It’s a fact: People lie on resumés, whether the format is a LinkedIn profile, or an old-fashioned document.
Checkster reports that 78% people who applied for a job in 2020 lied about their skills or experience.
Another poll by LendEDU found that 34% of LinkedIn users lie, to some extent, on their profiles. Of that number, 55% said they padded out their ‘Skills’ section. To win roles, it seems, many of us are not above a little trickery.
In 2023, when talent acquisition specialists and hiring managers have hours (and sometimes less) to assess candidates, interview them, and woo them, the risk of resumé skill-creep is magnified.
For a rushed and overworked hiring manager, who is fed up with losing talent and looking bad because of it, the process of vetting becomes less about careful analysis and more about keyword-matching.
All of this culminates in a series of statistics that should not be surprising: According to a 2022 Aptitude Research report of more than 300 HR leaders at major companies, 50% of companies have lost quality talent due to the way they interview and hire.
At the same time, 50% of companies do not measure the ROI of their interview process. One third are not confident in their interviewing game as a whole.
The process is broken.
That same Aptitude Research report examined the average company recruitment funnel, laying out the points at which candidates typically drop out. It found that, on average:
So you might be losing anywhere from 20 to 40% of your talent pool while you spend time vetting resumés and sifting through cover letters.
Aside from the fact that this is a massive time-waster and a prime source of frustration of hiring managers, enforcing the use of resumés is not an effective way to ensure quality of hire.
That’s for two reasons:
Therefore, our over-reliance on resumés creates problems when we go to interview candidates. It’s a classic problem: Overworked hiring managers formulate questions on-the-fly after making cursory glances at candidate submissions.
It’s little wonder that 25% of candidates bail at this point – often, they’re just reconfirming information they’ve already told you about who they are and what they’ve done.
There is an alternative: Structured interviews. Schmidt and Hunter found that structured interviews are the best predictor (26%) of on-the-job success.
The biggest companies are starting to focus more on this.
According to the Wall Street Journal, employers like Google, Delta and IBM are combatting the tight labor market by easing strict needs for college degrees, focussing instead on interview and assessment processes that accurately measure soft skills and behavioral traits.
In its simplest form, the structured interview is based around a predefined set of questions.
These questions are typically behavioural and situational in nature: It’s about giving candidates the opportunity to explore how they think, solve problems, formulate plans, and deal with success and failure.
Therefore, questions like ‘Tell me how you’d respond if [specific situation] occurred’ don’t belong in a structured interview.
Instead, you might ask, ‘Tell me about when something went wrong with work, and you had to fix it. How did you go about it?’
Importantly, the questions you ask must be the same for all candidates. A critical component of the structured interview is fair and balanced comparison of candidates.
If you ask each candidate something different – as so often happens in a fast-paced hourly hiring setup – you can never accurately compare one candidate against another.
In that uncertainty, bias creeps in. It becomes a case of ‘I like this guy, he leans forward when he speaks.’
We’ve developed a handy tool to help you get started with structured interviews today: Our HEXACO job interview rubric. It comes with step-by-step instructions to help you figure out what skills and traits you need based on your open roles and company values.
From there, we’ve supplied you with more than 20 science-backed questions and a scorecard. It’s something simple enough for a busy hiring manager to use.
There is a possible world in which the resumé serves hiring managers as a kind of back-up validation document, used purely to verify the veracity of a candidate’s skills and experience.
In this world, the first stage of your recruitment funnel is the actual candidate interview.
That’s what our Ai Smart Interviewer can do. It’s a conversational Ai that takes candidates through a chat-based interview, using questions tailored to your open roles.
Candidates give their responses – with plenty of time to think – and Smart Interviewer analyses their word choices and sentence structures using its machine learning brainpower.
A candidate may be able to lie about their years of experience, or their knowledge of CSS, but our Smart Interviewer can accurately determine their cognitive ability, language proficiency, and personality traits.
Then it can make recommendations to you on the best candidates, according to the criteria you’ve set – and, at this point, you haven’t even looked at a single resumé.
But, as with traditional processes, you have the final say in who you hire.
In 2023, the name of the game is efficiency. Success will be measured in time saved NOT having to screen, review resumes and cover letters, compile candidate feedback, communicate with candidates, or improve hiring manager interview techniques.
When you’re saving that much time and money, your recruitment (or HR) function has more bandwidth to focus on long-term talent acquisition and people initiatives.
Don’t struggle in 2023 – speak to our team today about how we can solve your hiring challenges.
Right now video screening is the solution of choice for many, given the challenges of recruiting during the pandemic. Every day I’m asked about video solutions, and every week there seems to be a new video solution for hiring.
This isn’t people simply switching to Zoom, but rather embracing AI video platforms where you are judged by algorithms. Often algorithms crawl these videos to identify top candidates. This is not great. In fact, it’s horrifying. Not all video interviews are bad, given the pandemic it’s often become a necessity as a default for face-to-face interviews in the final stages of a recruitment process. But when it comes to top-of-the-funnel screening with first interviews, video interviews lead to biased outcomes.
Put simply, image and video recognition is built to favour white faces. In the documentary Coded Bias an M.I.T. Media Lab researcher Joy Buolamwini found that the algorithm couldn’t detect her face–until she put on a white mask. There are hundreds of validated research findings which confirm this.
Video invites judgement. It adds stress to the candidate with added pressure around hair and makeup, picking the right fake backdrop (yes, there are hundreds of advice columns on this), and practising and rehearsing your answers until you nail the recording. It turns a simple interview into a small theatre production.
Not everyone is comfortable on video, most especially introverts, people with autism, and people who feel marginalised. These factors do not influence or speak to a person’s ability to do a job, but by using video as part of the interview process they are put at a deep disadvantage. What percentage of people are you excluding just by using video?
Chat is a better option. It solves the challenges of remote interviews while being inclusive.
Try it for yourself, we’ll send you real results.
Transcript (Maura van As):
Hi everyone. I’m Maura van As, Head of Customer Success at Sapia, and today, I wanted to talk to you about our human in the loop approach. So when we talk about ethical AI at Sapia, we always put our human in the loop approach front and center, and especially in the natural language processing industry that we operate in today with tools like ChatGPT really changing the name of the game and it coming under increased scrutiny, we are confident that the human in the loop approach is more important than ever. And also something that we’re super proud of.
A human in the loop approach allows us to get this perfect intersection where we’re combining human and machine intelligence and we’re creating smart chat experiences that are predictive, but also responsible and personalized. Ultimately, my customer success team is incredible at building definitions of success. They spend a lot of time and energy and effort building custom algorithms that are models, if you will, of success in roles across organizations, across industries, all over the world.
And ultimately, our secret weapon in building those models is a human touch, which speaks to the irony of how even the most advanced technologies requires the human touch, human judgment, human oversight. We can’t live without that. And our human touch is actually our clients. So we bring our client experts to the table. Really, the rule of thumb with machine learning is what you put into it is what you get out of it. And our client experts are the owners of success, performance, of culture, of future proofing talent in our organizations. So we give them a seat at the table to make sure that we create and build with them so that we feel confident we’re teaching our AI what matters most, and we are continuing to teach it. We are continuing to evolve it, iterate on it, and retrain it.
And that makes us feel confident that our AI is accurate but also appropriate, and that we’re creating natural experiences for users that feel human and feel real. And it also speaks to the way that we partner. We set a real sense of joint accountability in our partnerships around validating and governing these models over time. So we constantly validate for accuracy, for fairness, and we retrain and teach our models to evolve in time. So really, this is a shout-out to our clients. You are the human in the loop for us. You bridge the gaps that AI can’t on its own. You make sure that we build responsible models and you are pioneers in building ethical AI with us in market every single day. So thank you.
It’s not every day or every job where you get to say you are changing the way the world works.
For 2+ years, the small team of incredibly dedicated data scientists led by the incredibly humble Buddhi Jayatilleke have tested and re-tested and experimented and re-experimented to find a new formula for assessing talent – one that is 100% inclusive and bias-free, but also human, using the combination of AI, machine learning and advances in NLP.
Apart from reading daily the thousands of comments of gratitude we receive from candidates for this new formula, which is globally unique! it is wonderful to see that team receive the industry acknowledgement at a global level.
Last week, at a Virtual CogX, the world’s largest Festival of AI and Emerging Technology, with top CEOs, Scientists, Technologists, Data Scientists in attendance, with over 30,000+ attendees from hundreds of countries, 6500 world leaders and 650 presenters across 17 forums, this team were awarded Top 3 For Best AI in HR technology.
For a team that has been tackling this problem for such a small amount of time, with limited resources but endless tenacity and commitment, we couldn’t be prouder to get to work with them every day.
The PredictiveHire Data Science Team:
Buddhi Jayatilleke
Chenxu Zhao
Johnny Yin
Madhura Jayaratne
Michael Zhang
Are you interested in using an award-winning solution in your business to recruit faster, better, fairer? Let’s chat