Job-hopping algorithm: Assessing Job-Hopping Attitudes From Chat Interview

We have no survivable and sustainable future without science, just as we do not have you without it. 

Since the start of the coronavirus epidemic, many companies have turned to smart algorithms to find out who is the best candidate for open positions. Most often, face-finding programs, games, quizzes, and software that examines other visual or linguistic patterns are used to decide who is included in the interview circle.

An Australian company called Sapia (Formerly PredictiveHire), founded in October 2013, appears to have gone much further. It has developed a machine-learning algorithm to assess the likelihood of frequent job changes for a given candidate. –  MIT Technology Review. 

According to Barbara Hyman, CEO of HR, their clients are employers who have to process a lot of application. Also they are active in the areas of customer service, retail, sales or healthcare, among others.

In the first round, a chatbot decides on the applicants

When someone applies for a job through an HR company, they must first “convince” a chatbot of their values. The algorithm asks a series of open-ended questions and analyses personality traits such as initiative, intrinsic motivation, or resilience.

Moreover, the algorithm may examine the likelihood of frequent job changes in the future – or, as advertised on the Sapia website, the “ risk of escape ” – even for fully career candidates. The focus of the HR company’s latest study is to develop a machine learning algorithm that specifically seeks to predict this. The research examined 45,899 candidates. They had previously answered 5-7 open-ended questions about their experiences and situational awareness through the Sapia chatbot.

The chatbot asked for personality traits that, based on Sapia’s own research, may be closely related to frequent job changes. For example the traits could be -greater openness to new experiences or lack of practicality.

Algorithms against wage increases

Nathan Newman, an associate professor at John Jay College of Criminal Justice in New York who wrote a study in 2017 on how large-sample data analysis can be used to break wages in addition to discriminating against employees, told MIT Technology Review Recent work by Sapia.

This includes the increasingly popular personality tests based on machine learning, which seek to screen out potential workers who are more likely to support unionisation or are more likely to ask for wage increases. According to MIT Technology Review, employers are increasingly keeping an eye on their employees ’emails, online chats, and data they can use to filter out whether a particular colleague is about to leave. All this so they can calculate the minimum wage increase is and where appropriate, they may be allowed to remain.

Uber’s algorithm-based management systems are said to seek to keep employees away from offices and digital locations in a way that they can’t even accidentally organize and collectively demand better pay or treatment.

Sapia has found a relationship between the language people use and their attitudes towards job-hopping.

If a simple automated chat interview can infer a candidate’s likelihood of job-hopping, it presents significant opportunities, especially when assessing candidates with no prior work history.

This work shows that the language one uses when responding to interview questions related to situational judgment and past behaviour is predictive of their likelihood to job hop. This paper explores:

• Research around self-initiated job hopping
• Correlation between language and job-hopping likelihood
• NLP methods that can be used to represent language

Find out how you can identify job-hopping attitudes before you hire.  To get your copy of the Research Paper click here.

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Finally, you can try out Sapia’s Chat Interview right now, or leave us your details to get a personalised demo

Also, have you seen the 2020 Candidate Experience Playbook? Download it here.

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: Simpler, but not fairer

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.

The answer is in chat

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?

Transcript:

Kyle Lagunas:
You and I both know that adding more headcount will not help the issue [of recruiters being overworked], since it’ll just result in more people doing more tasks.

At one point, we had General Motors in a position where we were having quarterly go-to-market meetings every quarter.

As a leadership team, we met to determine what we wanted to achieve in the next quarter and what it would take to get there.

When I started running the go-to-market functions for my boss, Cyril George, I told him that no one here knew what their KPIs were because it wasn’t clear; it was like everything was on fire all the time.

So we began having these go-to-market meetings, and a significant portion of them focused on the tech and innovation that we were driving to resource the team.

Then someone asked, “What’s the point once we implement all of this?”

I knew the subtext was, “Are we laying people off? Are we getting rid of recruiters?”

I responded, “No, the point is for you not to be working 65 hours a week every week.”

The room fell silent; there was no slow clap, just disbelief and shock.

They thought, “I don’t think that’s real,” but it is.

That’s what tech can do, you know.

Not only can it help for one quarter, but it can also make a difference for years to come.

So, stop thinking of buying tech for new best practices that it can bring, and start thinking of it as a way to extend our capacity sustainably and meaningfully.

It’s critical.

Barb Hyman:
Yeah, I see it the same way, in terms of giving you leverage.

Every time you hire someone for your team, you gain more leverage, allowing you to achieve more.

Technology does the same thing, but on a larger scale.

Listen to the full episode of our podcast featuring Kyle Lagunas here: