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An Unlikely Recruit

A few weeks ago, I confessed my imposter syndrome on social media. That I was, and still am, the least likely candidate to run an Ai tech company. I am a former CHRO, I am female, I am neither an engineer nor a data scientist. I also have no sales experience, and yet I find myself spending 80% of my time in sales (although we don’t call it that of course).

When I was Head of HR at BCG back in the noughties, the firm was going through a growth period. Due to the way teams were sold into engagements, having senior people who could execute on complex change programs in areas that were quite new to the firm (digital, etc), meant looking externally for ‘lateral’ hires.

These were people who could be trusted to uphold and amplify the firm’s strong values and bring much-needed expertise by virtue of their seniority and transferable skills. It was hard.

‘Organ rejection’ is a term I learned in my next gig, as CHRO at the then-largest digital company in Australia, the REA Group. Organ rejection is what happens when a lateral hire fails miserably – for both parties.

So, here I am 2.5 years into my current role. The one I feel professionally ill-qualified for when I realize I’m a lateral hire. But despite my self-doubt, there hasn’t been any ‘organ rejection’.

When I reflect on my life and the things that mean I might (there’s that imposter syndrome again) make a great CEO, I realize that so much of what I bring to this job is what I experienced outside of education. Born out of a need to be resilient from a young age, and a bit of serendipity.

Background

In 1980, when I was 10, my family immigrated from Zimbabwe to Perth, Australia. We arrived, a family of six, with little else than each other. Anyone who’s done it knows the uncertainty of immigration. Most of us do it to risk a better life knowing very little beyond what is a glossy brochure-like version of the new land we are sailing to. It wasn’t as easy as we had been sold, but we survived and adapted to our new home country.

At 18, I moved to Melbourne from Perth to study my undergrad. Not because I wanted to make a bold move again, but because I wanted to get as far away as possible from my stepmother. My mother had tragically died at a very young age a few years after we immigrated and my dad remarried within 10 months.

I took law as my undergrad because a friend a year ahead of me was doing it and she seemed to like it. I then took a wild punt on doing an MBA and managed to get a full scholarship. Which meant I could take my time to figure out what exactly I would do with an MBA.

Fast forward three kids, and a divorce in the middle. I decided I needed to be in a creative environment. So I took an executive role in the arts knowing nothing about the two areas I was responsible for nor the sector.

Perspective

I accepted an opportunity to be Deputy Chair on a board because someone believed in me. Not because I had a grand plan to build a portfolio career. I’ve never planned my life really, but I have often taken a punt. After all, I found my home by knocking on the front door because I just loved the look of it from the outside and thought ‘what the heck?”

I landed in this job because a close friend recommended me. I found the whole idea of figuring out how you find the best lateral talent so fascinating – without realizing until right now, I was a good example of just that.

I’d say that very little of my formal qualifications and work experience has really equipped me for the rough and tumble of being the CEO of a startup. The sheer unknown of building a new product in an emerging market, and the stress of checking the bank balance daily to make sure we can make this month’s payroll.

Most of what got me here came from the lessons I learned away from the workplace. From immigrating, losing a parent when I was young, leaving a city that I knew well on my own, learning to follow my whims, take chances, and constantly look for meaning.

None of that makes it onto my CV.

My mission is to make those things matter the most when it comes to finding the right people for the right job. I’m also making peace with my imposter syndrome by accepting that it’s the different perspective that I bring to the table that makes my contribution so unique.

I’d go so far as to say we should all hire “industry imposters” if we can. And I’m here to help you find them.

Barbara Hyman, 03/08/2020

Source: https://recruitingdaily.com/an-unlikely-recruit/


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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. 

See why our users love us 

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.

Share the candidate love

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. 

Join us in celebrating an incredible 2024

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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.

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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.

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