We know that the global pandemic has caused a disruption in global workforces. Much has already been said about the Great Resignation, and how it has morphed into the Great Reshuffle, a period in which many are looking to reinvent themselves in the light of new jobs and careers. No industries or role types have been spared, either, it seems – even recruiters are leaving positions in the tens of thousands.
With a reshuffle, however, comes uncertainty, doubt, and anxiety. The war on talent may have benefited some, but the path to career reinvention is by no means guaranteed. Consider the following factors, factors job-hunters must face every day:
- Bias in recruitment. According to a recent survey, 65% of tech recruiters believe their hiring process is biased. You may not get a fair shake, and you may not ever know why.
- Ghosting. According to CandE research, In 2020, 33% of candidates in North America who completed job applications had still not received a response more than two months later.
- Unfair competition. 78% of people admit to misrepresenting themselves on their resume.
- Threats to longevity and progression. According to Harvard Business Review, almost two thirds of the tasks that a manager currently does may be automated by as soon as 2025.
- Changes to the very nature of work. Noted future-of-work columnist Dror Poleg said it best: “It is not just where or when we work that is changing; it is the nature of work itself. For a growing number of people, work is becoming indistinguishable from leisure. In some cases, the workers don’t even know they are working. In others, workers think they are working while they are, in fact, resting. In the emerging world of work, video gamers are getting paid to play games, and fans are paid to listen to music.”
It’s little wonder that some Great Reshufflers, especially emerging adults (ages 18-24), are experiencing anxiety about working in the post-COVID world. Instability is the only constant. Consider, too, that some people are better at dealing with uncertainty – or, in technical terms, they are higher-than-average in the HEXACO personality traits Flexibility (or Adaptability, as it’s sometimes known).
This hypothesis is supported by at least one study, published last year in the International Journal of Social Psychiatry. It suggested that, “…due to the outbreak of ‘Fear of COVID-19’, people are becoming depressed and anxious about their future career, which is creating a long-term negative effect on human psychology.”
How this translates to good (or not-so-good) candidate experience
The traditional face-to-face interview is typified by stilted small talk and a general air of nervousness. If a candidate is low in Extraversion, high in Agreeableness, or high in the Anxiety and Fearfulness scales of the Emotionality personality domain, their experience of walking into a blind interview is likely to be worsened by the additional stressors left by COVID-19.
Consider, as is likely to be the case, that the candidate might possess a combination of all three traits, in the proportions laid out above. These people, especially if they are young, may not even bother to apply for a job in today’s climate.
The ramifications of this are obvious: You risk, at best, filling your workforce with open, disagreeable, type-A employees. At worst, you risk baking unfairnesses or bias into your recruitment process, at the cost of good candidates who don’t shine in awkward face-to-face situations.
How good candidate experience data, and talent analytics, can help you ease gender biases at the top of your hiring funnel
Take this small data visualisation from our TalentInsights dashboard as a key example. Please note here that the following results apply to the outcomes of the hiring process, and not Smart Interviewer’s recommendations.
It presents an assessment of candidate hiring outcomes according to key HEXACO personality traits. The red dots represent female candidates, the blue dots male. Immediately, we can see that when it comes to Conscientiousness – one of the best predictors of workplace success – females and males are more or less identical.
The main differences between the two genders occur, however, in the domains of Agreeableness and Emotionality. Combined, these two traits are good predictors of anxiety and/or aversion to fear. As you can see, females tend to be higher in Agreeableness and Emotionality than males.
Though the difference is not incredibly significant, it is still present – and it may require a slight change to the way you bring female candidates into your hiring process. The data proves, of course, that your best candidates are just as likely to be female as male – but your recruitment tactics may be producing outcomes that favour males.
How to account for fear, anxiety, and Agreeableness in your recruitment process
We’ve said it before, and it’s the whole reason we exist: A blind, text-based Chat Interview with a clever, machine-learning Ai. Smart Interviewer is our smart interviewer, and it has now analysed more than 500 million candidate words to arrive at the kinds of data points you see above. It helps you combat bias at the top of your funnel, and gives you the Talent Analytics you need at the bottom.
And it works. Take it from the candidates high in Agreeableness:
“I have never had an interview like this online in my life… able to speak without fear or judgement. The feedback is also great to reflect on. I feel this is a great way to interview people as it helps an individual to be themselves and at the same time the responses back to me are written with a good sense of understanding and compassion also. I don’t know if it is a human or a robot answering me, but if it is a robot then technology is quite amazing.”
– Graduate Candidate A
“[It was] approachable, rather than daunting. I found the process to be comprehensive and easy to complete. I also enjoyed that the range of questions were different than those commonly asked. The visual aspects of the survey makes the task seem approachable rather than daunting and thus easier to complete.”
– Graduate Candidate B
The future of work is uncertain. But with a fair and unbiased assessment tool, you can prevent the best talent from being lost under the dust of the Great Reshuffle – and save a lot of time and money doing it.
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Sapia.ai Wrapped 2024
It’s been a year of Big Moves at Sapia.ai. From welcoming groundbreaking brands to achieving incredible milestones in our product innovation and scale, we’re pushing the boundaries of what’s possible in hiring.
And we’re just getting started 🚀
Take a look at the highlights of 2024
All-in-one hiring platform
This year, with the addition of Live Interview, we’re proud to say our platform now covers screening, assessing and scheduling.
It’s an all-in-one volume hiring platform that enables our customers to deliver a world-leading experience from application through to offer.
Supercharging hiring efficiency
Every 15 seconds, a candidate is interviewed with Sapia.ai.
This year, we’ve saved hiring managers and recruiters hours of precious time that can now be used for higher-value tasks.
Giving candidates the best experience
Our platform allows candidates to be their best selves, so our customers can find the people that truly belong with them. They’re proud to use a technology that’s changing hiring, for good.
Leading the way in AI for hiring
We’ve continued to push the boundaries in leveraging ethical AI for hiring, with new products on the way for Coaching, Internal Mobility & Interview Builders.
Blog
Situational Judgement Tests vs. AI Chat Interviews: A Modern Perspective on Candidate Assessment
Choosing the right tool for assessing candidates can be challenging. For years, situational judgement tests (SJTs) have been a common choice for evaluating behaviour and decision-making skills. However, they come with limitations that can make the hiring process less effective and less inclusive.
AI-enabled chat-based interviews, such as Sapia.ai, provide organisations with a modern alternative. They focus on understanding candidates as individuals and creating a hiring experience that is both fair and insightful while enabling efficient screening and selection.
This shift raises important questions: Are SJTs still a tool that should be considered for volume hiring? And what do AI assessments offer in comparison?
1. The Static Nature of SJTs
Traditional SJTs use predefined multiple-choice questions to assess behavioural tendencies and situational knowledge. While useful for screening, these static frameworks lack the flexibility to adapt based on real-world performance data or evolving role requirements.
Once created, SJTs don’t adapt to new data or evolving organisational needs. They rely on fixed scenarios and responses that may not fully reflect the dynamic realities of modern workplaces, and as a result, their relevance may diminish over time.
AI-enabled chat interviews, on the other hand, are inherently adaptive. Using machine learning, these tools can continuously refine their models based on feedback from real-world outcomes such as hiring or turnover data. This ability to evolve ensures the assessments align with organisations’ needs.
2. Richer Data Through Open-Ended Responses
One of the main critiques of SJTs is their reliance on multiple-choice responses. While structured and straightforward, these options may not capture the full scope of a candidate’s thinking, communication skills, or problem-solving ability. The approach is often limiting, reducing complex human behaviour to a few predefined choices.
AI-enabled chat interviews work more holistically and dynamically. These tools provide a more complete picture of a person by allowing candidates to answer questions in their own words. Natural language processing (NLP) analyses their responses, offering insights into personality traits, communication skills, and behavioural tendencies. This open-ended format lets candidates express themselves authentically, giving employers a deeper understanding of their potential.
3. The Candidate Experience: Stressful or Supportive?
SJTs often include time constraints and rigid formats, which can create pressure for candidates. This is especially true when candidates feel forced to choose options that don’t fully reflect how they would actually behave. The process can feel impersonal, even transactional.
In contrast, chat-based interviews are designed to be conversational and low-pressure for candidates. By removing time limits and adopting a familiar chat interface, these tools help candidates feel more at ease. They also frequently include personalised feedback, turning the assessment into a valuable experience for the candidate, not just the employer.
4. Addressing Bias and Fairness
Traditional SJTs are prone to transparency issues, as candidates can often identify and select the “best practice” answers without revealing their true tendencies. Additionally, static test designs can unintentionally embed bias; due to the nature of the timed test, SJTs have been found to disadvantage some groups.
AI chat interviews, when developed ethically within a framework like Sapia.ai’s FAIR Hiring Framework, eliminate explicit bias by relying solely on the content of a candidate’s responses. Their machine learning models are continuously validated for fairness, ensuring that hiring decisions are free from subjective judgments or irrelevant demographic factors.
5. An Assessment That Improves Over Time
Workplaces are constantly changing, and hiring tools need to keep up. SJTs’ fixed nature can make them less effective as roles evolve or organizational priorities shift. They provide a snapshot but not a dynamic view of what’s needed.
AI-enabled chat interviews are built to adapt. With feedback loops and continuous learning, they incorporate real-world hiring outcomes—like retention and performance data—into their models. This ensures that assessments stay relevant and effective over time.
Rethinking Candidate Assessment
As hiring demands grow more complex, so does the need for tools that can capture the whole person, not just their response to hypothetical scenarios. While SJTs have played an important role in hiring practices, they are increasingly being replaced by tools like AI-enabled chat interviews.
These modern approaches provide richer data, adapt to changing needs, and create a richer and more engaging experience for candidates. Perhaps most importantly, they emphasise fairness and inclusivity, aligning with the growing demand for unbiased hiring practices.
For organisations evaluating their assessment tools, the question isn’t just which method is “better.” Understanding the specific needs of your roles, teams, and candidates will help you choose tools that help you make decisions that are both informed and equitable.
Blog
Keeping Interviews Real with Next-Gen AI Detection
It’s our firm belief that AI should empower, not overshadow, human potential. While AI tools like ChatGPT are brilliant at assisting us with day-to-day tasks and improving our work efficiency, employers are increasingly concerned that they’re holding candidates back from revealing their true, authentic selves in online interviews.
As an assessment technology provider, we are responsible for ensuring the authenticity and integrity of our platform. That’s why we’re thrilled to unveil the latest upgrade to our flagship Chat Interview: the AI-Generated Content Detector 2.0. With groundbreaking accuracy and a candidate-friendly design, this innovation reinforces our mission to build ethical AI for hiring that people love.
Artificially Generated Content (AGC) is content created by an AI tool, such as ChatGPT, Claude, or Pi. We initially rolled out the first version of our AGC detector last year and have continued to improve it as our data set has grown and these AI tools have evolved.
What’s New?
Our updated AGC Detector 2.0 achieves an impressive 98% detection rate for AI-assisted responses, with a false positive rate of just 1%. This gives organisations peace of mind that they’re getting the most authentic assessment of every candidate.
This cutting-edge system builds on Sapia.ai’s proprietary dataset of over 2 billion words, derived from more than 20 million interview question-answer pairs spanning diverse roles, industries, and regions. It’s trained on real-world data collected before and after the release of tools like ChatGPT, ensuring it remains robust and reliable even as AI tools evolve.
The Challenge of AI in Chat-based Interviews
Our data shows that around 8% of candidates use tools like GPT-4 to generate responses for three or more interview questions. While these tools may offer a quick way for candidates to complete their interview, they can inadvertently hide a person’s true personality and potential – qualities our customers are most interested in understanding through our platform. In fact, research from Sapia Labs shows that these tools have their own personality traits, which may be quite different from the candidate applying for the role.
For Candidates: Enabling Authenticity
When a response is flagged as potentially AI-generated, the system doesn’t disqualify candidates. Instead, a real-time warning pops up, allowing them to revise their answers or submit them as-is. This ensures that candidates are encouraged to present themselves authentically, reflecting their unique communication styles and sharing their genuine experiences.
For Hiring Teams: Actionable Insights
Responses flagged as AI-generated are highlighted in the candidate’s Talent Insights profile, accessible via Sapia.ai’s Talent Hub or ATS integrations. These insights give hiring teams the transparency to make informed decisions, fostering trust while accelerating hiring timelines.
Built on Unmatched AI Interview Expertise
“Our detection model’s strength lies in its foundation of real-world interview data collected from diverse roles and regions,” says Dr Buddhi Jayatilleke, Sapia.ai’s Chief Data Scientist. This depth of understanding enables the AGC Detector to maintain its industry-leading accuracy – even when candidates subtly modify AI-generated answers to appear more human.
Why This Matters
The AGC Detector 2.0 embodies Sapia.ai’s commitment to ethical AI that amplifies human potential. As our CEO Barb Hyman explains:
“The hiring landscape has fundamentally changed since ChatGPT, but our commitment remains clear: AI should amplify human potential, not penalise it. This breakthrough fosters authentic hiring conversations. Our real-time warning system helps candidates make better choices and gives enterprises confidence in their selection decisions.”
Testing and Validation of the AGC Detector 2.0
The new detector has been rigorously tested on over 25,000 interview responses generated by humans and leading AI models like GPT-4, Claude-3.5, and Llama-3. The results speak for themselves, reinforcing the reliability and fairness of this game-changing technology.
Fairness & Transparency in AI-Enabled Hiring
By detecting AI-generated content while allowing candidates to correct their responses, our AGC Detector 2.0 ensures every applicant has the chance to put their best, most authentic foot forward when applying for a role powered by Sapia.ai. For enterprises, it provides confidence in the integrity of their hiring decisions and ensures they’re connecting with real candidates at scale.