To find out how to interpret bias in recruitment, we also have a great eBook on inclusive hiring.
And then suddenly the video interview went mainstream!
Whether it’s Google Meet, Facetime or Zoom, 2020 will always be remembered as the year that video meet-ups went mainstream. It’s how kids kept up their lessons. How their parents hooked up with their personal trainers. It’s where people met up for Friday drinks. And of course, it’s the technology that enabled millions to stay connected to colleagues and clients while working from home.
And just as video has impacted so many parts of our lives and businesses, it also accelerated the adoption of video tools in contemporary recruiting.
It might be considered the next-best-thing to ‘being there’, but could video interviewing actually be filled with traps that are working against the best interests of recruiters, candidates and employers?
What is a video interview?
There are two types of video interviews:
- one-way or asynchronous video interviews – where candidates record their responses to a set of job-relevant questions.
- two-way video interviews – using one of the platforms described above or bespoke tools that connect the interviewer (or interviewing panel) in conversation with candidates.
Can video interviews really reduce unconscious bias?
Within both types of video interviews, an ability to reduce unconscious bias is promoted as a key benefit.
Unconscious bias is the sum of the inherent beliefs, opinions, cultural background and life experiences that shape how we assess, engage and interact with others.
There are several ways that video interviewing might help reduce unconscious bias:
- A consistent experience – With a structured approach to interview questions and process that provides every candidate with the same parameters. A standardised experience for every candidate can be seen to reduce bias. When questions are set, there’s little or no room for distracting small talk (in two way interviews) that may reveal bias triggers.
- No geographic or travel barriers – By interviewing all candidates in a location of their choosing, the bias of distance and the effort and expense of travel to attend an interview in person is reduced.
- Open the opportunity to more candidates – With the ability to automate video interviews and applications, recruiters can connect with many more candidates, helping to reduce the bias that may see a CV or application ignored or put aside.
The bias problem that’s staring you in the face.
As much as proponents of video screening or interviewing claim it removes bias from the process, by its very nature, the opposite is in fact true.
As soon as an interviewer or hirer sees a candidate, the blindfolds of bias are removed. No matter how aware or trained in bias the reviewers may be, images and sound can trigger bias. Additionally, it can distract attention from the things that really matter. Here are just a few things that someone talking to the camera will reveal. All possible points of unconscious bias:
- gender
- age
- skin colour
- cultural background
- visible disabilities
- attractiveness or otherwise
- what people wear – headscarves, religious jewellery, or maybe you just don’t like stripes or the candidate’s personal style
- the background of the video – are you making judgements about candidates because of their home environment or choice of art on the walls
- accents might sound ‘funny’ or strange to your ear
- candidates may have unusual voices or speech impediments that would not impact their ability to perform in the role
- you may negatively associate candidates with other people you’ve worked with or met
- the candidate may be highly nervous about ‘performing’ for the camera, affecting their ability to speak normally and communicate clearly
No rule says you need to see someone to hire them
That’s just a bias (much like the bias pre-Covid) that you need to see someone at work to know that they are doing the work.
Blind hiring means you are interviewing a candidate without seeing them or knowing them. It’s fair for the candidate and also smart for your organisation.
If you are hanging your hat on the fact you just finished bias training- research has shown consistently unconscious bias training does not work.
While we have all been dutifully attending it for years, the truth is the change factor is zero.
Video interviews vs text interviews. Which delivers blind interviewing at its best?
Sapia’s 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.
Unlike video interviewing, Sapia removes all the elements that can bring unconscious bias into play – video, visual content such as candidate photos or data gathered from social channels such as LinkedIn. Sapia even takes CVs out of the process.
Read: The Ultimate Guide To Interview Automation With Text-Based Assessments
An enjoyable and empowering candidate experience
While being ‘camera shy’ works against many candidates in video interviews, Sapia evaluates candidates with a few simple open, transparent questions via a text conversation.
Candidates know text and are comfortable using it. A text interview is non-threatening and candidates tell us they feel respected and recognised as the individual they are. They are grateful for the space and time to tell their story in their words. It’s the only conversational interview platform with 99% candidate satisfaction feedback.
Better hiring outcomes with Sapia
Beyond a more empowering candidate experience, the platform helps recruiters and employers connect with the best candidates faster and cost-effectively. The platform uses Ai, machine learning and NLP to test, assess and rank candidates according to values, traits, personality, communications skills and more.
Recruiters can gain valuable personality insights and the confidence of a shortlist with the best matched candidates to proceed to live interviews. By removing bias from the screening process Sapia is helping employers increase workplace diversity.
Does video hiring productise bias?
In recent years, we have all wisened up to the risk of using CVs to assess talent. A CV as a data source is well known to amplify the unconscious biases we have. A highly referenced study from 2003 called “Are Emily and Greg More Employable than Lakisha and Jamal?” found that white names receive 50 per cent more callbacks for interviews.
However, during COVID, we reverted to old ways in a different guise.
HR substituted CV as a data input with video interviews.
This isn’t a step forward.
Video hiring productises bias. It actually enables bias at scale.
It leads to mirror hiring – those who look and sound most like me. Instead of screening CVs in 30 seconds now, your team is watching 3-minute videos, so recruiting takes longer, and it’s exhausting.
Video platforms are being challenged in the US (EPIC Files Complaint with FTC about Employment Screening Firm HireVue) for concerns over invisible biases that may be affecting candidate fairness given the opaque nature of those algorithms. Facial recognition systems are worse at identifying the gender of women and people of colour than at classifying male, white faces. This year IBM openly pulled out of facial recognition, fearing racial profiling and discriminatory use, partly due to the questionable performance of the underlying AI.
How did we substitute one inferior and biased methodology with another that’s arguably even more biased?
We get that at some point you and the candidate need to meet, although no rule says you need to see someone to hire them. That’s just a bias (much like the bias pre-Covid) that you need to see someone at work to know that they are doing the work.
Blind hiring means you are interviewing a candidate without seeing them or knowing what school they went to, the jobs they have had. It’s a real meritocracy in that it’s fair for the candidate – and also smart for your organisation.
If you are hanging your hat on the fact you just finished bias training- research has shown consistently unconscious bias training does not work.
While we have all been dutifully attending it for years, the truth is the change factor is zero.
At a recent event attended by academics and data-loving professionals –whilst there was a welcome recognition that humans are more biased than Ai, and despite hearing that Wikipedia lists more than 150 biases we humans have – the majority of the audience still believe the impossible: that we can be trained out of our unconscious biases.
Algorithms are better at dealing with biases
The Nobel Prize winner Dr Daniel Kahneman prescribes an algorithmic approach as better at decision-making to remove unconscious biases. He claims “Algorithms are noise-free. People are not. When you put some data in front of an algorithm, you will always get the same response at the other end.” Also, see why machines are a great assistive tool in making hiring a fair process, here.
We know your inbox is flooded with Ai tools with each proclaiming to remove bias and give you amazing results and it’s tough to discriminate between what’s puffery, what’s real and what you can trust.
If your role requires you to know the difference between puffery and science, then read this. Buyers Guide: 8 Questions You Must Ask.
The 30-second due-diligence test that every HR professional should be asking when presented with one of these whizz-bang Ai tools is this:
- No data scientists in the team = not likely to be based on Ai
- No research available even under NDA to substantiate the method of assessment being used = pseudoscience or science that’s flawed if the company is not prepared to share it
- No regular bias testing to review = the Ai is likely to be biased in application
- Data used to training the models is 3rd party/ social media data = high risk of bias.
It’s critical, in fact, it’s a duty of care you have to your candidates and your organisation to be curious and investigate deeply the technology you are bringing into the organisation.
We have to be careful not to think that all AI is biased. AI is based on data, and that data can be tested for bias. ‘Data-driven’ also means transparent. Testing for bias, fairness and explainability of AI models is an active area of research and has advanced a lot. If built with best practices, AI can be used to challenge human decisions and interrupt potential biases. In the end, hiring is a human activity, and the final outcome should always be owned by a human.
Find out more about Sapia’s Ai-powered text interview platform. Also, see how we can support your best-practice recruitment needs today.
To keep up to date on all things “Hiring with Ai” subscribe to our blog!
Finally, you can try out Sapia’s Chat Interview right now HERE >
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Blog
Mirrored diversity: why retail teams should look like their customers
Walk into any store this festive season and you’ll see it instantly. The lights, the displays, the products are all crafted to draw people in. Retailers spend millions on campaigns to bring customers through the door.
But the real moment of truth isn’t the emotional TV ad, or the shimmering window display. It’s the human standing behind the counter. That person is the brand.
The missing link in retail hiring
Most retailers know this, yet their hiring processes tell a different story. Candidates are often screened by rigid CV reviews or psychometric tests that force them into boxes. Neurodiverse candidates, career changers, and people from different cultural or educational backgrounds are often the ones who fall through the cracks.
And yet, these are the very people who may best understand your customers. If your store colleagues don’t reflect the diversity of the communities you serve, you create distance where there should be connection. You lose loyalty. You lose growth.
We call this gap the diversity mirror.
What mirrored diversity looks like
When retailers achieve mirrored diversity, their teams look like their customers:
- A grocery store team that reflects the cultural mix of its neighbourhood.
- A fashion store with colleagues who understand both style and accessibility.
- A beauty retailer whose teams reflect every skin tone, gender, and background that walks through the door.
Customers buy where they feel seen – making this a commercial imperative.
How to recruit seasonal employees with mirrored diversity
The challenge for HR leaders is that most hiring systems are biased by design. CVs privilege pedigree over potential. Multiple-choice tests reduce people to stereotypes. And rushed festive hiring campaigns only compound the problem.
That’s where Sapia.ai changes the equation: Every candidate is interviewed automatically, fairly, and in their own words.
- Bias is measured and monitored using Sapia.ai’s FAIR™ framework.
- Outcomes are validated at scale: 7+ million candidates, 52 countries, average candidate satisfaction 9.2/10.
- Diversity can be measured: with the Diversity Dashboard, you can track DEI capture rates, candidate engagement, and diversity hiring outcomes across every stage of the funnel.
With the right HR hiring tools, mirrored diversity becomes a data point you can track, prove, and deliver on. It’s no longer just a slogan.
Retail recruiting strategies in action: the David Jones example
David Jones, Australia’s premium department store, put this into practice:
- 40,000 festive applicants screened automatically
- 80% of final hires recommended by Sapia.ai
- Recruiters freed up 4,000 hours in screening time
- Candidate experience rated 9.1/10
The result? Store teams that belong with the brand and reflect the customers they serve.
Read the David Jones Case Study here 👇
Recruiting ideas for retail leaders this festive season
As you prepare for festive hiring in the UK and Europe, ask yourself:
- How much will you spend on marketing this Christmas?
- And how much will you invest in ensuring the colleagues who deliver that brand promise reflect the people you want in your stores?
Because when your colleagues mirror your customers, you achieve growth, and by design, you’ll achieve inclusion.
See how Sapia.ai can help you achieve mirrored diversity this festive season. Book a demo with our team here.
FAQs on retail recruitment and mirrored diversity
What is mirrored diversity in retail?
Mirrored diversity means that store teams reflect the diversity of their customer base, helping create stronger connections and loyalty.
Why is diversity important in seasonal retail hiring?
Seasonal employees often provide the first impression of a brand. Inclusive teams make customers feel seen, improving both experience and sales.
How can retailers improve their hiring strategies?
Adopting tools like AI structured interviews, bias monitoring, and data dashboards helps retailers hire fairly, reduce screening time, and build more diverse teams.
Blog
The Diversity Dashboard: Proving your DEI strategy is working
Why measuring diversity matters
Organisations invest heavily in their employer brand, career sites, and EVP campaigns, especially to attract underrepresented talent. But without the right data, it’s impossible to know if that investment is paying off.
Representation often varies across functions, locations, and stages of the hiring process. Blind spots allow bias to creep in, meaning underrepresented groups may drop out long before offer.
Collecting demographic data is only step one. Turning it into insight you can act on is where real change and better hiring outcomes happen.
What is the Diversity Dashboard?
The Diversity Dashboard in Discover Insights, Sapia.ai’s analytics tool, gives you real-time visibility into representation, inclusion, and fairness at every stage of your talent funnel. It helps you connect the dots between your attraction strategies and actual hiring outcomes.
Key features include:
- Demographic filters – Switch between gender, ethnicity, English as an additional language, First Nations status, disability, and veteran status. View age and ethnicity in standard or alternative formats to match regional reporting needs.
- Representation highlights – Identify the top five represented sub-groups for each demographic, plus the three fastest-growing among underrepresented groups.
- Track trends over time – See month-by-month changes in representation over the past 12 months, compare to earlier periods, and connect the data back to your EVP and attraction spend.
- Candidate experience metrics – Measure CSAT (satisfaction) and engagement rates by demographic to ensure your hiring process works for everyone. Inclusion is measurable.
- Hiring fairness – Compare representation in your applied, recommended, and hired pools to spot drop-offs. Understand not just who applies, but who progresses — and why.
From insight to action
With the Diversity Dashboard, you can pinpoint where inclusion is thriving and where it’s falling short.
- See if your EASL candidates are applying in high numbers but not progressing to live interview.
- Spot if candidates with a disability report high satisfaction but have lower offer rates.
- Track the impact of targeted campaigns month-by-month and adjust quickly when something isn’t working.
It’s also a powerful tool to tell your success story. Celebrate wins by showing which underrepresented groups are making the biggest gains, and share that progress with boards, executives, and regulators.
Built on science, backed by trust
Powered by explainable AI and the world’s largest structured interview dataset, your insights are fair, auditable, and evidence-based.
Measuring diversity is the first step. Using that data to take action is where you close the Diversity Gap. With the Diversity Dashboard, you can prove your strategy is working and make the changes where it isn’t.
Book a demo to see the Diversity Dashboard in action.
Blog
Neuroinclusion by design. Not by exception.
Why neuroinclusion can’t be a retrofit and how Sapia.ai is building a better experience for every candidate.
In the past, if you were neurodivergent and applying for a job, you were often asked to disclose your diagnosis to get a basic accommodation – extra time on a test, maybe the option to skip a task. That disclosure often came with risk: of judgment, of stigma, or just being seen as different.
This wasn’t inclusion. It was bureaucracy. And it made neurodiverse candidates carry the burden of fitting in.
We’ve come a long way, but we’re not there yet.
Shifting from retrofits to inclusive-by-design
Over the last two decades, hiring practices have slowly moved away from reactive accommodations toward proactive, human-centric design. Leading employers began experimenting with:
- Sharing interview questions in advance
- Replacing group exercises with structured simulations
- Offering a variety of assessment formats
- Co-designing assessments with neurodiverse candidates
But even these advances have often been limited in scope, applied to special hiring programs or specific roles. Neurodiverse talent still encounters systems built for neurotypical profiles, with limited flexibility and a heavy dose of social performance pressure.
Hiring needs to look different.
Insight 1: The next frontier of hiring equity is universal design
Truly inclusive hiring doesn’t rely on diagnosis or disclosure. It doesn’t just give a select few special treatment. It’s about removing friction for everyone, especially those who’ve historically been excluded.
That’s why Sapia.ai was built with universal design principles from day one.
Here’s what that looks like in practice:
- No time limits — Candidates answer at their own pace
- No pressure to perform — It’s a conversation, not a spotlight
- No video, no group tasks — Just structured, 1:1 chat-based interviews
- Built-in coaching — Everyone gets personalised feedback
It’s not a workaround. It’s a rework.
Insight 2: Not all “friendly” methods are inclusive
We tend to assume that social or “casual” interview formats make people comfortable. But for many neurodiverse individuals, icebreakers, group exercises, and informal chats are the problem, not the solution.
When we asked 6,000 neurodiverse candidates about their experience using Sapia.ai’s chat-based interview, they told us:
“It felt very 1:1 and trustworthy… I had time to fully think about my answers.”
“It was less anxiety-inducing than video interviews.”
“I like that all applicants get initial interviews which ensures an unbiased and fair way to weigh-up candidates.”
Insight 3: Prediction ≠ Inclusion
Some AI systems claim to infer skills or fit from resumes or behavioural data. But if the training data is biased or the experience itself is exclusionary, you’re just replicating the same inequity with more speed and scale.
Inclusion means seeing people for who they are, not who they resemble in your data set.
At Sapia.ai, every interaction is transparent, explainable, and scientifically validated. We use structured, fair assessments that work for all brains, not just neurotypical ones.
Where to from here?
Neurodiversity is rising in both awareness and representation. However, inclusion won’t scale unless the systems behind hiring change as well.
That’s why we built a platform that:
- Doesn’t rely on disclosure
- Removes ambiguity and pressure
- Creates space for everyone to shine
- Measures what matters, fairly
Sapia.ai is already powering inclusive, structured, and scalable hiring for global employers like BT Group, Costa Coffee and Concentrix. Want to see how your hiring process can be more inclusive for neurodivergent individuals? Let’s chat.