Interview Bias: Problems, Advantages and Disadvantages of Video Interviewing

To find out how to interpret bias in recruitment, we also have a great eBook on inclusive hiring.

Last updated on October 14th, 2025

TL;DR

• Video interviewing has gone mainstream, but visuals can still trigger interviewer bias despite structured processes.
• Common risks include first impression bias, nonverbal bias, stereotyping bias, halo/horn effects, similarity and affinity bias.
• Anonymous, text-based interviews focus on assessing job requirements, candidates’ qualifications, skills, and predicted job performance.
• Standardised questions, clear scoring criteria, multiple interviewers, and broad sourcing help reduce bias.
• Algorithms can stabilise the decision-making process, but buyers should demand evidence, regular bias testing, and transparency.
• Sapia.ai’s text interview platform removes visual cues, applies consistent scoring, and accelerates fair, high-quality hiring decisions.

How the hiring process became reliant on video interviews

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 with their lessons, and how their parents connected 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.

Just as video has impacted many aspects of our lives and businesses, it has 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 work against the best interests of recruiters, candidates, and employers?

What is a video interview? Types of interview to know

There are two types of interviews used today: one-way (asynchronous) and live two-way:

• 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 reduce interview bias — or amplify it?

Within both types of video interviews, the 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. Using standardised questions and clear scoring criteria helps ensure fairness and objectivity in the interview process.
• No geographic or travel barriers – By interviewing all candidates in a location of their choice, the bias of distance and the effort and expense of travel to attend an in-person interview are 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 cause a CV or application to be ignored or set aside.

A structured approach to video interviews, such as using standardised questions and scoring criteria, not only ensures consistency but also allows for the involvement of multiple interviewers. This helps reduce individual bias by bringing in diverse perspectives and skills.

Reducing bias is further supported by implementing a scoring system and training interviewers to conduct interviews with a focus on avoiding bias. This approach can improve hiring outcomes and ensure a fairer, more objective process. Well-designed standardised interview questions and a clear scoring system can reduce bias, but visuals often reintroduce interviewer bias.

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. When an interviewer sees or hears a candidate, first impression bias, nonverbal bias and subjective factors creep into the interview process.

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.

Common forms of interviewer bias to watch:

• 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 judgments 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

Interviewers often bring preconceived notions and subjective factors into the process, which can influence their first impression and overall impression of a candidate.

Impression bias occurs when initial impressions, nonverbal cues, and subtle signals, such as body language, facial expressions, and eye contact, influence an interviewer’s perception. Cultural noise and socially acceptable responses can affect the interpretation of the candidate’s responses.

Negative information, negative emphasis, or focusing on one negative trait can lead to the horn effect, while the halo effect occurs when a single positive trait overshadows other qualities. Confirmation bias, stereotyping bias, contrast effect, and contrast effect bias can all distort the evaluation of candidates.

Generalised opinions, similarity bias, and affinity bias can lead interviewers to favour candidates who display similar traits, have similar hobbies, or with whom they discuss hobbies. Interviewers may make assumptions based on how a candidate presents themselves or behaves during the interview, and the hiring manager’s own biases can also influence the outcome.

No rule says that the interview process requires visual aid

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 refers to the process of interviewing a candidate without seeing or knowing their identity. It’s fair for the candidate and also smart for your organisation.

If you are relying on the fact that you have just completed bias training, research has consistently shown that unconscious bias training is ineffective.

While we have all been dutifully attending it for years, the truth is that the change factor is zero.

Blind interviewing: a more innovative interview method for fair hiring decisions

Sapia.ai’s AI-enabled, text chat interview platform has been designed to deliver the ultimate in blind testing at the most critical stage of the recruitment process: candidate screening.

Using standardised interview questions and an interview guide helps ensure that all candidates are evaluated based on job requirements and job-related criteria. By focusing on the candidate’s qualifications and skills, rather than visual cues, the assessment more accurately reflects job performance and suitability for the position.

Implementing a scoring system and clear scoring criteria allows organisations to identify the right candidate in a candidate-based and objective manner. Involving multiple interviewers and asking the same questions to different candidates further reduces bias and ensures fairness. Recruiting broadly from a broad range of sources and diversifying the application process improves the hiring process and leads to better hiring outcomes. A structured hiring process and decision-making process, supported by examples and an understanding of standard forms of bias, helps ensure fairness and objectivity throughout the recruitment process.

Unlike video interviewing, Sapia.ai removes all elements that can introduce unconscious bias – including video, visual content such as candidate photos, and data gathered from social channels like LinkedIn. Sapia.ai even removes CVs from 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.ai evaluates candidates with a few simple, open, transparent questions via a text conversation.

Candidates are familiar with text and feel 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 own words. It’s the only conversational interview platform with 99% candidate satisfaction feedback.

Better hiring outcomes with Sapia.ai

Beyond a more empowering candidate experience, the platform helps recruiters and employers connect with the best candidates faster and cost-effectively. The platform utilises AI, machine learning, and NLP to evaluate, assess, and rank candidates based on values, traits, personality, communication skills, and more.

Sapia.ai supports objective hiring decisions by focusing on job performance and identifying the right candidate for the role. Recruiters can gain valuable personality insights and the confidence to shortlist 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 become more aware of the risks associated with 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, titled “Are Emily and Greg More Employable than Lakisha and Jamal?” found that white names receive 50 per cent more callbacks for interviews. The study showed that caucasian applicants received more callbacks than candidates with other ethnic backgrounds, highlighting the impact of bias in the application process.

However, during the COVID-19 pandemic, 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. This is often due to similarity bias and affinity bias, where interviewers unconsciously favour candidates who display similar traits or with whom they discuss hobbies, resulting in hiring decisions based on personal similarities rather than the candidate’s qualifications. 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 have been 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. In 2020, IBM publicly withdrew from facial recognition, citing concerns about racial profiling and discriminatory use, partly due to the questionable performance of the underlying AI.

How Sapia reduces interview bias in the hiring process

We understand that at some point, you and the candidate will need to meet, although there is no rule that requires you to see someone in person 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 their educational background or previous job experience. It genuinely embodies a meritocracy in that it’s fair for the candidate – and also smart for your organisation.

If you are relying on the fact that you have just completed bias training, research has consistently shown that unconscious bias training is ineffective.

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.

When algorithms help: making the decision-making process fairer

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.” Using algorithms can help standardise the decision-making process, ensuring that hiring decisions are more objective and less influenced by unconscious biases. Additionally, learn why machines can be a valuable 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 excellent 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.

What to ask vendors: avoiding bias in AI hiring tools

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 ND, A 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
• The data used to train the models is 3rd-party/social media data, which carries a 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 must be cautious not to assume that all AI is inherently 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 in AI models is an active area of research that has advanced significantly. If built with best practices, AI can be used to challenge human decisions and interrupt potential biases. Ultimately, hiring is a human activity, and the final outcome should always be attributed to a human.

Find out more about Sapia.ai’s AI-powered text interview platform. Additionally, explore how we can support your best-practice recruitment needs today or book a demo.

To keep up to date on all things “Hiring with AI”, subscribe to our blog!

FAQs

What is interview bias?
Distortions in the interview process can skew evaluation, leading to hiring decisions that are influenced by visuals or subjective factors rather than job-related criteria and predicted job performance.

What is interviewer bias, and how does it show up?
When an interviewer’s perception is shaped by first impression cues, preconceived notions, or unrelated discussion, it affects how they rate a candidate’s responses and overall outcome.

What interview biases should we be aware of?
First impression bias, nonverbal bias (eye contact, body language, facial expression), confirmation bias, similarity bias, affinity bias, stereotyping bias, contrast effect, contrast effect bias, halo effect and horn effect.

When does impression bias occur?
Impression bias occurs at the very start, when visuals and sound trigger generalised opinions or negative emphasis based on one negative trait or negative information.

Can unconscious bias training fix this?
It can raise awareness, but lasting change comes from a structured interview method with safeguards that consistently reduce bias in the hiring process.

How do we reduce interview bias in practice?
Use standardized interview questions, a shared interview guide, clear scoring criteria, and multiple interviewers; anchor ratings to the job description, job requirements, candidate’s qualifications and candidate’s skills.

Why do multiple interviewers help?
They bring diverse viewpoints, dilute subjective factors, challenge preconceived ideas, and improve calibration so hiring decisions are based on evidence, not a single first impression.

How should we conduct interviews to be fair?
Ask the same interview questions of different candidates, maintain consistent timing, take structured notes tied to job performance, and avoid culturally loaded or socially acceptable prompts that may mask accurate responses.

Do specific signals reliably predict performance?
No — cultural noise, body language, accent or setting can mislead; focus on job-related evidence and examples that map to the position and scoring criteria.

What are the types of interviews, and which best limit bias?
One-way and two-way interviews are common types of interviews; text-based, structured formats with standardised questions typically reduce bias more than video-heavy approaches.

How do contrast effects influence ratings?
After meeting a very strong or very weak candidate, the next one may be judged against that contrast, not against the rubric — classic contrast effect and contrast effect bias.

How should hiring managers make decisions?
Follow a transparent decision-making process: rate evidence against the rubric, compare like-for-like, and document why the right candidate met the criteria — not why they “felt” perfect.

What sourcing practices support fairness before interviews?
Recruit broadly across a broad range of channels to widen the talent pool so strong candidates aren’t filtered out before the interview process even begins.

What does good vendor practice look like for bias control?
Vendors should show their decision-making process, regular bias testing, and objective data that their interview method improves consistency and outcomes.

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Laura Belfield