Interview bias training is essential for businesses looking to optimize their hiring processes. Is unconscious bias in recruitment holding your business back? When aiming to expand your team, it’s tempting to select a candidate who appears to be a solid ‘cultural fit’.
However, what if that means you’re overlooking a candidate who could be an invaluable ‘cultural add’? Interview bias training can help hiring managers and teams recognize and overcome these pitfalls. When you strive to challenge unconscious bias and foster an environment that appreciates diversity – in terms of background, experience, worldview, and many other facets – you nurture an office that benefits not only your team but also your enterprise.
Hiring based on a gut instinct that someone will mesh well with the team might be a sign that your choice was swayed by unconscious hiring bias. It’s not unusual, and in reality, we all possess unconscious bias and are influenced by it. This is where interview bias training becomes pivotal.
Bias might be evident in others.
You may notice it in how someone behaves or speaks about others. Maybe you’ve felt the sting of bias firsthand. Recognizing our inherent biases can be tough, which is why it’s dubbed unconscious.
Unconscious bias training for recruiters and unconscious bias training for hiring managers is not just a trending term; it’s a burgeoning industry. In this piece, we delve into the pivotal questions surrounding bias: What exactly is unconscious bias? How does it alter the hiring framework? Is it possible to truly counter unconscious bias? If you’ve swiftly reached your own verdicts on these queries, that’s a manifestation of unconscious bias too!
The Imperative Discussion on Bias
From the era when our ancestors congregated around fires, bias has been prevalent.
It’s essentially how we lean towards or against a concept, object, individual, or group. Bias often implies these sentiments are prejudiced or discriminatory.
Bias revolves around presumptions, stereotypes, or trepidation of the unfamiliar. It can be intrinsic or acquired, and unconscious bias is shaped and amplified by our personal histories, cultural backdrop, and surroundings. Biases can be trivial – like despising broccoli – or they can be significantly detrimental.
Why is Unconscious Bias Crucial During Hiring?
The aim of overcoming bias at work is to establish a milieu where every staff member feels the environment is congenial, secure, and devoid of discrimination or harassment. While this might sound idealistic, diverse and inclusive work settings can elevate employee contentment, augment engagement and efficiency, and bolster your company’s repute as an exemplary employer. It also diminishes the risk of potential legal repercussions from inequitable employment practices.
The Most Frequent Forms of Unconscious Bias in the Workplace
Regarding recruitment, certain biases are more prevalent. While some are self-explanatory – such as gender bias, ageism, and racism – experts have pinpointed over 150 types of unconscious bias influencing our interactions. We’ll examine a handful here. It’s plausible you’ve allowed one or more of these biases to sway your decisions, hence missing an ideal candidate.
- Confirmation Bias – Rapidly forming an opinion based on a singular detail and subsequently seeking to validate that impression.
- Overconfidence Bias – Overestimating one’s judgment capability, often intertwined with confirmation bias.
- Illusory Correlation – Misinterpreting or overstating the relevance of certain responses to the candidate’s competence.
- Beauty Bias – Preferring candidates based on appearance, which isn’t indicative of their job proficiency.
- Conformity Bias – Yielding to group consensus even if personal opinions differ.
- Contrast Effect – Comparing candidates to their predecessors instead of evaluating them based on the job’s demands.
How are you scoring in bias roulette?!
Here’s some more:
Affect heuristics – this unconscious bias sounds very scientific, but it’s one that’s being a very human survival mechanism throughout history. It’s simply about making snap judgements on someone’s ability to do a job based on superficial and irrelevant factors and your own preconceptions – someone’s appearance, tattoos, the colour of their lipstick.
Similarity attraction – where hirers can fall into the trap of essentially hiring themselves; candidates with whom they share similar traits, interests or backgrounds. They may be fun to hang out with, but maybe not the best match for the job or building diversity.
Affinity bias – so you went to the same school, followed the same football team and maybe know the same people. That’s nice, but is it really of any relevance to the hiring decision?
Expectation anchor – where the hirer is stuck on what’s possibly an unrealistic preconception of what and who the candidate should be
Halo effect – Your candidate is great at one thing, so that means they’re great at everything else, right? Judging candidates on one achievement or life experience doesn’t make up for a proper assessment of their qualifications and credentials
Horn effect – It’s the devil’s work. The opposite of the halo effect where one negative answer or trait darkens the hirer’s judgement and clouds the assessment process.
Intuition – going with that gut feeling again? While the emotional and intellectual connection may come into the process, it’s largely irrelevant. Focus on their actual experience and capabilities instead.
Can unconscious bias be eliminated? Can bias be unlearned?
In an ideal world, every hire would be approached in an objective way, free of unconscious basis and based on the candidate’s ability to do the job well. However, we don’t live in that perfect world and, time and time again, bias can cloud our judgement and lead to the wrong recruitment decisions. So what can we do? Let’s first talk about what doesn’t work.
Why unconscious bias training does not work
The efforts of any business to drive affirmative change in their business are to be respected. However, there’s a very good reason why unconscious bias training simply can’t work. Why?
Because unconscious bias is a universal and inherently human condition. Training targets individuals and their well-worn attitudes and world views.
While awareness and attitudes may change, inherent bias will remain because that’s the human condition.
So if humans can’t solve a very human problem, what can? Sapia is challenging the issue of unconscious bias in hiring by promoting ‘top-of-funnel’ screening that entirely avoids humans and their bias. Instead, candidates are interviewed and assessed through automation and algorithms. The data that trains the machine is continuously tested so that if ever the slightest bias is found, it can be corrected.
According to an Article Published By Fast Company:
(Ref. https://www.fastcompany.com/90515678/science-explains-why-unconscious-bias-training-wont-reduce-workplace-racism-heres-what-will)
From a scientific perspective, there are reasons to be cautious that unconscious bias training will have a significant impact on racism, sexism, and other forms of workplace discrimination.
1. MOST BIASES ARE CONSCIOUS RATHER THAN UNCONSCIOUS
Contrary to what unconscious bias training programs would suggest, people are largely aware of their biases, attitudes, and beliefs, particularly when they concern stereotypes and prejudices. Such biases are an integral part of their self and social identity.
2. THERE IS ONLY A WEAK RELATIONSHIP BETWEEN ATTITUDES AND BEHAVIORS
Contrary to popular belief, our beliefs and attitudes are not strongly related to our behaviours. There is rarely more than 16% overlap (correlation of r = 0.4) between attitudes and behavior, and even lower for engagement and performance, or prejudice and discrimination.
3. THERE IS NO ACCURATE WAY TO MEASURE UNCONSCIOUS BIAS
The closest science has come to measuring unconscious biases is via so-called Implicit Association Tests (IAT), like Harvard’s racism or sexism test. (Over 30 million people have taken it, and you can try it for free here. These have come under significant academic criticism for being weak predictors of actual behaviours. For example, on race questions (black vs. white), the reported meta-analytic correlations range from 0.15 to 0.24.
4. IT’S HARD TO CHANGE PEOPLE’S BELIEFS, ESPECIALLY WHEN THEY DON’T WANT TO
The hardest thing to influence through any D&I initiative is how people feel about concepts such as gender or race. Systematic reviews of diversity training concluded: “The positive effects of diversity training rarely last beyond a day or two, and a number of studies suggest that it can activate bias or spark a backlash.”
Algorithms do the job humans can’t
Using machines and artificial intelligence to augment and challenge decisions is fast becoming mainstream across many applications and industries. To reduce the impact of unconscious bias in hiring decisions, testing for bias and removing it using algorithms is possible. With humans, it’s not.
Sappia tackles bias by screening and evaluating candidates with a simple open, transparent interview via a text conversation. Candidates know text and trust text.
Unlike other Ai Hiring Tools, Sapia has no video hookups and no visual content. No CVs.
All of these factors carry the risk that unconscious bias can come into play. Nor is data extracted from social channels as our solution is designed to provide every candidate with a great experience that respects and recognises them as the individual they are.
A better experience for candidates, recruiters and clients alike
A research study by The Ladders found that recruiters only spend about 6 seconds looking at a resume. With bulk-hiring, it’s probably less. That’s 6 seconds to make or break a candidate’s hope.
Sapia’s AI-based screening comes into to its own with high volume briefs, with the capability to conduct unlimited interviews in a single hour/day, assessing >85 factors – from personality traits to language fluency and other valuable talent insights. Candidates receive personalised feedback, coaching tips for their next interview and faster decisions on their progress in the hiring process.
Sapia is not out to replace human recruiters but we are here to work as your co-pilot, helping you to make smarter, faster and unbiased hiring decisions.
Understand where unconscious bias has held your business back
AI-enabled enabled interviewing and assessment also tracks and measures bias at a micro level so businesses can understand the level and type of bias that may previously have influenced decisions. With candidate and client satisfaction rated 95%+, it’s a game-changer for changing behaviours.
Hiring’s a team sport and we’re rewriting the rules
The ability to measure unconscious bias is just one more reason to use AI-based screening tools over traditional processes.
Everyone has a story that’s bigger than their CV.
Sapia gives every candidate an opportunity to tell theirs. Through our engaging, non-threatening process where unconscious bias can be taken out of the equation (literally!), we will help you get to the best candidates sooner.
You’ll get a shortlist of candidates with the right traits and values for your business so you can move ahead to interviews with confidence and clarity. With time and resources saved on upfront screening, your team can concentrate on making the interviewing stage more rewarding for hirers and candidates alike.
With Sapia, you can soon be on your way to building more diverse, inclusive and happier workplaces. We know we can work for your business, so we’d love to work with your business. Let’s talk.
Have you seen the Inclusive e-Book? It offers a pathway to fairer hiring in 2021.
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.
Download Inclusivity Hiring e-Book Here >
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Reinventing the Competency Framework: A Data-Driven Approach for the AI Era
We can’t hide from reality anymore. Talent needs are shifting overnight, and AI is redefining what it means to work. Traditional talent frameworks are no longer fit for purpose. At Sapia.ai, we believe the future of talent strategy lies in a smarter, fairer, and more adaptive way of defining what great looks like.
Our AI hiring platform is built on the largest proprietary dataset of interview answers globally – we’re a data company at heart, and we’ve seen the power of data-driven people methodology in transforming how organisations hire and retain good talent.
So, when it came to building a new Competency Framework that could be leveraged globally for hiring for any role at any scale, of course, we used a ground-up, data-led methodology that bridges the gap between organisational psychology and AI.
Why Rethink Competency Frameworks?
Conventional frameworks are typically crafted through expert interviews and focus groups. While valuable, they tend to be subjective, static, and too slow to keep pace with evolving job demands. As roles become more fluid and technology augments or replaces task-based skills, organisations need a new way to understand the human capabilities that genuinely matter for performance.
We wanted to identify enduring, job-agnostic competencies that reflect what drives success in a modern workplace – capabilities like adaptability, resilience, learning agility, and customer orientation.
(Why competencies and not just skills? Read why here.)
Our Approach: Where AI Meets I/O Psychology
Sapia.ai’s methodology is rooted in the science of human behaviour but powered by cutting-edge AI. We asked two core questions:
- Can we make competency discovery agile, scalable, and evidence-based?
- Can we use AI to automate the process without losing the rigour of traditional psychology?
The answer to both: yes.
We began with a rich dataset of over 37,000 job descriptions across industries and role types. Using large language models (LLMs) and advanced NLP techniques, we extracted over 200,000 behavioural descriptors. These were distilled down through a four-step process:
- Behavioural Descriptor Extraction
- Clustering and Labeling
- Cluster Analysis by I/O Psychologists
- Thematic Categorisation and Definition of Competencies
This resulted in a refined list of 25 human-centric competencies, each with clear behavioural indicators and practical relevance across a wide range of roles.
Built to Scale. Built to Adapt.
Our framework is intelligent, but importantly, it’s adaptive. Organisations can apply this methodology to their own job descriptions to discover custom competencies. This bottom-up, role-data-led approach ensures alignment to real work, not just theoretical models.
And because the framework integrates directly with our AI-powered hiring tools, you get a connected system that brings your talent strategy to life.
Our framework comes to life in the following tools:
- Job Analyser – Starting with a job description, it creates a unique competency profile for each role to build tailored structured interviews in seconds.
- Structured Chat-based Interviews that assess candidates’ responses according to the competency profile for consistent candidate assessment.
- Talent Insights Reports from every interview with deep reasoning and explainability for fair and objective hiring decisions.
- Phai Career Coach for internal mobility and employee growth that considers their competency strengths and career aspirations.
The Future of Talent Acquisition & Development is Competency-First
Skills alone cannot predict success. Competencies do. As AI continues transforming how we work, Sapia.ai’s Competency Framework offers a scalable, scientific, and fair foundation for hiring and developing the talent of tomorrow.
Want to see how it works? Download the full framework.
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It’s Time to Stop Hiring for Skills, and Start Hiring for Competencies
If you’re a CHRO or Head of Recruitment at an enterprise today, chances are you’ve been inundated with messages about the importance of “skills-based hiring.” LinkedIn’s recent Work Change Report (2025) is full of compelling data: a 140% increase in the rate at which professionals are adding new skills to their profiles since 2022, and a projection that by 2030, 70% of the skills used in most jobs today will have changed.
This is essential reading. But there’s a missed opportunity: the singular focus on “skills” fails to acknowledge the real metric that talent leaders need to be using to future-proof their workforce — competencies.
Skills vs Competencies: The Crucial Distinction
- Skills are task-specific capabilities. Think Python programming, Excel, or even negotiation.
- Soft skills refer to interpersonal or behavioural qualities like adaptability, communication, and resilience.
But skills on their own — even soft ones — are generic, disjointed, and often disconnected from real-world performance. In contrast:
- Competencies are clusters of skills, knowledge, behaviours and abilities that are observable, measurable, and context-specific.
Put simply, competencies answer the all-important question: Can this person apply the right skills, in the right way, at the right time, to deliver results in our environment?
Why Competencies Matter More Than Ever
The Work Change Report outlines a future where job titles are fluid, roles evolve quickly, and AI is a constant disruptor. This creates three massive challenges for hiring at scale:
- Roles are changing faster than static skill frameworks can keep up
- Job candidates may have non-linear, cross-functional backgrounds
- The shelf-life of technical skills is shrinking rapidly
Skills alone don’t tell us whether someone can succeed in a role that will look different 12 months from now. But competencies can. Because they measure not just what a person knows, but how they apply it.
Adaptive Talent: The New Competitive Advantage
The LinkedIn report highlights a critical insight: organisations now prioritise agility in entry-level hiring. And there’s a good reason for that. With professionals expected to hold twice as many jobs over their careers compared to 15 years ago, adaptability is not just a nice-to-have. It’s core to success.
But you can’t measure agility with a keyword on a CV. You measure it by looking at competencies like:
- Learning agility
- Change resilience
- Cross-functional collaboration
- Problem-solving in ambiguous contexts
When you shift the focus away from skills to behavioural competencies that can be defined, observed, and assessed in structured ways, you open yourself up to a much more dynamic and more useful way of managing talent.
Building a Competency-Based Talent Framework
To hire effectively at scale, particularly in a technology-driven world of work, talent leaders must shift their lens:
- Define Role-Specific Competencies: Move beyond job descriptions based on qualifications or vague skill sets. Break roles down into measurable competencies that reflect current and emerging performance expectations. This step is crucial for organisations to be able to accurately assess role-fit in the next stages. Sapia.ai does this automatically, taking job descriptions and building role-specific competency models in seconds.
- Assess Competencies Fairly and Objectively: Use structured behavioural interviews, ideally at scale. These provide a much more accurate picture of a candidate’s readiness than self-reported skills or credentials. Sapia.ai’s AI powered interviews enable competency assessment, at scale.
- Build Pathways for Development and Internal Mobility: A competency framework makes it easier to identify transferable strengths, development gaps, and future-fit potential. It gives employees clarity on how to grow within the business. Using an AI-powered coach can help ensure that talent is being continuously developed against the organisation’s competency framework.
The Future of Work Requires Depth, Not Just Breadth
LinkedIn’s data shows that people are learning more skills more quickly than ever. But the real question for talent leaders like you is: Are those skills being applied in ways that drive value? Are we hiring for task proficiency or performance?
The truth is that the organisations that will thrive in an AI-driven, skills-fluid economy aren’t the ones chasing the next hot skill. They’re the ones designing systems to identify, develop and scale competence.
Keen to Shift to Competencies, but Lacking a Framework?
Sapia.ai has developed a comprehensive Competency Framework using a data-driven approach. Download the full paper here.
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 👇