PredictiveHire has recently released a scientific research paper that shows that a simple chat interview can measure personality with improved user experience and at a fraction of the time required for a traditional psychometric assessment.
It proves that textual content of answers to standard interview questions related to past behaviour and situational judgement can be used to reliably infer personality traits. It explores how the AI techniques of Natural Language Processing (NLP) and Machine Learning (ML) present a new future for personality assessments.
Why this matters?
Personality is widely accepted as an indicator of job performance, job satisfaction and tenure intention.
The research outcomes suggest that the work is more enjoyable and thus engaging to the individual and beneficial to the employer and the society at large when there is congruence between one’s personality and career.
However, conducting a traditional personality test adds an extra cost to the recruitment process. It also tends to diminish candidate experience as personality tests are less favoured by candidates compared to other assessment methods such as job interviews.
Therefore personality tests are not as ubiquitous as employment interviews. Actually, for the past 100 years, interviews are the most widely used selection method in. However, strong criticism of the job interview is the likelihood of bias introduced by the prejudices of the interviewer.
Structured interviews where the same questions are asked from every candidate, in a controlled conversation flow and evaluated using a well-defined rubric have shown to reduce bias and also increase the ability to predict future job performance. The questions asked in a structured interview are derived using a job analysis as opposed to interviewer preference and are typically based on past behaviour and situational judgement.
This research paper is written by Madhura Jayaratne, Data Scientist and Buddhi Jayatilleke, Principle Data Scientist of PredictiveHire.
The ability to infer personality from interview responses could replace lengthy and less favoured personality tests while also providing objective outcomes from text interviews.
Transcript:
Barb Hyman:
I am seeing organizations increasingly rely on AI that comes from social media or resume data. How do you see that? Does that bother you? Do you think we need to educate the market about the difference between first-party and third-party data and ask questions about how clean and unbiased the data is?
As a former HR leader, I couldn’t use technology that analyzes my candidate pool or my people based on what they do on social media. It horrifies me, and it kills trust. I feel like that kills trust, you know, because I’m on social media in my own personal way. What do you think about that trend, and how can we tackle it?
Meahan Callaghan:
I think we need to educate people at the point of recruitment. We could let them know why they should feel safe using AI-based technology and that it doesn’t use third-party data or do anything unethical.
If we provide warnings and information, people will start to look for trustworthy AI. Remember how banks got everyone to feel safe about transferring money online? We need an education piece on how this AI is different from that one.
Imagine if we said, “Before you’re about to go through AI-based technology for this recruitment process, we’re going to let you know why you should feel safe in doing so. It doesn’t use third-party data, it doesn’t do anything unethical.”
Again, take internet banking: How did the banks get everyone to feel OK about transferring money online?
I mean, all of us used to go and check the money even got there, and you know, there’s some people that still don’t use it today. I’ve got a friend with a fantastic organic beauty products business. Another one who’s got a collagen business. Both are constantly having to say, “We look the same as other products – but let me tell you how we’re not.”
And I think there is an education piece on, let me tell you how we’re not.
Barb Hyman:
I love that you’ve taken the candidate’s view on that. We need to protect them and our brand, and trust is crucial. We shouldn’t blindly trust AI; we should be able to trust it because it’s safe to do so. That’s a great call to action for all of us in that space.
Listen to the full episode of our podcast with Meahan Callaghan, CHRO of Redbubble, here:
How did you deal with a change in your life?
What motivates you?
Are you able to share a valuable lesson you’ve learnt from a prior colleague?
They sound like the questions you’d ordinarily get asked in a job interview – except this particular interview is being conducted by a hiring bot. Welcome to the new world of job interviews, where robots are the ones doing the hiring.
On average, job seekers are having to apply for 20 to 25 jobs before securing employment, said Trini Nixon, regional director of talent management at recruiter Hudson.
She said AI was growing in popularity as a recruitment tool, being a much faster and more efficient way to screen applicants.
“That in itself creates a more positive and engaging experience for applicants when they’re able to get responses at each milestone. AI can also help candidates put their best foot forward, according to Sam Zheng, CEO of conversational AI start-up Curious Thing.
“This is because a recruiter may not have time to talk to everybody but an AI does,” he said.
AI can be used to discover many things about applicants. Such as their fit for the role, their personality, their communication skills and their tendency to move around jobs.
– Barb Hyman, chief executive of Sapia, a Melbourne-based tech firm that uses AI to filter job applicants.
In the wake of COVID-19, Sapia (Formerly PredictiveHire) has launched a new function that lets job seekers be interviewed by text message.
Candidates answer a series of questions by text, with their responses analysed by AI, and then get personalised feedback.
“I know it’s hard to believe, but what we can learn from 200 words is a hell of a lot. That’s because it’s about the questions you ask. You have to ask questions which really get to you and your experience – what we call behavioural questions,” Ms Hyman said.
Ms Hyman said chat-based interviews addressed some of the big failures of current assessments of young people: ghosting (not hearing back about job applications), bias and trust.
“In all of these roles it doesn’t matter what you look like. What matters is your traits or your behaviours, are you someone I can rely on, do you get on with people,” she said.
Ms Nixon said although AI did reduce bias, it was important to remember it was built off algorithms.
“We need to make AI continually learn from those mistakes and get smarter and smarter. Otherwise we’re working on an algorithm that’s not correct and that I think has perils that we need to be really conscious of,” she said.
Ms Hyman said feedback from candidates showed they found chat-based interviews much more comfortable than other styles of interviews.
When applying for a job where AI is involved, Ms Hyman gives the same advice as she would for an in-person interview.
“Be yourself,” she said. “If you try and game the system, the system will find you out.
“In our case, we can identify when someone has plagiarised. We can identify profanity, we know the top sites graduates use to source answers and we can reveal that to our customers.”
Mr Zheng agreed applicants should not try to game the system.
“Every AI runs with different algorithms and a method like this might ultimately penalise you,” he said.
“For example, at Curious Thing, our AI will notice if a candidate is piling on keywords. That is when they aren’t connected into a well-structured and coherent answer. The best results will come from you being authentic.
Mr Zheng said it was important for applicants to remember AI was essentially information collection tools designed to analyse provided information.
If done effectively, interviews are a great means of assessing a candidate. We trust them to enable us to determine if our candidates have the attributes, traits, behaviours, skills, experience and personality to meet the role requirements.
Here’s the problem. It is physically impossible to interview every candidate. So, we rely on CV screening as the first step. A recruiter on average spends six seconds looking at the resume. In six seconds, a snap judgement is made on shortcuts (biases).
At the starting block, the process has failed. You cannot possibly pick qualities like grit and initiative from a CV, right? Then, of the people who applied for the job, around 13% of applicants may get an interview. During C-19 times – you can more than half that number.
In this way, you realise the value of interviews without investing one-minute of your time in them.
Imagine this. Everyone has already been interviewed before you have read one CV. A pre-qualified, pre-assessed, high-quality shortlist before you have read ONE CV. That’s the dream! Because now you are not wasting time reading resumes of people who either can’t do the job, won’t do the job, or they just don’t fit. And, instead of flicking through 100 resumes for a puny 6 seconds each, you can take the space to consider the best. The best? Those candidates who have already been pre-selected for that grit and initiative you so badly want in your team.
You can try out Sapia’s FirstInterview experience here.
Time to hire measures recruiting efficiency. It is the number of days between the first contact with a candidate to the day the candidate accepts the offer. Screening is your first time-to-hire bottleneck.
Even if you’re using an ATS you may be able to easily rank resumes, but you still have to consider them. And there’s your block.
A new generation of interview automation is here so that you can have every candidate interviewed in a flash. Of course, it integrates and works seamlessly within your ATS. It saves recruiters from screening resumes and boosts the efficiency of your recruiting process.
Reducing time to hire is great for candidates who get the job faster (or can move onto the next job). It is terrific for recruiters who get the reward of quicker placements and attaining their metrics. It is a relief for hiring managers who get their team to a full complement and can get back to their actual job.
Interviewing automation makes your recruiting process much faster – usually around 90% faster.
Hiring managers want their best team. They want people who can do the job, who will do the job and who will perform. With interview automation, Ai assesses traits, communication skills, optimism and temperament prior to you getting involved.
As a Recruiter, you get a complete picture of a candidate beyond what is written on their CV. You learn a lot of information about the candidate. Ai will rank and grade all your candidates for you. It pre-qualifies those who are a fit to move forward.
Have you ever thought to yourself: “If only I could hire 10 more Julie’s!” (*insert name)? With Ai, you can. And, as far as quality goes, this is the distinction from all other forms of pre-employment.
AI learns what a successful hire looks like and pin-points more like them. AI bases this learning on your historical recruiting decisions and then applies that knowledge to new candidates to automatically screen, grade, and rank them.
Interviewing automation gets you to the best of your talent pool much quicker resulting in, on aggregate, much better quality in your hires.
Diversity and Inclusion have been on the HR agenda for a long time. And in more recent years, it’s made its way onto the Business agenda too. In 2020, global management consulting company McKinsey again confirmed that companies with both ethnic and cultural diversity and gender diversity in corporate leadership are outperforming non-diverse companies on profitability. They found: “The most diverse companies are now more likely than ever to outperform non-diverse companies on profitability”
Diversity improves employee productivity, retention and happiness. Settled then. We want businesses that are diverse and fair.
Here’s the King of Recruiter biases: The Dunning-Kruger Effect. It’s where we lack the self-awareness to accurately assess our own skills meaning that we overestimate our ability. You think you are a brilliant totally unbiased Recruiter, right? You may well be, but it’s not uncommon to think you’re smarter or better than the average person. Haven’t we all skipped over candidates who don’t have the requisite ‘Big 4’ employer on their resume, or the ‘right kind of degree’?
Even when we don’t mean to be, human bias is pervasive. We keep these biases alive, through our relentless refusal to admit our shortfalls. And unfortunately, this isn’t great when it comes to hiring for diversity.
The reason for this is you can test, adjust and get rid of biases. The good news is Ai doesn’t resist stubbornly while claiming absolute fairness and denying any bias. This means that undesirable machine learning biases will tend to decrease over time. In Sapia’s case, its blind screening at its best. Nothing that typically influences human bias is introduced into the algorithms – no CV’s, no socials, no videos, no facial recognition – it’s just the candidate and their text answers. Much fairer for candidates of course and a richer experience where they can just be themselves.
Interviewing automation makes your recruiting process much fairer and your hiring decisions far more diverse.
Your ability to hire cost-effectively will be hampered if you don’t have the right tools. Make sure that all your recruitment technology is pulling in the same direction – to make hiring as seamless, streamlined and stress-free as possible – rather than working against you. The money you invest in the right technology will soon pay off when it comes to time and efficiency savings.
Significant costs are borne by an organisation when an employee voluntarily leaves.
These include replacement costs such as costs associated with advertising, screening and selecting a new candidate. A study conducted by the Australian HR Institute in (AHRI) 2018 across all major industry sectors in Australia (Begley & Dunne, 2018) found that on average companies face an annual turnover rate of 18%. Within the age group of 18 to 35 it worsens significantly, at 37%. That is, more than 1 in 3 people in the youngest age group leave an organisation within a year.
Imagine if you could predict those with a likelihood of churning before you had met them? Then think about the enormous savings that would be derived across your organization if you could do so.
If you haven’t yet automated your interviews, you are spending too much on hiring.
Chances are that reading CV’s and running interviews are not the hardest part of your job but are the most time-consuming. What if you could have available time for those high-value tasks. Like managing your stakeholders. Getting to know the business better. Improving your business partnership skills. Learning the essence of what Hiring Managers actually want. Networking and improving talent pools, particularly for those hard-to-fill roles.
So, if interview automation can take care of all of your first interviews for you then ask yourself:
Of how much value am I when buried knee-deep in screening? Visualise less of that and more of the buzz you get when you find the perfect fit. There’s no better feeling than knowing you’ve helped someone further their career AND helped your Hiring Manager find someone who ‘just fits’ and will perform. Nothing can replace the collaboration and empathy that you as a live person can extend.
According to this Sapia research paper published by IEEE: Structured interviews (where the same questions are asked from every candidate, in a controlled conversation flow and evaluated using a well-defined rubric) have not only shown to reduce bias but also increase the ability to predict future job performance. With interview automation, the questions asked in a structured interview are derived using a job analysis as opposed to interviewer preference and are typically based on past behaviour and situational judgement.
Interviewing automation frees up recruiter’s time to perform higher-value tasks with far greater output.
With interview automation you can move from an elongated process that leaves candidates in the dark, not knowing where they stand, to a super-efficient experience that feels empowering.
According to the Society for Human Resource Management (SHRM), 82% of candidates report the ideal recruiter interaction is a mix of innovative technology and personal, human interaction.
Improving your candidate experience is so much easier by adopting technology that is inclusive, personalised and relatable. Sapia’s interview automation offers a mobile-first, chat interview that interviews everyone in-depth and at scale. Giving every candidate personalised feedback.
Here is what interview automation offers above a manual interview process for candidates:
Interviewing automation enhances candidate experience, with no further time investment from you.
Download the 2020 Candidate Experience Playbook here
Gartner predicts by 2021, 50% of enterprises will spend greater budget on chatbot creation and bots than traditional mobile app development.
Businesses are adopting Sapia’s chat interviews across various job families – especially in front-line customer service roles. The quickest payback you will get on an investment in interview automation is to apply it to your high-volume roles first. Interview automation can truly enhance your high-volume recruitment process and help you make it more efficient (and pleasant) for everyone involved. This will help you get your time-back really quickly and release the budget for automation in other areas of recruiting.
The future of all first interactions between candidates and your business will be through automation. The only decision, for now, is where you will adopt interview automation first.
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