Part of our job here in the workforce science team is to keep up to date with new research in Organisational Psychology. This might sound boring to some people – but we love it!
As massive nerds, we find nothing more exciting than seeing new progress in our field. This time, our knowledge-cravings took us all the way from Melbourne to Orlando, Florida, to this year’s SIOP conference.
The issue of Adverse Impact
An important issue within our field – and within the US in general – is adverse impact and hiring for diversity.
We are passionate about ensuring people are not discriminated against in selection methods, whether it is because of gender, age, ethnic background or sexual orientation.
(Actually, this is also one of the key values and driving forces behind why Paul, our CEO, founded Sapia.)
One key topic at this year’s conference was the combination of data science and behavioural science. Specifically, there were a lot of discussions around how these sciences can work together to minimise bias and discrimination in the hiring process.
The standard recruitment selection process
To give you some background as to why this is important, let’s explore what a standard selection process might look like today.
If you ever have applied for a job, it is likely you have gone through a process involving;
- your resume
- a cover letter
- a psychometric test (personality/intelligence)
- an interview
- reference checks
As mentioned, pretty standard. This is typically the different pieces of information that recruiters would use to assess your suitability for a role.
However, from an adverse impact perspective, this isn’t good enough.
The reason is that humans are biased (there are a plethora of studies out there proving this). And even if our biases (in most cases) are unconscious, we still base discriminatory decisions on them.
Does your name predict future performance?
A research study by The Ladders found that recruiters only spend about 6 seconds looking at a resume. Using gaze-tracking technology they identified that recruiters spend almost 80% of this time on only a few items:
- name
- current title/company
- previous title/company
- previous position start and end dates
- current position start and end dates
- education
To most people that would seem reasonable. Our previous professional and educational experience should be predictive of future performance, right?
If you agree, it might surprise you that past job experience only has a 0.13 validity when used to predict performance (and your name certainly has nothing to do with how you would perform).
So not only is the information recruiters look at not actually predictive of performance, but it also has the potential to adversely impact minorities.
An eye-opening example
In the 1970s, the Toronto Symphony Orchestra was composed of almost all white males. A few years later, they caught on to their diversity issue and decided to do something about it.
One initiative was to introduce ‘blind auditions’. Individuals would perform from behind a screen, making the assessors ‘blind’ to who was performing. This meant that the performance was in the center of the assessment, not the individual.
The result?
The proportion of women within the orchestra increased from 5% to 35%.
Individuals within racial minority groups are also discriminated against based on resumes.
Research found that applicants with ‘traditional’ english names received an interview for every 1/10 resumes sent out. This is in contrast to applicants with African-American names, who only got an interview for every 1/15 resumes.
As the resume is one of the most common determinators of whether an applicant progresses to the next stage – it is alarming that this method can adversely impact minority groups.
Luckily, some progress is definitely being made to combat this.
Different techniques, for example blind recruitment, are increasing in popularity. Some progressive businesses have leap-frogged and started using artificial intelligence (AI) driven algorithms as a first step in their assessment process.
Important to keep in mind with AI and Adverse Impact
When using AI, it is very important to understand that the data put into the algorithm is of great importance. AI is often touted as the solution to the biases inherent in our thinking, but if not executed properly, AI can also become biased.
This is because an AI algorithm is only ever as bias-free as the data we used to build it.
It can be difficult to make sure AI is increasing diversity, and at the same time maintaining its predictive power. The predictive power is basically how good a model is at predicting good performance – and weeding out those who wouldn’t do so well.
To ensure best chance of success it is crucial that the data we put into AI recruitment tools is bias free.
One way is to control what you put into your AI models. Big Data can for example be dangerous, as it looks at adding all possible data sources of information to predict performance.
This could mean that the AI model learns that ethnic background is a predictor for success, which we clearly want to avoid.
To combat this issue at Sapia, we make the following decisions:
Targeted variables:
- we only choose variables that minority groups do not answer differently to other groups
(if we did the model could learn to discriminate against these groups if the variable was considered predictive)
Test our predictors:
- Are they in fact adversely impacting anyone?
- Conduct adverse impact studies
When considering a new assessment tool, you should always ask your test provider the following;
How do you ensure the assessment isn’t biased against any gender, age or racial category, whilst remaining highly predictive of performance?
If they can’t give you a satisfying answer, it is definitely worthwhile considering another vendor.
Liked what you read? For further reading on how we minimise bias in our algorithms, head here.
Related
Blog
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
Blog
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.
Blog
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.