Depending on which media you read, technology, and specifically Artificial Intelligence, will create or destroy thousands of jobs. It is already radically changing many, as well as how we apply and hire for them.
Back in the day when cars were first released, there was such a fear about the danger they presented to society, that when they came to a junction, they were required to stop the car, get out and fire a warning shot so that the people in the surrounding area would be safe from unexpected danger.
I was reminded of this when reading the commentary around Amazon and its use of AI to screen talent.
In case you missed it, Amazon did an experiment. They analysed 10 years of CV data to build a predictive model to help filter through what I am sure is hundreds of thousands of applications to work at the company. Because the sample group was mostly male, the CVs were naturally based towards male ‘traits’ if there is such a thing. The model built off this training data naturally ended up mirroring that sample group which meant it preferred male to female CVs.
It is pretty obvious to all of us that if you create a product off one homogenous group, then you will end up flavouring it with the characteristics of that group. YouTube found that when the team they used to build their iOS app didn’t consider left-handed users when it added in mobile uploads, causing videos recorded in a left-handed person’s view of the landscape to be upside down. I presume because the team building it was comprised of all right-handed people.
Suggested reading: A CV Tells You Nothing
While these biases help us not go insane, unfortunately, it has led us to the point today where they are having a very significant effect in the workforce. There are many serious forms of bias, but the best known is gender bias. A recent study showed simply by changing the name of an applicant from a woman’s to a man’s, with every other detail kept the same, the ‘male’ applicant was more likely to progress to an interview. The exact same CV.
When humans do screening, they are prone to making snap judgements based on superficialities, ignoring the very many factors that can help actually predict whether a candidate will perform. This is where data platforms actually have an advantage, by doing ‘blind screening’ and making the process both faster and fairer. However, this only works when the data that goes into the model manages for human frailties.
When it comes to using data to build predictive models to inform and guide decision-making, it is important to really dig deep on the input data.
And if you think unconscious bias training is the answer … read this first.
The key insight for this experiment for Amazon is that relying on CVs to assess talent, is inherently flawed. This is accentuated even more when you accept that what differentiates talent now and will become even more acute in the future is not hard skills, not what uni someone went to or degree they have, but soft skills. Jeff Weiner who has the benefit of this kind of rich data from 600m users attested to that this week.
At Sapia, working with dozens of companies across the world to help blind screen thousands of candidates, we know that it’s the behaviours and values of a potential coworker that will influence their performance and tenure. Values, such as commitment and attitudes are invisible in a CV. It’s not easy to see either in an interview. But it’s easily tested using well-crafted data platforms.
So let’s try to look beyond the news grab, the headline which naturally attracts attention when it has Amazon in the first line.
The algorithms we build aren’t sentient beings or unmanageable acts of nature, they are built by humans. When we recognise that and are conscious of those risks, we can start to counteract these biases through technology to help humans see what’s in front of us more clearly, without the filters of bias.
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Despite all the rhetoric, it seems that the world is becoming worse at removing bias from our workplaces, leveling the playing field for all employees, and improving diversity, equity, and inclusion.
COVID was tough for everyone, but the one good moment that seemed to come out of it was how people galvanized around the Black Lives Matter movement. Companies dedicated large advertising budgets to sophisticated promotional campaigns to convince us that they supported the movement.
At work, people demanded better from the companies they worked for. They demanded real and measurable progress on matters like diversity and inclusion, not just better benefits.
Employees weren’t going to accept the hypocrisy of their employer, a consumer brand spending millions on advertising about how woke they are when nothing changed internally. Bias was just not something that people were prepared to accept. It seemed like progress was being made, at least in the workplace.
Fast forward to 2023, and things have gotten worse than they were before the movement. What happened to push us so far backward on all the progress we’d made? The answer is video interviewing, specifically when it comes to amplifying bias in recruitment.
Video interviewing took off as a solution to the challenges of remote recruiting. However, video is a flawed way of assessing potential candidates as a first gate. It invites judgment, adds stress to the candidate, puts added pressure around hair and makeup, and turns a simple interview into a small theater production. Additionally, simply automating interviews with video doesn’t create any efficiencies for hiring teams, who are still watching hours and hours of interviews.
Video also excludes people who are not comfortable on camera, such as introverts, people with autism, and people of color. These factors do not influence a person’s ability to do a job, but using video at the start of the interview process puts them at a disadvantage. We are excluding a significant percentage of people by using video as a first gate.
We analyzed feedback comments from more than 2.3 million candidates across 47 countries using smart chat invented by Sapia.ai to apply for a role, and the overwhelming theme is that “it’s not stressful.”
As an industry, we must put a stop to this. Already, there is growing cynicism when companies talk about “improving candidate experience” because we like to say we care about something that will win us good PR, but we do little to hold ourselves accountable. We care more about optics than results.
However, you cannot say you care about candidates or diversity and inclusion and only use video platforms to recruit people. Frustratingly, there is technology that solves for remote work, improves the candidate experience, and truly reduces bias, and that is text chat.
Some of the most sought-after companies, like Automattic (the makers of WordPress), have been using it for years.
Chat is how we truly communicate asynchronously. It needs no acting, and we all know how to chat. Empowered by the right AI, text chat can be human and real. It can listen to everyone, it is blind, reduces bias, evens the playing field by giving everyone a fair go, and gives them all personalized feedback at scale.
It can harness the true power of language to understand the candidate’s personality, language skills, critical thinking, and much more.
Video should only ever be used as a secondary interaction, for candidates who are already engaged in the process and have been shortlisted. In that case, it does give hiring teams a chance to meet candidates, and candidates are more likely to be comfortable with video as they know they’ve progressed, and they’ve had a chance to present themselves in a lower pressure format already.
Why are we settling for video as a first interaction, when we can actually do more than make empty marketing promises to candidates? Why choose a solution that erodes all the hard gains we’ve made in diversity and inclusion?
Becoming, by Netflix tells the Michelle Obama story, and throughout the documentary, it is clear that other people’s stories resonate with her just as much as her story resonates with them. As inspiring as you would expect her to be, she spends much time mentoring and coaching young women, just by listening to them and sharing her story. Midway through the doco, as another young African American woman shares her self-doubt because she doesn’t have all the reference-able facts to open up the right doors, (the right college on her CV, the right GPA, etc. ). Michelle Obama says this:
Wow! That line just nailed it for us because your story of what makes you you. What shapes and motivates you is what matters not how you turn up to your education, to an interview, to your job.
It’s why so many organisations are investing in testing your softs skills, the real skills because hard skills can be learnt. Your openness to new ideas, ability to cope with change, humility to ask for help, are way more relevant than ‘your stats’ at any point in time. That means two things for HR: Finding technology that will help you understand the story and removing bias that gets in the way of being able to hear the story.
COVID-19 enforced WFH restrictions have created zoom fatigue. It’s a real thing.
Eight weeks and already we are so over video.
Text has been around for a decade. Ever heard of text fatigue? No, that’s because text is easy, it is fast (especially if you are a 16-year-old who texts in acronyms (our latest fav ‘POS’ (not point of sale but parent over shoulder)). It’s also safe. Safe for introverts, safe for people who might not feel comfortable on a video call or even worse a video interview.
Forcing your applicants to invest in impression management is not a good start to building a relationship of trust and authenticity with your newest employee. How many great introverts, deep-thinkers and high-integrity individuals are you at risk of losing when you force people to perform on a video interview?
And why would you make people play a game, answer 150 +multi choice questions, (many repetitive that gives your experience no platform at all), when you can make it easy and comfortable with a chat or text interview?
Doing it by text gives everyone a chance to shine, without performance anxiety, without having to prepare or risk someone gaming it by googling the right answer. When you connect with people about them, using technology they trust, that lets them be themselves (without bias getting in the way). That is what a candidate first experience looks like. It’s why we get 99% + candidate satisfaction from 10,000 applicants a month.
It’s an understatement to say that recruiters and talent acquisition managers have had it tough over the last four-odd years. The pressures have compounded like a line of falling dominoes: First it was the COVID-19 pandemic; then came the mass talent migration; then the advent of new concepts like ‘quiet quitting’ and ‘acting your wage’, which, like them or not, seem to be the manifestations of a tired and existentially anxious workforce.
Now, in 2023, it’s likely that we’ll have to contend with a global recession.
Hiring is tougher. Candidates are wary and they expect more. Duh.
So do companies and their CEOs. However – and somewhat counter-productively – many companies have sought to cut recruitment budgets, lay off recruiters and talent acquisition managers en masse, and deprioritize long-term recruitment marketing strategies. We’re facing troubled times, and recruitment (and perhaps HR, more generally) is being treated as a cost center.
This misunderstanding of HR as a money sink is nothing new. It happens during every trough in the market. But, if we don’t make efforts to change this perception, 2023 will be a particularly painful valley to climb out of.
CEOs have been keen on talent strategy for years, but are struggling to quantify the effects of recruitment and talent acquisition activities. They cannot see the A to B journey, the action and its result. When the market is good, talent is in abundance, and you’re hiring effectively, nobody cares. But when times are hard, nebulous processes are put under harsh light.
Relatedly, recruitment and talent acquisition leaders are struggling to prove that the outcomes of their work are driving revenue. This is primarily an issue of data capture and analysis, in our experience: When companies come to us to help with hiring quality talent, the number one issue they have is to do with metrics and KPIs. Most do not know how to reliably measure quality of hire, nor time-to-hire, nor the effectiveness of their recruitment marketing channels. Many know that their processes are plagued with inefficiencies, but are not sure how to go about fixing them.
(To be clear, totally understandable. This stuff is hard.)
Where recruitment is concerned, a HR tech stack tends to look like this: an unwieldy ATS, often coupled with a conversational AI or scheduling tool.
These technologies cost big money. As a result, the question CFOs and CEOs will be constantly asking of HR is this: Is it adding real value? Can you prove it? Or are we simply stuck to a system that tackles old problems with insufficient solutions?
The bottom line is this: Enterprise companies are overstacked, overworked, and need to adopt different solutions to old problems. It doesn’t mean less tech, necessarily, although it can; it means the right tech.
Easier, perhaps, than it sounds. It’s always better to iterate than to completely restructure your hiring function. So get your team together and examine your processes. How much time is spent:
Ideally, you have baseline data in your ATS to help you arrive at some indicative numbers. But let’s assume that you don’t: calculating rough person-hours is enough to see where time may be spent more effectively.
In our experience, sourcing and screening are the stages in which quick wins might be gotten. As time-honored research (and our Smart Interviewer product) shows, resumes and cover letters are not useful indicators of candidate quality or potential. They can be easily falsified. What’s more, Sapia and Aptitude research from 2022 discovered that 22% of candidates drop out at the application stage and 24% at the screening stage.
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.
Interviews are another huge cause of inefficiency. Structured interviews are the best explainer (at 26%) of an employee’s performance, but many companies allow recruiters and hiring managers to conduct interviews haphazardly, causing a misidentification and loss of talent that can be hard (if not impossible) to measure. If you’re interviewing badly, how can you know if you’re capable of finding good candidates? What’s the associated cost of such a problem?
It’s no surprise, then, that according to our research, 50% of companies say they’ve lost talent due to the way they interview. Big costs involved there.
Don’t worry: We’re not going to lay out a massive and exhaustive list of metrics you should be tracking. Not feasible; you’re overworked as it is.
Instead, we’ll prescribe three good places to start, including links to helpful blog posts explaining how you measure them effectively:
Each of these metrics can help you improve efficiencies, and in turn, start to prove that your recruitment function is having a positive effect on business outcomes.
At a certain point, we must realize that force-multiplying technology is the only way to win in the unfolding ‘now’ of work. We’re spending way too much time with processes that can be repeated and automated – often out of some sense of duty to uphold 1:1 human connection (as if technology completely removes that, which it doesn’t).
And, because we do this, we weaken our position at an executive level: CEOs care about what is scalable, and the average recruitment function, traditionally speaking, does not.
In a recent episode of our Pink Squirrels! podcast, Sapia CEO and founder Barb Hyman had a chat with expert HR change management leader, Kyle Lagunas, about this very topic.
We exist to help you hire better, faster, and with fewer headaches. Our Smart Interviewer takes care of the scheduling, interviewing, and assessment stages of your process – saving upwards of 2,000 recruitment hours (av.) per month, and enabling you to offer jobs to candidates within 24 hours of application.
It’s delivered in a chat-based format (hello, Gen Z!), and candidate responses are assessed according to science-backed personality models. This means you can be sure you’re getting top talent, and you can prove it with measurable, repeatable data.
That’s not all: Our tech is blind, which means it natively disrupts bias and maximizes the size of your talent pool. Everyone gets an interview, and everyone gets personalized coaching tips whether or not they get the job. Our application completion rate, for all customers, sits at around 85% on average; our candidate satisfaction rate is well over 90%!
(And, if you need a second stage interview, you can use our Video Interview tool.)
Everything you do with our platform is pulled through to comprehensive data dashboards, allowing you to see hiring efficiency, quality, time, diversity, and other metrics. CEOs love this kind of transparency.
There you go: 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.