Hello HR Tech – Recruiting is so much easier!
Last week I made a promise to share a journey that brought me to be working in the business at the cutting edge of technology and science within the People/Talent sector.
In my previous post, I shared some of the thinking of people within my sector. This is what I learned about hard work during my 13 years working in tech recruitment.
I was 22 years old when I became a recruiter. I was competitive, driven and hungry to succeed. Not only in financial terms, like many other recruiters, but also my professional status and standing. I wanted to be one of the best at my job and to be respected for the work I did.
And I know there are thousands of recruiters out there whose hard work often goes unrecognised by clients, candidates, managers and colleagues alike. I no longer know exactly what it’s like to be a recruiter in 2018 but back in 2005-2010 if you joined one, my teams, we’d have had conversations that went something like this:
There is no shortcut in recruitment
It requires a lot of hard work and skill with a splash of good luck.
The hard work is the time commitment needed to consistently deliver for your clients and candidates.
You need the skill to learn the difference between C# and C++ and how technologies stack together.
Eventually, your business development efforts will combine with good luck when that client answers your call and confirms they are indeed looking to hire someone within your vertical specialism. Happy days!!
You agree to terms for the customer’s key role, you pat yourself on the back and then you go again – back to the hard work because now you’ve got to find suitable candidates.
Good recruiters already have a network of great candidates – you go to them first, qualify/rule out and you’ve got a shortlist inside an hour or two. Then, more hard work.
When the other unknown recruiters working at unknown agencies also trying to fill the same role, clock off at 6 pm to enjoy their evening plans, you’re still in the office.
If you’re anything like I was you’ll still be in the office until 9 pm when the contractors start to get a little irate.
“Sorry for ringing so late in your evening but I’m trying to fill a key role for an important customer.”
Most of them appreciate your hard work and candour. Some even sound impressed with your commitment.
A few get grumpy but them’s the rubs – it’s water off a duck’s back for a driven, professional recruiter who wants to do their best for their customer and won’t mind, professionally, ruffling the feathers of a few early-to-beders to ensure they keep on top of their game, delivering great candidates to their clients.
Eventually, your hard work pays off and you place the successful candidate (probably after at least one candidate did an interview no-show following the death of a distant relative/hospital appointment/dog vs homework / insert obscure excuse)
Meet Tom & Sally to get a sense of what I was filling – I was definitely ‘Tom’!
That was my early recruitment career. Because I knew there were no shortcuts to success. I needed to graft, sacrifice my evening socialising (don’t worry, I made up for it at the weekends!) to ensure I found the best candidates for my clients.
I was a recruiter and I really, really loved my job. I genuinely hope today’s recruiters love their jobs as much as I did but the recruitment world I knew is no longer. And that’s because Talent AI has created a shortcut!
Not a corner-cutting shortcut. But an evidence-based, efficiency-creating, quicker, faster, more accurate shortcut.
AI can now rapidly identify suitable talent and create a shortlist of candidates for a human recruiter to then engage with.
A shortcut that also helps remove bias from talent workflows.
In fact, it’s such a clever shortcut that it should have its own name. I have a suggestion. Let’s call it…Recruitment!
Because recruitment was still recruitment when ATS providers rolled out filters and keyword identification tools which were quickly gamed by candidates – writing retail on a CV pushed it up the results list but that didn’t make the candidate more knowledgeable in retail.
It’s still recruitment – just done heaps better
Recruitment was still recruitment when talent attraction projects were created. Recruitment is still recruitment throughout the modern-day careers day (which I hope has evolved from my experiences back in the early 2000s)!
It’s still recruitment if you bring in video interviews (disclaimer: I hate the idea of video interviews; I think they simply shift bias to a different stage in the recruitment process).
Recruitment will still be recruitment with AI, it’ll just be better for candidates, clients and recruiters alike.
Suggested reading:
https://sapia.ai/7-tips-to-making…stment-decisions/
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And we’re just getting started 🚀
Take a look at the highlights of 2024
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.