The marriage of behavioural science, data science and AI technology
The introduction of artificial intelligence (AI) technologies into the world of HR and recruitment is not just an idea anymore, it is a reality, specifically focusing on AI for HR. Neural networks, machine learning, and natural language processing are all being introduced into different areas of HR, marking a significant shift towards integrating AI for HR purposes.
These developments contribute to the function’s increased accessibility to data-driven insights and analytics, enabling better-informed people decisions.
In recruitment and talent acquisition, AI technologies have the potential to make a significant impact by identifying candidates who can perform well in individual business environments.
However, pre-hire assessment is a complex area, and without incorporating validated behavioural science we only end up with a 2D view – instead of the 3D view we actually wanted. This is why the marriage of data, computer and behavioural sciences is essential.
By bringing together organisational psychologists, data scientists and computer scientists we truly leverage the power of artificial intelligence – and change the way candidates are recruited. It takes the recruitment process beyond the technical excellence necessary to collect and report on data and insights.
By merging these scientific areas we get:
- Computer science expertise providing the critical ‘how’ for collecting quality data.
- Data science brilliance then revealing the ‘what’ of unseen connections within that data.
- Well-constructed behavioural science explaining the ‘why’ behind those connections.
Through the combination of all three disciplines, we can access a whole extra world of meaning, enabling us to get closer to the core of what’s happening in organisations.
Behavioural science is the key to success
A recent Industrial & Organisational Psychology article pointed to the disruption taking place in the talent identification industry through new digital technologies. The authors noted that although big data is attractive, the data is often thrown together and interrogated using data science until correlations are found. This has become known as ‘dustbowl empiricism’.
My favourite for this at the moment has to be the strong correlation between the number of people who have drowned by falling in a pool, and the number of films Nicolas Cage has appeared in any given year. Who knew how dangerous Nicolas Cage could really be?
Despite the evident danger of watching Nicolas Cage films (particularly near water), I believe there is more value in explaining behaviour than in just predicting it.
For example, is there a correlation between owning a certain type of car and being a high performer?
Perhaps, but I don’t think to look for the best candidates in car parks is very useful. After all, people change cars, and so might the correlations change between particular car models and performance. To cite another famous example, as often as people change their eating preferences, so goes the link between curly fries and intelligence.
Understanding why data is linked can suggest better ways to improve performance than just updating the carpool or changing the canteen menu.
Linking a vehicle preference to well-established behavioural science may suggest that a client considers how a candidate is innovative elsewhere in their lives, such as in their adoption of other new technologies. Or they may look for other ways the candidate demonstrates a penchant for reliability (perhaps through previous work choices).
The scientific approach
This is where organisational psychologists come in.
They have an intimate knowledge of the theories that can help interpret and explain the links between personal attributes and performance, or other variables that matter. They know how to use these theories to solve real problems and they know how to design studies and measurement tools to ensure that scientific knowledge is applied correctly in an organisational setting.
I learned a lot of organisational psychology models and theories during my Masters and PhD studies. We focused on these and the research behind them when I taught MBA and Master of Organisational Psychology programs – sometimes noting gaps in current models and theories – and designing studies to help extend or debunk what we knew.
While completing my MBA and later in a corporate role, I became skilled in applying that knowledge to the problems managers and executives face.
As an organisational psychologist I often find that it isn’t just knowing behavioural science that matters, it is knowing the behavioural science detail to understand what is most relevant for a role or business problem.
For example, consider sales performance.
Thanks to the popularity of some psychometric instruments, ‘extroverted’ or ‘introverted’ are understood as reliable ways to describe elements of a person’s personality, and many people are convinced that being extroverted is important in a sales role.
However, the research on sales performance says otherwise. An International Journal of Selection and Assessment article shows that across a range of studies there isn’t a strong link between ‘extraversion’ (broadly) and sales performance, despite this being such a common view.
Knowing the detail matters here.
A broad description of extraversion may not do a candidate justice, particularly when we’re focused on understanding performance in a particular role.
Instead, we might be interested in a candidate’s level of dominance, their sociability, what they would be like in a group setting, or presenting to a group to make a sale.
Perhaps we’d be interested in whether they are independent, adventurous, or ambitious, all of which (as potential elements of extroversion) may have different implications for sales performance.
We might also focus on the particular nature of the sales role – many roles are becoming more formalised and structured, with down-to-the-minute journey plans and call times. No wonder then that the Journal of Selection and Assessment article found another personality factor, conscientiousness, to be relevant for predicting sales performance.
The business focus of pre-employment assessments
It’s the acceptance of how important behavioural science is to the new world of AI that has led me to Sapia, where we believe all people decisions should be based on science, data and analytics – not just gut feeling.
Sapia focuses on the things that matter.
We use validated behavioural science to build predictive models, centred on the issues your business wishes to address and their corresponding KPIs. The predictive model is based on your workforce data so it’s unique to your organisation, maximising predictive accuracy while also prioritising the candidate experience.
We use various techniques, including training a neural network to identify what drives performance in the organisation, based on the data we collect. We build our algorithms to achieve accurate predictions from the start, and the model improves over time through machine learning.
We’re now at a point where we can use behavioural science, data science and computer technology to understand the intricate links between candidate information and performance data. With that we can help reduce bias and level the candidate playing field and give managers a 3D view of their candidates, to enable them to make the best people decisions.
Dr. Elliot Wood is a registered organisational psychologist with a bachelor’s degree, various master’s degrees and a PhD in the field. He spent 12 years in academia, teaching master’s-level organisational psychology; supervising post-graduate research; and working on research grants and consulting projects. He then moved into organisational development–focused consulting in Australia and Asia, followed by an internal talent role in a multinational brewer. He is now Chief Organisational Psychologist at Sapia.
References
Tomas Chamorro-Premuzic, Dave Winsborough, Ryne Sherman and Robert Hogan, Industrial & Organisational Psychology, ‘New Talent Signals: Shiny New Objects or a Brave New World?’
Murray R. Barrick, Michael K. Mount, Timothy A. Judge, International Journal of Selection and Assessment, ‘Personality and Performance at the Beginning of the New Millennium: What Do We Know and Where Do We Go Next?’
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The AGC Debate: Are AI-Written Interview Answers a Red Flag or Smart Strategy?
Every day, we read stories of increased fake or AI-assisted applications. Tools like LazyApply are just one of many flooding the market, driving up applicant volumes to never-before-seen levels.
As an overwhelmed hiring function, how do you find the needle in the haystack without using an army of recruiters to filter through the maze?
At Sapia.ai, we help global enterprises do just that. Many of the world’s most trusted brands, such as Qantas Group, have relied on our hiring platform as a co-pilot for better hiring since 2020.
Our Chat Interview has given millions of candidates a voice they wouldn’t have had – enabling them to share in their own words why they’re the best fit for the role. To find the people who belong with their brands, our customers must trust that their candidates represent themselves. Thus, they want to trust that our AI is analysing real human answers—not answers from a machine.
The Rise of GPT
When ChatGPT went viral in November 2022, we immediately adopted a defensive strategy. We had long been flagging plagiarised candidate responses, but then, we needed to act fast to flag responses using artificially generated content (‘AGC’).
Many companies were in the same position, but Sapia.ai was the only company with a large proprietary data set of interview answers that pre-dated GPT and similar tools: 2.5 billion words written by real humans.
That data enabled us to build a world-first:- an LLM-based AGC detector for text-based interviews, recently upgraded to v2.0 with 99% accuracy and a false positive rate of 1%. An NLP classification model built on Sapia.ai proprietary data that operates across all Sapia.ai chat interviews.
Full Transparency with Candidates
Because we value candidate trust as much as customer trust, we wanted to be transparent with candidates about our ability to detect artificially generated content (AGC). As an LLM, we could identify AGC in real time and warn candidates that we had detected it.
This has had a powerful impact on candidate behaviour. Since our AGC detector went live, we have seen that the real-time flagging acts as a real-time disincentive to use tools like ChatGPT to generate interview responses.
The detector generates a warning if 3 or more answers are flagged as having artificially generated content. The Sapia.ai Chat Interview uses 5 open-ended interview questions for volume hiring roles, such as retail, contact centre, and customer service, and 6 questions for professional roles, such as engineers, data scientists, graduates, etc.
Let’s Take a Closer Look at the Data…
We see that using our AGC detector LLM to communicate live with candidates in the interview flow when artificial content has been detected has a positive effect on deterring candidates from using AI tools to generate their answers.
The rate of AGC use declines from 1 question flagged to 5 questions – raising the flag on one question is generally enough to deter candidates from trying again.
The graph below shows the number of candidates, from a total of almost 2.7m, that used artificially generated content in their answers.
Differences in AGC Usage Rate by Groups
We see no meaningful differences in candidate behaviour based on the job they are applying for or based on geography.
However, we have found differences by gender and ethnicity – for example, men use artificially generated content more than women. The graph below shows the overall completion ratios by gender – for all interviews on the left and for interviews where the number of questions with AGC detected is 5 or more on the right.
Perception of Artificially Generated Content by Hirers.
We’re curious to understand how hirers perceive the use of these tools to assist candidates in a written interview. The creation of the detector was based on the majority of Sapia.ai customers wanting transparency & explainability around the use of these tools by candidates, often because they want to ensure that candidates are using their own words to complete their interviews and they want to avoid wasting time progressing candidates who are not as capable as their chat interview suggests.
However, some of our customers feel that it’s a positive reflection of the candidate, showing that they are using the tools available to them to put their best foot forward.
It’s a mix of perspectives.
Our detector labels it as the use of artificially generated content. It’s up to our customers how they use that information in their decision-making processes.
This concept of having a human in the loop is one of the key dimensions of ethical AI, and we ensure that it is used in every AI-related hiring product we build.
Interested in the science behind it all? Download our published research on developing the AGC detector 👇
Research Paper Download: AI Generated Content in Online Text-based Structured Interviews
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Joe & the Juice Partners with Sapia.ai, Scaling an Exceptional Candidate Experience and Cutting Time to Hire
Read the full press release about the partnership here.
Joe & the Juice, the trailblazing global juice bar and coffee concept, is renowned for its vibrant culture and commitment to cultivating talent. With humble roots from one store in Copenhagen, now with a presence in 17 markets, Joe & The Juice has built a culture that fosters growth and celebrates individuality.
But, as their footprint expands, so does the challenge of finding and hiring the right talent to embody their unique culture. With over 300,000 applications annually, the traditional hiring process using CVs was falling short – leaving candidates waiting and creating inefficiencies for the recruitment team. To address this, Joe & The Juice turned to Sapia.ai, a pioneer in ethical AI hiring solutions.
A Fresh Approach to Hiring
Through this partnership, Joe & The Juice has transformed its hiring process into an inclusive, efficient, and brand-aligned experience. Instead of faceless CVs, candidates now engage in an innovative chat-based interview that reflects the brand’s energy and ethos. Available in multiple languages, the AI-driven interview screens for alignment with the “Juicer DNA” and the brand’s core values, ensuring that every candidate feels seen and valued.
Candidates receive an engaging and fair interview experience as well as personality insights and coaching tips as part of their journey. In fact, 93% of candidates have found these insights useful, helping to deliver a world-class experience to candidates who are also potential guests of the brand.
“Every candidate interaction reflects our brand,” Sebastian Jeppesen, Global Head of Recruitment, shared. “Sapia.ai makes our recruitment process fair, enriching, and culture-driven.”
Results That Matter
For Joe & The Juice, the collaboration has yielded impressive results:
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33% Reduction in Screening Time: Pre-vetted shortlists from Sapia.ai’s platform ensure that recruiters can focus on top candidates, getting them behind the bar faster.
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Improved Candidate Satisfaction: With a 9/10 satisfaction score from over 55,000 interviews, candidates appreciate the fairness and transparency of the process.
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Bias-Free Hiring: By eliminating CVs and integrating blind AI that prioritizes fairness, Joe & The Juice ensures their hiring reflects the diverse communities they serve.
Frederik Rosenstand, Group Director of People & Development at Joe & The Juice, highlighted the transformative impact: “Our juicers are our future leaders, so using ethical AI to find the people who belong at Joe is critical to our long-term success. And now we do that with a fair, unbiased experience that aligns directly with our brand.”
Trailblazing for the hospitality industry
In an industry so wholly centred on people, Joe & the Juice is paving the way for similar brands to adopt technology that enables inclusive, human-first experiences that can reflect a brand’s core values.
If you’re curious about how Sapia.ai can transform your hiring process, check out our full case study on Joe & The Juice here.
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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.