Recruiters: The corporate hiring machine is evolving. Can you feel it?
As recently as a year ago, many top companies still selected candidates based on the most misleading of heuristics: The school they attended.
Harvard? Right this way! Community college? No thanks, we don’t take your kind around here.
This Pearson Hardman-style hiring strategy may have ‘worked’ in the past. Not any more, for two reasons: A) the talent isn’t out there, and B) everyday people expect a better standard of hiring fairness. They know that opportunity isn’t distributed equally, and that elite colleges are more a proxy for privilege than actual performance potential.
(Funny that it took a labor shortage to show companies that potential can come from anywhere. Psychologists and sociologists have known it, and have been saying it, for decades.)
Regardless, you’ve got LinkedIn CEO Ryan Roslansky telling Fortune that its company is favouring soft skills over college degrees, because such a practice creates a ‘much more efficient, equitable labor market, which then creates better opportunities for all’. He’s right about this approach. Even if you take away the benefits to diversity and inclusion, it makes sense purely mathematically: Now your hiring pool has increased from a few hundred thousand candidates to, at the very least, millions.
Resumes foster bias. Despite this fact, we insist on using them. Why? Because, until now, there hasn’t been a compelling reason not to. You could screen, interview, hire, and get warm bodies in seats with relative ease. Business could go on. Consequently, bias became a can that could be continually kicked down the road. Not anymore, for reasons discussed above.
The same is true for hire quality. Google ‘how to measure quality of hire’ and you’ll get a million different answers. Some advocate the for speed- or time-to-productivity approach; others say it’s about measuring ‘culture fit’. One or both of those might be true, but that’s beside the point: hire quality is nebulous not by its nature, but because the inputs (i.e. resumes) are messing with the outcomes.
We know that conscientiousness (that is, the propensity for someone work diligently and systematically on tasks) is a good predictor of on-the-job success. We also know that structured interviews are the best explainer (at 26%) of employee performance (versus previous job experience, which explains just 3%).
We might construct a valid candidate interviewing and vetting process based on these two facts alone. Fundamentally, we know that if A) we look for conscientiousness, and B) we do it in a structured, fair, repeatable way, we’ll get good candidates. Hire quality will take care of itself. Good inputs, good outcomes. Voila.
(It’s not quite that simple, but you get the point: There are reliable, proven ways to ensure validity, and the two examples cited above are very real and useable.)
Instead we rely on unstructured interviews, unruly hiring managers, and resumes – none of which can determine how hard-working a candidate is. Bad inputs that create bad outcomes. Consequently, we regularly examine hire quality and wonder why we struggle to measure it, or worse, connect it to the wider financial outcomes of our business.
Let’s keep this as simple as possible.
Our free job interview rubric contains more than 20 questions designed by our psychologists to help you uncover hire quality. Get it here, use it, and let us know how you found it.
There are millions of ways to assess for soft skills in interviews, just as there are millions of ways to calculate quality of hire. You may get some success by going it alone, but humans are, historically speaking, terrible at accurately assessing personality traits (and therefore, hire quality).
Our Ai Smart Interviewer does this very thing. Using deep, always-evolving personality science, our platform interviews and assesses candidates for desirable soft skills and behaviors, and even matches the resultant talent profiles to your company values.
Of course, the benefit is that hire quality is achieved and proven for you – you don’t have to worry about biased interviewers, bad questions, enforcing consistent processes, and the other headaches of recruitment. With that time back, you can focus on your people.
Or, think about it this way: LinkedIn is getting really smart with its hiring. Other companies like Apple, Delta, and IBM are too. Will you be left behind?
https://www.shortlist.net.au/
MELBOURNE, July 2020: Australian AI recruitment start-up Sapia, has published peer-reviewed research validating a new AI-based approach to talent assessment that determines personality and job suitability through text.
The research was published by IEEE. https://ieeexplore.ieee.org/document/9121971
Personality assessments have long been used to supplement CV data. It is widely accepted that one’s personality can be a predictor of job performance and suitability. Thus, Sapia uses structured text-based interviews, NLP, and machine learning to identify personality traits by analysing text answers to questions related to the job being applied for.
Every candidate gets a “chat based smart interview”. As no demographic data is gathered from other sources such as CVs, the process is blind to gender, race and characteristics that are not relevant in candidate selection. The research validates the accuracy of Sapia’s AI approach. Lastly, it also signals a huge improvement to personality tests, where the candidate experience is underwhelming.
Also Know, Personality AI refers to the use of artificial intelligence (AI) technologies to analyze and understand human personality traits, tendencies, and behavior patterns. This field of AI has gained significant attention in recent years, as businesses and organizations seek to better understand their customers, employees, and other stakeholders.
Barbara Hyman, Sapia (Formerly PredictiveHire) CEO says chat-based interviews address the three big failures of current assessments – ghosting, bias and trust.
“Recruiters are the ultimate ghosters,” Ms Hyman says. “With Sapia, the fact that every single candidate receives a personalised learning profile is gold for candidates and your employer brand. Using text to analyse fit that’s blind to gender, race, age and any personal factors is a must-have in today’s current climate and means every company can introduce bias interruption for every hire and promotion. Imagine what that will do to diversity in hiring”
Principal Data Scientist Buddhi Jayatilleke says “language has long been seen as a source of truth for personality- it defines who we are. This technology offers a direct way to understand personality from language. All is done by using an experience that is human and empowering. Additionally, this capability can be used for assessment and personalised career coaching. Furthermore, it could be a game changer for job seekers, universities, and employers.”
Candidates across 34 countries have experienced Sapia’s unique chat-based interviews. More insight into how the technology works can be found here. https://sapia.ai/science-explained/
Sapia (Formerly PredictiveHire) is a team of data scientists, engineers and HR professionals. Together we have built a product suite that is based on science and built to humanise hiring. Sapia believes that relying on data to drive your most important decisions. Who you hire/ promote, enhances trust and confidence that decisions are fair. We also serve customers in the UK, South Africa, India Australia, and New Zealand.
To keep up to date on all things “Hiring with Ai” subscribe to our blog!
Finally, you can try out Sapia’s Chat Interview right now, or leave us your details to get a personalised demo.
There are some steps we can take to eliminate bias in recruitment and it begins with not relying on CVs as a method of evaluating candidates.
CVs are full of information that is irrelevant to assessing a person’s suitability to do a job. They instead highlight things that we often use to confirm our biases, and draw our attention from other key attributes or aptitudes that might make someone especially suitable for a job.
For example, if a CV mentions a certain university it might pique our attention (a form of pedigree bias). This is problematic, as there may be socio- economic reasons why someone attended a certain university (or did not attend another) and CVs do little to reveal this. Situations like this confirm the bias that lead to it in the first place, compounding bias for these long-term systemic issues.
Additionally, CV data reduces a candidate pool in a way that is not optimising for better fits for the role, by relying on the wrong input data and criteria to find a candidate. Amazon discovered this when it abandoned its machine learning based recruiting engine that used CV data when it was discovered the engine did not like women.
Automation has been key to Amazon’s dominance, so the company created an experimental hiring tool that used artificial intelligence to give job candidates scores ranging from one to five stars.
The issue was not the use of Ai, but rather its application. Amazon’s computer models were trained to vet applicants by observing patterns in resumes submitted to the company over a 10-year period. Most came from men, a reflection of male dominance across the tech industry. As a result of being fed predominantly male resumes, Amazon’s system taught itself that male candidates were preferable. It penalised resumes that included the word ‘women’ as in “women’s chess club captain.” It also downgraded graduates of all-women’s colleges.
Studies have shown systemic unintended bias occurs when reviewing resumes that are identical apart from names that signify a racial background or gender, or a signifier of LGBTQIA+ status. The solution for this has been to remove names or any identifiable data from an interview or CV screening, but these have still experienced bias issues like those discussed earlier.
In order to be truly blind, any input data needs to be clean and objective. This means that it gives no insight into someone’s age, gender, ethnicity, socio-economic standing, education, or even past professional experience.
To truly disrupt bias, recruiters and hiring managers should utilise a new wave of HR tech tools such as Sapia, stepping away from using CV data as a way to determine job suitability.
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Getting your organisation’s candidate experience right is proving to be something we’ll hear about increasingly. This is as job applicants demand more from companies they interact with. A recent poll on LinkedIn by a recruitment specialist attracted almost 80,000 views and 1000’s of reactions. It revealed that 52% of the people polled (one assumes mostly recruiters) believe that a template email is good enough as a response to an application for a job.
When it comes to recruitment, responding to candidates has always been an area we know has been ripe for improvement. And it costs companies too, with a bad candidate experience said to have cost Virgin $5 million.
That’s not to say there aren’t historical reasons why recruiters have not been able to respond to the hundreds of applicants received for a job. Until now it’s not been something we can practically do with limited time and resources. This is where AI plays a fundamental role in moving our industry forward as it allows mass personalisation at scale.
This has never been more important than right now as we have had mass job losses across industries due to the impact of COVID-19. If you look at the Hospitality and Tourism industry across the globe, it’s hard to wrap your head around the sheer number of job losses with very little hope of returning to normal soon. If with every job application we were able to give each unsuccessful candidate feedback on where they could improve, imagine the impact we could have in activating the world economy.
This is entirely possible and every day we hear about the impact our technology is having on people’s lives when they get personalised feedback designed to steer them in the right direction.
81% of people who get personalised feedback from our platform said it was useful in identifying their strengths, 71% said it would help them better prepare for interviews and 59% said it would help them find a job that suited them.
And lastly, it’s not something we can quantify, but we do believe it’s important. What we’re giving so many people right now is hope. We think that’s something worth companies cultivating alongside us too.
To keep up to date on all things “Hiring with Ai” subscribe to our blog!
Finally, you can try out Sapia’s Chat Interview right now, or leave us your details to get a personalised demo
Have you seen the 2020 Candidate Experience Playbook? Download it here.