without question.
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A recent poll surveyed nearly 3,000 job candidates globally and found that 25% trust employers less if AI is used to evaluate their information.
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The findings come as 72% of HR professionals across the world admit they are now using AI tools for their work, according to poll from HireVue.
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The use of artificial intelligence is being applied to nearly all aspects of human resources. According to the HireVue poll, human resources leaders said the most common uses of AI are:
- Resumé screening (35%)
- Training (35%)
- Candidate communications (34%)
- Recruiting (33%)
- Candidate screening (31%)
- Assessments (31%)
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The jobseekers survey, conducted by Gartner HR Practice, found that only 26% of them have trust that AI will fairly evaluate them in the recruiting process.
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Employers' Lack of Trust
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One of the reasons employers are turning increasingly to AI is concern over how frequently job seekers turn to AI in searching for employers.
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"It's getting harder for employers to evaluate candidates' true abilities, and in some cases, their identities," according to Jamie Kohn, Senior Research Director, with Gartner HR Practice.
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Earlier research from Gartner predicted that one in four candidate profiles worldwide will be fake by the year 2028.
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Another poll from the organization found that six per cent of jobseekers had committed interview fraud, where they either posed as someone else or had someone else pose as them in an interview.
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"Employers are increasingly concerned about candidate fraud, which creates cybersecurity risks that can be far more serious than making a bad hire," Kohn said.
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What can HR leaders do?
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Gartner suggests, addressing the lack of trust between employers and jobseekers requires organizations to set clear expectations and communicate hiring standards.
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"Employers should explain to candidates how they define acceptable use of AI and emphasize their fraud detection efforts, including the legal consequences if fraudulent behaviour is detected," Gartner advised.
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To avoid being duped by jobseekers, employers are also advised to implement anti-cheating safeguards, such as conducting in-person interviews.
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"Fraud prevention must extend beyond the initial hiring phase," according to Gartner.
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"Employers should focus on system-level validation rather than individual surveillance – tightening background checks, using risk-based data monitoring, and embedding detection tools like identity verification and anomaly alerts in recruiting systems."
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Understanding the Job Seekers' Perspective
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I was recently watching an interview with a job seeker who said, "I just want a job, I don't want to be an expert at writing cover letters."
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This is a common refrain job seekers use to justify using AI to write cover letters, prepare resumes, respond in interviews and even complete online competency tests.
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To their credit, an employer may see the cover letter, resume and application as simply an information resource and if AI can prepare it better, why not?
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Other employers are going to say these tools are just another way of demonstrating attention to detail, articulation and self-marketing. If AI is writing it, how do we know anything about what the candidate really thinks and believes?
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It’s worth noting that people who are better communicators and people who are better with technology have increasingly done better at job search over the past 30 years. AI now has the ability to level the playing field.
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If artificial intelligence is indeed just another tool, then it's important for job seekers to be able to use it to support their job search but not purposely mislead an employer.
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Whenever I've coached job seekers, I've told them that anything they write in their cover letter or say in their interview should be something they can back-up. Meaning, if there is more than one way of seeing something or more than one perspective, they should be prepared to share their reasoning in sharing what they’ve shared.
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The classic example is someone who was fired from a past job. To say they resigned to pursue other opportunities is a lie. To say the position ended over a difference of opinion, could be argued, if the prospective employer probes for more information.
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Similarly, job seekers should be prepared to justify their use of AI as a tool, rather than a way of misleading an employer or eliminating expecting responsibilities.
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Understanding the Employers' Perspective
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Over the last two decades, employers have introduced many new technologies to make applying for jobs easier, to better promote jobs and to ease the process of onboarding new employees.
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If AI is just another tool, it makes sense they will use this to achieve all of the things noted above such as screening resumes, communicating with candidates and evaluating potential applicants.
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People become concerned when employers use it justify hiring a candidate they may not hire if the decision was solely up to them. Quite often it’s used to justify a hiring decision that isn’t ‘inclusive’.
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If I use AI, to sort for the ‘best-qualified' candidates, and search for Canadian education and work experience; length of service; highest position achieved; and past salaries; then more than likely it’s hiring a middle-age, white, Canadian-born male. Not always, but in the majority of cases.
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Why is this? Because today in Canada, most recent immigrants are not white, and typically have international-experience and international-education, so they will be ranked lower for lacking Canadian experience and education. A significantly higher portion of women over men, take breaks to have and raise children, so male candidates are going to typically have more years of sustained work experience. Men are also more likely to fill roles in supervisory and managerial positions and typically have earned higher salaries than their female counterparts.
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I'm not saying employers should hire someone who has less education, or less experience, or who's had less career opportunities, just that these traditional criteria are what put middle-age, white males at the top of the list.
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Employers will often argue they don’t have any bias, in fact, they are relying on AI to eliminate bias.
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Instead of these traditional deal-breaker criteria, employers can evaluate criteria that make people qualified for the position, not necessarily having 'the most' of anything, such as education, experience or advancement opportunities.
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Instead, employers can use AI to sort candidates who have a minimum education level, a minimum number of years work experience, or a minimum certification. This would essentially create a large pool of 'qualified candidates' who are all capable of doing the job. This would avoid unnecessarily screening out candidates who may otherwise be great employees.
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In an ideal world, the employer may choose to narrow this pool through short phone interviews, personality assessments, sorting for key workplace competencies, or reference checks.
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To use AI further, perhaps a series of in-person evaluations that are recorded and evaluated by AI could be used to narrow down suitable candidates.
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Of course, good old-fashioned interviewing is a great way of narrowing down a candidate pool of qualified applicants.
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Employers need to understand that if they are going to use a tool without considering how the tool works or the quality of candidates it suggests, then job seekers are not only going to judge them for it, they will be bypassed as a result.
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Many years ago, a client of mine applied for a job with a large retail chain. They asked her to complete a questionnaire that asked 150 different ways, whether stealing is justified.
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She did well, on the quiz and only got one question wrong. When asked, what is the total value of goods you have taken from your workplace, her response was $10. She argued that between pens and paperclips, she believed she'd take about $10 worth of things home.
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This response got her an automatic fail and bared her from ever working for that chain in the future. Even though the question provided space for an explanation, anyone putting a value above zero dollars in this answer resulted in automatic fail.
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When I asked the manager of the store, why this wasn’t taken into consideration, she told me that her human resources department believes that if a person is willing to acknowledge any sort of financial impropriety, it indicates a much bigger trend.
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Rationally, we can look at this and say someone who is willing to acknowledge some grey area is likely to be more honest than someone who resorts to lying to get a perfect questionnaire, but where is the room for personal interpretation?
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For both job seekers and employers there is the rational use of AI and irrational use of AI. People who rationally use it see it as a tool and should be recognized for this in the workplace.
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People who irrationally use AI, never question the data going in or coming out and people who see it as only a pathway to employment or 'the best' candidate, are actually demonstrating they really don't get the value of artificial intelligence.
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The best candidate is rarely the best person on paper and it's likely an employer won't realize they are were or weren't the best candidate until they've worked for them for some time and demonstrated what they can and can't do when they are no longer subject to evaluation and scrutiny.
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AI is great for evaluating experience, education, training and hard skills. I’d say, it can even be valuable in evaluating soft skills. What hiring managers need to think about are qualities that cannot be easily ranked or evaluated such as trust, integrity, loyalty, hard work, enthusiasm, character, honesty and commitment.
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This is our place in job development, co-op education and other types of employer engagement. We need employers to think more broadly about hiring, not less. We don’t want them to resist new and emerging technologies but to work in concert with them and help employers see candidates based on their ability to contribute to the team, be a good fit for the organization and as someone the employer will value more and more over time.
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We’ll be discussing the growing use of AI at our #MotivatingMondays meeting of the Canadian Job Development Network, Monday August 25th at 8:30am Pacific; 9:30am Mountain; 10:30am Central; 11:30am Eastern; 12:30pm Atlantic and at 1pm in Newfoundland.
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On the morning of Monday August 25th 'Click this Link' to join the session LIVE.
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'Developing a Comprehensive Approach to Effective Job Development'
WORKSHOP
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This Thursday August 28th is going to be your LAST DAY to register for ‘Developing a Comprehensive Approach to Job Development’, and still get the 20% discount on registration. If you or your colleagues haven’t yet registered, just visit: www.jobdevelopment.org/pro-d where you can register and learn everything you need to know.
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'National Networking Day for Job Developers'
NETWORKING IN LOCAL COMMUNITIES
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We’re now less than a month from the National Networking Day for Job Developers, on September 19th. We’ve lined up all of our sponsors but if there isn’t a session in your community we have an online version everyone can attend. If you haven’t yet registered or want to learn more, just visit: www.jobdevelopment.org/nnd
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