Before COVID, the conversations I was having with HR executives were about how Sapia might help them with the volume of candidates they were receiving for job openings. For every job posted there were often over a thousand candidates, and it doesn’t take much of a stretch of the imagination to understand how overwhelmed many big organisations were. Our Ai was seen as the solution to automate dealing with candidate volume in a way that found the best people, but also touched base with everyone who applied as part of their brand building. In a nutshell, before the pandemic, efficiency was the key driver in looking for automated hiring solutions like ours.
Now that we’re emerging from the disruption of COVID, no one is talking to me about needing help with the volume of candidates they receive. In fact, they are asking how we might help them get any candidates in the first place! All around the globe, and across multiple industries, there is a need for candidates. It’s certainly been an abrupt change that has left many scratching their heads, but there is almost no time to wrap your head around it if you want to stay in the game. This is a new war for talent unlike any we’ve seen before, and candidates have the upper hand. It’s created a need for a solution to solve two things: firstly, to identify skills in candidates that traditional ways of hiring failed to identify (I call this cohort “undiscovered talent”) and a strong candidate experience (you are the one being interviewed from the moment they hit “apply”).
I thought it was worth looking at how the “war of talent” has evolved since it was first coined by Steven Hankin at McKinsey & Company in 1997. At that time there was a shift in the way that companies valued their talent, and it became seen as important to attract the best in order to have a successful organisation. It’s hard to think about this now, but at that time the whole idea of cultivating company cultures that aimed to elevate and value employees was new. At this stage though the “war” was largely for executive talent with recruiters focusing on building their brand by poaching star C-Suite talent off competitors, wooing them with big sign-up bonuses and lavish overtures like unexpected gifts and trips.
As tech companies started to become the big players in the market, the focus turned from business acumen to the need for the best digital and technical talent. Recruiting became less about material perks (though many engineers still commanded high salaries) but also about giving talent things they wanted besides just money. Flexibility, free lunches, unlimited holidays and creating cultures that were about “working hard and having fun” were how the war for technical talent was won. This was really a time of culture wars between companies, but also meant that many companies hired only for culture-fit. This resulted in fairly homogenous teams that were largely white male techbros, and eventually many large tech companies were called out on it. Beyond tech, corporates were also waking up to the fact that they had some serious diversity issues that needed to be addressed. This led to a new war. The war for diverse talent.
Pre-COVID, hiring more diversely was a strong focus for companies to find the best talent. We all know that diverse teams result in better business outcomes and anyone who had a “pale, male and stale” executive team was seen as minted in the past. Coupled with Black Lives Matter, which became a global movement to address racial inequality from the C-suite down, finding more diverse talent through reducing bias in hiring, was where the war was being fought. This is not a won battle by the way, and remains a large focus for many companies that we work with and help. Importantly, finding diverse talent is still a key part of this new and emerging next phase of the “war on talent” … the one where workers have the upper hand. The one where candidates are in short supply, and people want jobs that suit them just as much as whether they are seen as just suited to the job.
Recruiters have been forced to look at people differently – and this is not a bad thing. Factors like age, ethnicity, education, gender and even past experience that obscured our understanding of someone’s ability to do a job have all been cancelled as qualifying factors. Soft skills, or human skills, have become the focus on what we need to understand in order to assess someone’s suitability to do a job. Are they a team player? Do they like to problem solve? How aligned are they to our company values? Are they self-aware and in touch with their emotions? Can they put stress aside to achieve outcomes?
“What we recruit for” has significantly shifted for many already, but there is still some catching up to do on the “how we recruit”. To be blunt, CV’s and cover letters begging recruiters to “pick me!” serve no purpose in this new battle. They ask too much of candidates from the outset, serve no valuable purpose in the information they provide, confirm our biases and just create work on the HR manager’s side.
We need to walk in a candidate’s shoes and make sure that our recruiting process puts them first, treats them fairly and without bias, meets them where they are at, and is both friendly and informative. And, HR teams need to do this all while working efficiently and fast. Speed is crucial when talent is in short supply.
Impossible? No, not at all. Recruiters need to understand that Ai platforms like ours exist to solve all these problems. We’re not a “technical” solution, but a human one, in that we can accurately identify soft skills immediately and engage with candidates in a one-on-one way, at scale.
You cannot win this war on talent without chat-driven Ai technology. Technology like ours is the only way you can quickly understand the real human skills that every candidate brings to the table, without dismissing anyone upfront.
I can’t help but think that these issues we’re facing as recruiters and HR managers right now, where workers have the upper hand, while unchartered territory, will only serve our industry for the better. It’s a chance to give everyone a fair go, truly understand them, treat them with the dignity they deserve … and still hire better teams.
Maybe it’s not a battle after all. Maybe it’s a win-win.
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For more on how to improve candidate experience using recruitment automation, we have a great eBook on candidate experience.
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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.