To find out how to interpret bias in recruitment, we also have a great eBook on inclusive hiring.
Blind hiring and screening approaches have become significant in recruitment recently and are now considered fair and objective. But what is blind screening? The blind screening involves a situation where the candidate’s personal information such as name, gender, age, or ethnicity is not known to the employer. This is to avoid the bias of conscience and make the process of employment be fair or meritocracy.
One of the AI-enhanced interviewing practices is the AI blind interviews, where an AI interviewer does not know about the personal and demographic details of the candidate. At times, AI blind interviews may also employ voice modulation to guarantee total anonymity. On the other hand, blind resumes are carefully edited versions, where personal information is removed, leaving only skills and experience, often processed through AI interview software.
Blind recruitment is defined as the process of making hiring decisions without regard to personal and demographic details. This approach has gained momentum, and recent blind hiring data indicate that organizations that practice these methods tend to see a rise in diversity as well as a decrease in hiring bias.
Blind Hiring.
In the late 1970s, as the world was changing around them, the Toronto Symphony Orchestra realised they had a problem. Specifically, a white male problem; the profile of nearly every musician.
In what is largely seen as the genesis of the blind interview, in 1980 the orchestra changed their audition process completely. Musicians were placed behind a screen so the auditioning panel couldn’t know the gender, race or age of the musician they were listening to. It’s said they even put down the carpet so the sound of high heels on the stage could not be heard.
All the panel could hear was the music.
Of course, the result of this blind screening was profound. Hiring decisions were made on the quality of the performance only. In just a few short years, the ‘white male’ orchestra was transformed to more equal gender representation with musicians further diversified by their cultural backgrounds.
Not only has the Toronto Symphony Orchestra continued to use blind screening ever since, but it was also quickly adopted by most major orchestras around the world.
Beyond the concert stage, blind screening and blind recruitment practices are used by government, academic and business organisations globally. Because when it comes to identifying the best qualified or best-fit candidates, all you need to hear is their ‘music’.
It’s hard to admit our biases play a role in our decisions. That’s why Blind Hiring works.
Are tall people more likely to get higher paid roles? Do the best looking candidates always get the job? Will Michael or Mohamed be the best fit for your team?
While it’s easy to recognise bias in other people, it’s usually harder to admit that we are biased ourselves. That’s why it’s called unconscious bias. It’s something we all have and something we can all be affected by.
Unconscious bias is about making assumptions, stereotyping or a fear of the unknown in how we assess other people. It can be innate or it can be learned and it’s created and reinforced through our personal experiences, our cultural background and environment.
Think of gender bias, ageism, racism or name bias – these are some common biases that need no explanation. However, psychologists and researchers have identified over 150 types of bias that impact the way we form opinions and make judgements about people, often instantly.
The science is in. People are biased. And, again, that’s why Blind Hiring works.
In a two year study titled Whitened Résumés: Race and Self-Presentation in the Labor Market published in the Administrative Science Quarterly in 2016, academics from the University of Toronto and Stanford University looked at racial and gender bias during resume screening.
In one US study, they created and sent out resumes for black and Asian candidates for 1,600 advertised entry-level jobs. While some of the resumes included information such as names, colleges, towns and cities that clearly pointed out the applicants’ race or status, others were ‘whitened’, or scrubbed of racial clues.
Amongst many insights, they found that white-sounding names were 75% more likely to get an interview request than identical resumes with Asian names and 50% more likely than black-sounding names. Males were 40% more likely to get an interview request than women.
Still need convincing?
Another 2016 study by The Institute for the Study of Labor (IZA) in Bonn, Germany examined how ethnicity and religion influenced a candidate’s chances of landing an interview. 1500 real employers received otherwise identical applications, complete with a photo, from Sandra Bauer, Meryem Ӧztürk, or Meryem Ӧztürk wearing a headscarf.
- German-sounding Sandra received interview invitations 19% of the time.
- The identical application from Meryem recieved a call back 14% of the time while Meryem with a headscarf got called just 4% of the time.
These are just two of many research studies that suggest bias and discrimination are rife in the hiring process. In a 2017 UK study, only a third of hiring managers felt confident they were not biased or prejudiced when hiring new staff, while nearly half of those surveyed admitted that bias did affect their hiring choice. 20% couldn’t be sure.
Tackling bias in hiring & recruitment
When it comes to hiring, we all have our own thoughts about what an ideal candidate is supposed to look like. The problem is that our own bias can get in the way of the right decision.
If you’ve already pre-determined a candidate’s suitability by their age, gender or the school they attended, then you could be missing out on employing the candidate with the best qualifications. Or while you’re thinking about the best ‘cultural fit’ for your team, you’re actually missing the opportunity for the best ‘cultural add’.
But what if you could take bias out of candidate screening and hiring process? Is that even possible?
A closer look at blind hiring
Just as the Toronto Symphony Orchestra hid the identities of auditioning musicians behind a screen, there are several ways to bring blind hiring to your recruitment process:
Blind Screening
Nearly all hiring decisions will involve a human to human interview. But take a step back in the process and blind screenings can ensure that all candidates are competing on a level playing field. With the opportunity to be assessed only on qualifications or skills, the best candidates for a role can be identified.
Blind screening is about making candidates anonymous – removing details from applications or CVs that reveal details that may colour the recruiter or hirer’s assessment. It makes it easier to make objective decisions about a candidate based on skills, experience and suitability without the distraction (and the damage!) of bias.
Unconscious bias can be triggered by someone’s name, their gender, race or age, the town they grew up in or the schools they attended.
Blind Assessments
Before making a final decision, many employers like to test a candidate’s skills or knowledge by setting a task or challenge. Others undertake personality or other testing to assess a range of relevant qualities such as aptitude, teamwork, communication skills or critical thinking. Candidates can be assigned an identifying number or code to retain their anonymity through blind testing, though this is often best done through a third-party service provider.
Blind Interviewing
With face-to-face, phone or video interviews, it’s clearly impossible to keep candidates anonymous. Blind interviewing is possible, however, using a written QandA format or by using next-generation chatbots or text-driven interview software. Most recruiters and employers would agree, however, that there would be few if any, times it would be appropriate to make hiring decisions based solely on blind interviewing and without an in-person interview.
Read: The Ultimate Guide to Interview Automation
Blind interviewing, testing and screening in one – how Sapia has changed the game
Sapia is a leading innovator and advocate in using technology to enhance the recruitment process. Our AI-enabled, text chat interview platform has been designed to deliver the ultimate in blind testing at the most important stage of the recruitment process: candidate screening.
The ultimate in blind screening
Firstly, you will never have to read another CV again. Especially in bulk recruiting assignments, Sapia can help recruiters find the best candidates faster and more cost-effectively. CV’s are littered with bias-inducing aggravators. With Sapia, blind interviews are at the top of the recruiting funnel, not CV reviews.
By removing bias from the screening process, we’re helping employers to increase workplace diversity. It also delivers an outstanding candidate experience.
Reviewing and screening CVs is the most time-consuming part of any recruiter’s job and Sapia can put more hours back in your day.
Removing bias elements from the equation
Sapia evaluates candidates with a simple open, transparent interview via a text conversation. Candidates know mobile text and trust text.
Our platform removes all the elements that can bring unconscious bias into play – no CVs, video hook-ups, voice data or visual content. Nor do we extract data from social channels.
What candidates do discover is a non-threatening text interview that respects and recognises them for the individual they are, providing them with the space and time to tell their story in their words.
Algorithms see what humans can’t
As candidates complete and submit their interview, the platform uses artificial intelligence and machine learning to test, assess and rank candidates on values, traits, personality, communications skills and more. By bringing this blind interview into the upfront screening, recruiters can gain valuable personality insights and the confidence of a shortlist with the very best matched candidates to proceed to live interviews.
The platform has a 99% satisfaction rate from candidates and they report they are motivated by the personalised feedback, insights and coaching tips that the platform provides, along with the opportunity to provide their feedback on the process.
Blind hiring is better for business
Free from biases of the candidate’s race, gender, age or education level, Sapia’s platform delivers blind interviewing, testing and screening in one. Helping to build workplace diversity brings benefits for everyone – it can help lift employee satisfaction, boost engagement and productivity and enhance the reputation of your business as a great employer.
We believe there is a formula for trust when it comes to interviewing …
- Blind screening
- Using inclusive and engaging technology
- Apply a consistent assessment rubric
- Explainable and relatable process
- Relying only on data consensually given by the candidate
Final human decision supported by objective data. Or more simply:
Trust = (Inclusivity + Transparency + Explainability + Consistency) – Bias
Find out more about our AI-powered blind recruitment tool and how we can support your hiring needs today. You can try out Sapia’s Chat Interview right now – here. Else you can leave us your details to receive a personalised demo
Have you seen the New Inclusive e-Book?
It offers a pathway to fairer hiring. Get diversity and inclusion right whilst hiring on time and on budget.
In this Inclusivity e-Book, you’ll learn:
- How to design an inclusive recruitment path. From discovery to offer and validation of the process.
- The hidden inclusion challenges that are holding your organisation back.
- How to tell if Ai technology is ethical.
Related
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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.