Job-hopping algorithm: Assessing Job-Hopping Attitudes From Chat Interview Using HR Algorithms
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 advanced HR algorithms to find out who is the best candidate for open positions. Most often, HR algorithms utilize face-finding programs, games, quizzes, and software that examines visual or linguistic patterns to decide who gets an interview.
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 rely heavily on HR algorithms to sift through vast applications. These employers mainly operate in customer service, retail, sales, or healthcare sectors, among others. They consider the potential “how often change jobs” metric crucial when hiring.
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, which is an embodiment of these advanced HR algorithms, of their worthiness. The HR algorithm poses open-ended questions and subsequently analyzes personality traits like initiative, intrinsic motivation, or resilience.
Importantly, this HR algorithm also gauges the frequency of how often the candidate might change jobs in the future, a metric highlighted as the “risk of escape” on the Sapia website. The primary aim of the HR company’s recent study was to refine their HR algorithm to predict this trait accurately. They assessed 45,899 candidates who previously responded to 5-7 open-ended questions about their experiences and situational awareness through the Sapia chatbot.
The chatbot, using insights from HR algorithms, probed for personality traits that Sapia’s research indicates might correlate with how often someone changes jobs. Traits like a heightened openness to new experiences or a perceived lack of practicality were among them.
Algorithms against wage increases
Nathan Newman, an associate professor at John Jay College of Criminal Justice in New York, who penned a 2017 study on data analysis’s potential pitfalls, highlighted the recent work by Sapia to MIT Technology Review.
This encompasses the increasingly favored personality tests rooted in machine learning. These HR algorithms aim to filter out potential workers more likely to support unionization or ask for wage hikes. MIT Technology Review noted that employers, armed with HR algorithms, are keenly monitoring employee communications, like emails or online chats. They harness this data to deduce if a colleague might be on the verge of quitting. This intel aids them in determining the bare minimum wage hike they could offer to retain said employee.
Uber’s management systems, driven by HR algorithms, reportedly strive to ensure employees remain disconnected from physical offices and digital forums. This strategy ensures they can’t unintentionally unite and collectively demand improved pay or conditions.
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.
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
Also, have you seen the 2020 Candidate Experience Playbook? Download it here.
About Author
