By Jennifer Hewett, Australian Financial Review, 31 January
The online questionnaire wants to know whether I respect and comply with authority. I get five options – strongly agree, agree, neutral, disagree or strongly disagree. I tick “neutral”. Well sort of, sometimes, I think to myself.
Same choice for whether I am good at finding fault with what’s around me at work. I tick “neutral” again, guiltily acknowledging it’s just possible my editor might have a different opinion about whether I am far too good at that particular skill.
The choice seems less ambiguous when I am asked whether I forget to put things back in their proper place. I hover over “strongly agree” or “agree” and tick the latter – perhaps a little optimistically.
And on it goes for 90 questions, with slight variations in the possible answers, as devised by an AI (artificial intelligence) algorithm. My responses to the bot will determine whether I get to the next stage of actually being interviewed for a job by a real person.
I soon get an encouraging email from Michael Morris, chief executive of Employsure – a company which provides advice on workplace relations and health and safety issues to small businesses. If I ever give up journalism, Morris tells me, I can try for a new career at Employsure. AI has approved me. Despite my deep scepticism about the process, I can’t help but feel a little pleased by the bot’s assessment.
That is because my rather self-serving answers to random personality questions fit those of the best performers at Employsure. There’s no possibility of ageism or sexism or any other latest “ism” influencing that. No old schoolmates or university or sporting framework, no biases about looks or clothes or mannerisms or personal history.
Instead, I participated in what is a variation on a personality test – based on the algorithmic analysis provided by another company, PredictiveHire, operating in Europe and Australia and with 20 clients.
Morris says Employsure tested the performance of employees selected by PredictiveHire’s algorithm against the choices of Employsure’s own human recruitment team for much of last year.
The fast-growing company hired around 450 people in 2018 with a workforce now totalling more than 800. Morris wanted good people and those more likely to stay.
The experience convinced him that rather than using more traditional CVs to screen applicants, it was worth paying PredictiveHire for its AI technology as Employsure continues to expand its numbers this year. Employsure now only interviews the 10-15 per cent of those who are graded “yes” or “maybe” by the bot.
“The overlay of AI made a significant difference in overall performance, productivity and tenure,” Morris says. “And it means the recruitment team can have a head start on engaging in better conversations with those who have interviews.” This is still a distinctly minority view among Australian businesses which have been generally reluctant to embrace the promise of AI when it comes to hiring.
The trend to make greater use of AI in business generally is inevitable and accelerating. Just consider all those online “conversations” we now have about customer service and products as the ever-patient bot nudges us this way and that.
Just as inevitably, it is leading to community concerns about whether AI will be used to replace too many people’s jobs. According to a study by the McKinsey Global Institute, intelligent agents and robots could eliminate as much as 30 per cent of human labour by 2030. The scale would dwarf the move away from agricultural labour during the 1900s in the United States and Europe.
Of course, the record of technology shifts over centuries always ending up creating many more other types of jobs does not completely soothe fears that this time it’s different. Even if such alarm is overstated, dramatic changes in technology can certainly prove socially and economically disruptive for long periods. AI can also be scary.
But this version of AI is more about filling new jobs more efficiently. Many large global companies already use it to filter job applicants, especially those coming in at lower levels. Its advocates argue it efficiently eliminates bias or the tendency for people to hire in their own image.
Not that this always goes smoothly – even for the most digitally sophisticated businesses. Amazon abandoned its own AI hiring tool last October when management realised it had only introduced more bias into the process. Its AI system was based on modelling the CVs of those already at the company – who tended to be male. Naturally, that made prospective hires more likely to be male too. So much for gender-diversity targets.
PredictiveHire’s chief executive is Barb Hyman, formerly a human resources executive for the online real estate advertising company REA Group. She says the system doesn’t work for those companies that don’t measure the performance of their existing employees but the data becomes more and more accurate as more information is added.
By matching responses of applicants against only those employees who are already doing well, it can be extremely efficient with immediate payback – especially for larger companies. The data can also be used to change the culture in an organisation by screening the types of personalities who are hired.
Not surprisingly, Hyman says the data demonstrates how different personalities are better fitted to different sorts of roles. So those who do well in caring jobs tend to be reliable and demonstrate traits of modesty and humility. Good salespeople are focused, somewhat self-absorbed, disorganised and transactional. Those who are involved in building long-term business relationships need to be more adaptable, resilient and open.
Sounds more like common sense than AI. But there’s less and less of that around anywhere. AI beckons instead.
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