Back

Interview Bias Training: What Every Business Needs to Understand About Unconscious Bias in Hiring

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 >


Blog

New Research Proves the Value of AI Hiring

A new study has just confirmed what many in HR have long suspected: traditional psychometric tests are no longer the gold standard for hiring.

Published in Frontiers in Psychology, the research compared AI-powered, chat-based interviews to traditional assessments, finding that structured, conversational AI interviews significantly reduce social desirability bias, deliver a better candidate experience, and offer a fairer path to talent discovery.

We’ve always believed hiring should be about understanding people and their potential, rather than reducing them to static scores. This latest research validates that approach, signalling to employers what modern, fair and inclusive hiring should look like.

The problem with traditional psychometric tests

While used for many decades in the absence of a more candidate-first approach, psychometric testing has some fatal flaws.

For starters, these tests rely heavily on self-reporting. Candidates are expected to assess their own traits. Could you truly and honestly rate how conscientious you are, how well you manage stress, or how likely you are to follow rules? Human beings are nuanced, and in high-stakes situations like job applications, most people are answering to impress, which can lead to less-than-honest self-evaluations.

This is known as social desirability bias: a tendency to respond in ways that are perceived as more favourable or acceptable, even if they don’t reflect reality. In other words, traditional assessments often capture a version of the candidate that’s curated for the test, not the person who will show up to work.

Worse still, these assessments can feel cold, transactional, even intimidating. They do little to surface communication skills, adaptability, or real-world problem solving, the things that make someone great at a job. And for many candidates, especially those from underrepresented backgrounds, the format itself can feel exclusionary.

The Rise of Chat-Based Interviews

Enter conversational AI.

Organisations have been using chat-based interviews to assess talent since before 2018, and they offer a distinctly different approach. 

Rather than asking candidates to rate themselves on abstract traits, they invite them into a structured, open-ended conversation. This creates space for candidates to share stories, explain their thinking, and demonstrate how they communicate and solve problems.

The format reduces stress and pressure because it feels more like messaging than testing. Candidates can be more authentic, and their responses have been proven to reveal personality traits, values, and competencies in a context that mirrors honest workplace communication.

Importantly, every candidate receives the same questions, evaluated against the same objective, explainable frameworkThese interviews are structured by design, evaluated by AI models like Sapia.ai’s InterviewBERT, and built on deep language analysis. That means better data, richer insights, and a process that works at scale without compromising fairness.

Key Findings from the Latest Research

The new study, published in Frontiers in Psychology, put AI-powered, chat-based interviews head-to-head with traditional psychometric assessments, and the results were striking.

One of the most significant takeaways was that candidates are less likely to “fake good” in chat interviews. The study found that AI-led conversations reduce social desirability bias, giving a more honest, unfiltered view of how people think and express themselves. That’s because, unlike multiple-choice questionnaires, chat-based assessments don’t offer obvious “right” answers – it’s on the candidate to express themselves authentically and not guess teh answer they think they would be rewarded for.

The research also confirmed what our candidate feedback has shown for years: people actually enjoy this kind of assessment. Participants rated the chat interviews as more engaging, less stressful, and more respectful of their individuality. In a hiring landscape where candidate experience is make-or-break, this matters.

And while traditional psychometric tests still show higher predictive validity in isolated lab conditions, the researchers were clear: real-world hiring decisions can’t be reduced to prediction alone. Fairness, transparency, and experience matter just as much, often more, when building trust and attracting top talent.

Sapia.ai was spotlighted in the study as a leader in this space, with our InterviewBERT model recognised for its ability to interpret candidate responses in a way that’s explainable, responsible, and grounded in science.

Why Trust and Candidate Agency Win

Today, hiring has to be about earning trust and empowering candidates to show up as their full selves, and having a voice in the process.

Traditional assessments often strip candidates of agency. They’re asked to conform, perform, and second-guess what the “right” answer might be. Chat-based interviews flip that dynamic. By inviting candidates into an open conversation, they offer something rare in hiring: autonomy. Candidates can tell their story, explain their thinking, and share how they approach real-world challenges, all in their own words.

This signals respect from the employer. It says: We trust you to show us who you are.

Hiring should be a two-way street – a long-held belief we’ve had, now backed by peer-reviewed science. The new research confirms that AI-led interviews can reduce bias, enhance fairness, and give candidates control over how they’re seen and evaluated.

Read Online
Blog

AI Maturity in the Enterprise

Barb Hyman, CEO & Founder, Sapia.ai

 

It’s time for a new way to map progress in AI adoption, and pilots are not it. 

Over the past year, I’ve been lucky enough to see inside dozens of enterprise AI programs. As a CEO, founder, and recently, judge in the inaugural Australian Financial Review AI Awards.

And here’s what struck me:

Despite the hype, we still don’t have a shared language for AI maturity in business.

Some companies are racing ahead. Others are still building slide decks. But the real issue is that even the orgs that are “doing AI” often don’t know what good looks like.

You don’t need more pilots. You need a maturity model.

The most successful AI adoption strategy does not have you buying the hottest Gen AI tool or spinning up a chatbot to solve one use case. What it should do is build organisational capability in AI ethics, AI governance, data, design, and most of all, leadership.

It’s time we introduced a real AI Maturity Model. Not a checklist. A considered progression model. Something that recognises where your organisation is today and what needs to evolve next, safely, responsibly, and strategically.

Here’s an early sketch based on what I’ve seen:

The 5 Stages of AI Maturity (for real enterprises)
  1. Curious
    • Awareness is growing across leadership
    • Experimentation led by innovation teams
    • Risk is unclear, appetite is cautious
    • AI is seen as “tech”
  2. Reactive
    • Gen AI introduced via vendors or tools (e.g., copilots, agents)
    • Some pilots show promise, but with limited scale or guardrails
    • Data privacy and sovereignty questions begin to surface
    • Risk is siloed in legal/IT
  3. Capable
    • Clear policies on privacy, bias, and governance
    • Dedicated AI leads or councils exist
    • Internal use cases scale (e.g., summarisation, scoring, chat)
    • LLMs integrated with guardrails, safety reviewed
  4. Strategic
    • AI embedded in workflows, not layered on
    • LLM/data infrastructure is regionally compliant
    • AI outcomes measured (accuracy, equity, productivity)
    • Teams restructured around AI capability — not just tech enablement
  5. AI-Native
    • AI informs and transforms core decisions (hiring, pricing, customer service)
    • Enterprise builds proprietary intelligence
    • FAIR™/RAI principles deeply operationalised
    • Talent, systems, and leadership are aligned around an intelligent operating model
Why this matters for enterprise leaders

AI is a capability.And like any capability, it needs time, structure, investment, and a map.

If you’re an HR leader, CIO, or enterprise buyer, and you’re trying to separate the real from the theatre, maturity thinking is your edge.

Let’s stop asking, “Who’s using AI?”
And start asking: “How mature is our AI practice and what’s the next step?”

I’m working on a more complete model now, based on what I’ve seen in Australia, the UK, and across our customer base. If you’re thinking about this too, I’d love to hear from you.

Read Online
Blog

Beyond the Black Box: Why Transparency in AI Hiring Matters More Than Ever

For too long, AI in hiring has been a black box. It promises speed, fairness, and efficiency, but rarely shows its work.

That era is ending.

“AI hiring should never feel like a mystery. Transparency builds trust, and trust drives adoption.”

At Sapia.ai, we’ve always worked to provide transparency to our customers. Whether with explainable scores, understandable AI models, or by sharing ROI data regularly, it’s a founding principle on which we build all of our products.

Now, with Discover Insights, transparency is embedded into our user experience. And it’s giving TA leaders the clarity to lead with confidence.

Transparency Is the New Talent Advantage

Candidates expect fairness. Executives demand ROI. Boards want compliance. Transparency delivers all three.

Even visionary Talent Leaders can find it difficult to move beyond managing processes to driving strategy without the right data. Discover Insights changes that.

“When talent leaders can see what’s working (and why) they can stop defending their strategy and start owning it.”

Article content

Metrics That Make Transparency Real (and Actionable)

 

🕒 Time to Hire

 

Article content

What it is: The median time between application and hire.

Why it matters: This is your speedometer. A sharp view of how long hiring takes and how that varies by cohort, role, or team helps you identify delays and prove efficiency gains to leadership.

Faster time to hire = faster access to revenue-driving talent.

 

💬 Candidate Sentiment, Advocacy & Verbatim Feedback

 

Article content

What it is: Satisfaction scores, brand advocacy measures, and unfiltered candidate comments.

Why it matters: Many platforms track satisfaction. Sapia.ai’s Discover Insights takes it further, measuring whether that satisfaction translates into employer and consumer brand advocacy.

And with verbatim feedback collected at scale, talent leaders don’t have to guess how candidates feel. They can read it, learn from it, and take action.

You don’t just measure experience. You understand it in the candidates’ own words.

 

🔍 Drop-Off Rates, Funnel Visibility & Automation That Works

 

Article content

What it is: The percentage of candidates who exit the hiring process at different stages, and how to spot why.

Why it matters: Understanding drop-off points lets teams fix friction quickly. Embedding automation early in the funnel reduces recruiter workload and elevates top candidates, getting them talking to your hiring teams faster.

Assessment completion benchmarks in volume hiring range between 60–80%, but with a mobile-first, chat-based format like Sapia.ai’s, clients often exceed that.

Optimising your funnel isn’t about doing more. It’s about doing smarter, with less effort and better outcomes.

 

📈 Hiring Yield (Hired / Applied)

 

Article content

What it is: The percentage of completed applications that result in a hire.

Why it matters: This is your funnel efficiency score. A high yield means your sourcing, screening, and selection are aligned. A low one? There’s leakage, misfit, or missed opportunity.

Hiring yield signals funnel health, recruiter performance, and candidate-process fit.

 

🧠 AI Effectiveness: Score Distribution & Answer Originality

 

Article content

What it is: Insights into how candidate scores are distributed, and whether responses appear copied or AI-generated.

Why it matters: In high-volume hiring, a normal distribution of scores suggests your assessment is calibrated fairly. If it’s skewed too far left or right, it could be too hard or too easy, and that affects trust.

Add in answer originality, and you can track engagement integrity, protecting both your process and your brand.

From Metrics to Momentum

To effectively lead, you need more than simply tracking; you need insights enabling action.

When you can see how AI impacts every part of your hiring, from recruiter productivity to candidate sentiment to untapped talent, you lead with insight, not assumption. And that’s how TA earns a seat at the strategy table.

Learn more about Discover Insights here

Read Online