Written by Nathan Hewitt

Sapia welcomes the EEOC Initiative on Ai and Algorithmic Fairness

Recently the The U.S. Equal Employment Opportunity Commission (EEOC) announced it was  launching an initiative to ensure that artificial intelligence (AI) and other emerging tools used in hiring and other employment decisions comply with federal civil rights laws that the agency enforces.

This is a strong step in the right direction. As many of you are aware Sapia has long advocated for the accountability of vendors in the market around the responsible development and application of Ai hiring tools.

Removing bias is not something that any solution can provide – not even many that claim they are. It’s complex and we pioneered this ability through focussing on solving this for the last three years working with progressive customers who are focused on the same. We  have also released a framework to help hiring managers navigate the claims companies make around removing bias – it’s called the  FAIR Framework (Fairness in Recruiting)

Sapia reduces bias by fulfilling the following requirements:

  1. Sapia assessment is based on a structured interview, is fully blind and uses direct unprocessed text chat from a candidate. This is in contrast to video or audio assessments which have error rates up to 20% in transcribing voice to text, which leads to further errors and biases in input. Video and voice are also known to induce bias through seeing the candidate and hearing accents.
  2. The training data used to assess candidates is not based on any 3rd party data or historical customer hiring data and so carries no risk of latent demographic signals that could amplify bias. This purity of data gives every candidate the fairest chance of being considered  for the job.
  3. Our innovation in algorithmic bias mitigation, recognised at the global Ai conference CogX earlier this year, means that fairness is now baked directly into the model optimization at training time. 
  4. Our rule based candidate recommendation models are built on a combination of machine learning and optimization algorithms striking a fine balance between fairness, validity and expert defined “ideal candidate profile”. This is in stark contrast to the mainstream approach in many candidate screening systems that employ machine learning only models using past hiring and performance data, with bias testing as an afterthought. In our approach, being unbiased is a constraint that the model has to satisfy while finding the optimum model aligned to expert judgement and/or past hiring/performance outcomes. In other words, the algorithm is “fairness bound” in its exploration to find the most predictive model.
  5. We use two tests as constraints,  which is going beyond the EEOC guidance for adverse impact testing- – the 4/5th rule as well as Effect size.    

In contrast, video Ai tools have been legally challenged on the basis that they fail to comply with baseline standards for AI decision making, such as the OECD AI Principles and the Universal Guidelines for AI or that they perpetuate societal biases and could end up penalising non-native speakers, visibly nervous interviewees or anyone else who doesn’t fit the model for look and speech. For example, current video AI is more effective in capturing facial expressions in white males than other groups.


Transparency has been a principle and a value for us since we first started to build technology designed to fix the biased and broken hiring practices of today. 

Every customer can view their model card which shows transparently the features tested for bias that are inputs to their model, the protected groups the model is tested on, the norm data going into the model and the bias testing results. 

Additionally, the customer has access to insights related to bias through the funnel (i.e. applied, recommended and hired) via the Sapia DiscoverInsights  dashboard. We are proud to be leading the market in transparency, including sharing our own standard for ethical use of Ai in the  FAIR™ Framework released publicly in 2020 which shows our own adherence to the principles of being unbiased, transparent, explainable and valid. 

We support the principles articulated in the EEOC Guidelines and will continue to be transparent with the market and our Customers on our science, our bias mitigation regime and our results.

See our press release welcoming the EEOC announcement here.


Blind screening – the smarter alternative to situational judgement tests?

To find out how to use Recruitment Automation to ‘hire with heart’, we also have a great eBook on recruitment automation with humanity.

Situational Judgement Tests (SJTs) or Ai interview automation?

From one recruiter to another and one employer to another, the ways candidates are selected vary greatly. But ask anyone involved in the process, and most will agree that what happens at the early candidate screening stage, is critical to getting the best outcomes. Traditionally, it’s also been the most time-consuming and costly part of the hiring process.

Long before a face-to-face interview, recruiters need to screen candidates to decide, from potentially thousands of applicants, who should proceed to the next steps in the hiring cycle.

But before they’ve even met a candidate, can recruiters really assess someone’s ability and suitability for the job they’re applying for? Yes, they can.

Choosing the best assessment solution for your recruitment tools suite.

In contemporary recruiting, a suite of tools and technologies can help take the hard work and the guesswork out of the hiring process.  Talent assessment tools help recruiters identify the best candidates faster – talent who will be the best fit for the role and the team, work most productively and stay in the role longer.

While traditionally a time-consuming manual review of applications and CVs would begin the hiring process, recruiters have embraced technologies that can automate these processes from the outset.  

In this article, we compare two top of the funnel tools recruiters are using to assess candidates: traditional situational judgement tests (SJTs) and the next generation text interview platform.

Sapia Ai-enabled automated interviews could provide the answers you’re looking for, helping to connect to the best talent faster and more cost-effectively.

So, what is a situational judgement test?

Situational judgement tests are used to assess a candidate’s judgement and ability to respond appropriately to the real-world situations they would be likely to encounter in the workplace.

Candidates are presented with a workplace scenario and then they are required to choose or rank the best (or worst) paths to resolve the challenge, conflict or opportunity. They are a type of psychological aptitude test that provides insight and assessment of a candidate’s job-related skills.

What do situational judgement tests measure? Situational Judgement Test for Real World Scenarios

While the challenging scenarios presented to candidates are hypothetical, the best tests are designed around the role they are applying for.

Reflecting real situations they could encounter, the scenarios may involve working with other team members or supervisors, interacting with customers or dealing with day-to-day challenges.

Situational judgement tests date back to the 1940s. While the ways they are delivered may have changed, they remain a popular way to assess skills such as problem-solving and interpersonal skills. They are also useful in assessing soft skills and practical, non-academic intelligence.

Situational judgement tests are customised to the role and the organisation. Generally, they would be looking to assess a candidate’s aptitude for a role by measuring competencies that might include:

  • Communication skills – clarity, persuasiveness, empathy
  • Organisation and planning  – solving the problem, staying cool under pressure
  • Teamwork – collaboration, encouraging others, prioritising team needs over the individual, implementing solutions
  • Decision making – exercising discretion, analysing the situation, demonstrating solid judgment
  • Customer focus – listening, recognising, delivering
  • Initiative – taking responsibility, demonstrating leadership, stepping up
  • Ambition – drive to achieve

How does a situational judgement test work?

As they are produced by a range of different providers, SJTs can be delivered in a number of ways. As they are also tailored to suit specific roles and companies, tests can vary in their length, structure and format. While some may be paper-based ,most tests are delivered digitally. 

The tests provide candidates with a workplace scenario – as a written description or as a video or digital animation – and a challenge related to that scenario. Typically, candidates are then presented with four or five possible paths of action in multiple-choice format to deal with the situation described.

Different approaches are used for candidates to provide their answers. Some may require candidates to choose both the most desirable and the least desirable action. Others may ask candidates to choose just one preferred option or rank all actions in terms of effectiveness. 

What benefits can SJTs bring to the hiring process?

SJTs are typically used before the interview stage and often used in combination with a knowledge-based test.

SJTs are designed to help recruiters and hiring managers to:

  • filter candidates from large talent pools
  • identify candidates who are likely to perform best in the role
  • provide candidates with further insight into the demands of the role
  • identify candidates who will be a good cultural fit
  • assess candidates’ aptitude and judgement against realities of the role
  • understand a candidate’s aptitude for the particular job
  • help reduce staff turnover by making more informed decisions

Sapia – the smarter way to assess candidates  

Since 2013, Australian recruitment technology specialist Sapia has worked to solve a problem for every recruiter and employer. That is how to get to the right talent faster while consistently improving the candidate experience.

Sapia’s text-based interview platform uses artificial intelligence, machine learning and natural language processing to provide reliable personality insights into every candidate. While SJTs can be expensive time-consuming to create, administer and assess, Sapia’s platform can a like-for-like personality and job-fitness tests with far greater ease and at a fraction of the cost.

Why organisations are turning to interview automation over situational judgement tests

Here is feedback from a customer after running a pilot using SJTs:

Often SJTs don’t accurately represent what the job is really about. There are so many aspects that need to be considered within a real-world situation. Feedback from the SJTs pilot groups is that they often felt as though they were being forced into specific areas that may not be job-related. There needs to be more flexibility for a candidate to say: “I would do this, but I would also do a bit of that”. Having an experience that gives flexibility in answering. It enables candidates to have that open-ended answer to express what was important to them.

How Sapia’s interview automation works

Smart Interviewer is Sapia’s machine learning interview platform. With learning from analysing more than 165 million words in text-based interviews with more than 700,000 candidates, Smart Interviewer combines standard interview questions related to past behaviour and situational judgement to reliably assess personality traits. The questions can be customised to the specific role family – sales, retail, call centre, service etc– and specific requirements relating to the employer’s brand and employment values.

Candidate assessment at scale

Improve User Experience Situational Judgement Test

The scientific foundation of Sapia’s Ai interview platform is that language forms the framework for the knowledge, skills and personality we possess. Through a simple text-based conversation, Smart Interviewer provides valuable candidate insights. It can predict a candidate’s suitability for a role and guide their progression through the recruitment process. It delivers the insights that recruiters and employers need to make better hiring decisions at scale.

Enhancing the candidate experience – 99% satisfaction

Improving the candidate experience is a priority for every recruiter and employer. The effect of a poor experience can cause lasting damage to reputations and brands. Sapia is the only conversational interview platform with 99% candidate satisfaction feedback. Candidates enjoy the process, appreciate the opportunity and value the personalised feedback. Something that’s simply not practical with most high-volume recruitment briefs.

Candidates know text and trust text

As text is a familiar, non-confrontational way to connect, candidates enjoy the text interview experience. Unlike SJTs that lock them into choosing options from pre-determined answers, candidates appreciate the open-ended questions . Here they are empowered by the opportunity to tell their story in their words. 

While questions are customised to the role, some typical examples include:
• What motivates you? What are you passionate about?
• Not everyone agrees all the time. Have you had a peer, teammate or friend disagree with you? What did you do?
• Give an example of a time you have gone over and above to achieve something. Why was it important for you to achieve this?
• Sometimes things don’t always go to plan. Describe a time when you failed to meet a deadline or personal commitment. What did you do? How did that make you feel?
• In sales, thinking fast is critical. What qualifies you for this? Provide an example.

Tackling bias and taking CVs out of the equation

Sapia provides blind-screening at its best, effectively reducing opportunities for bias from the assessment process to ensure every candidate is playing on a level field. Candidates recognise and appreciate the opportunity to tell their story without the subjective biases of a human interview or a cursory review of their CV. For top of the recruitment funnel interviews, Sapia removes CVs from the process altogether.

Find out more about Sapia’s Ai-powered candidate assessment tool and how it could replace your time-consuming and costly SJTs today.

You can leave us your details to get a personalised demo OR try out Sapia’s Chat Interview right now, here. 

Read Online

COVID career anxiety is creating hiring bias!

We know that the global pandemic has caused a disruption in global workforces. Much has already been said about the Great Resignation, and how it has morphed into the Great Reshuffle, a period in which many are looking to reinvent themselves in the light of new jobs and careers. No industries or role types have been spared, either, it seems – even recruiters are leaving positions in the tens of thousands.

With a reshuffle, however, comes uncertainty, doubt, and anxiety. The war on talent may have benefited some, but the path to career reinvention is by no means guaranteed. Consider the following factors, factors job-hunters must face every day:

  • Bias in recruitment. According to a recent survey, 65% of tech recruiters believe their hiring process is biased. You may not get a fair shake, and you may not ever know why.
  • Ghosting. According to CandE research, In 2020, 33% of candidates in North America who completed job applications had still not received a response more than two months later.
  • Unfair competition. 78% of people admit to misrepresenting themselves on their resume.
  • Threats to longevity and progression. According to Harvard Business Review, almost two thirds of the tasks that a manager currently does may be automated by as soon as 2025.
  • Changes to the very nature of work. Noted future-of-work columnist Dror Poleg said it best: “It is not just where or when we work that is changing; it is the nature of work itself. For a growing number of people, work is becoming indistinguishable from leisure. In some cases, the workers don’t even know they are working. In others, workers think they are working while they are, in fact, resting. In the emerging world of work, video gamers are getting paid to play games, and fans are paid to listen to music.”

It’s little wonder that some Great Reshufflers, especially emerging adults (ages 18-24), are experiencing anxiety about working in the post-COVID world. Instability is the only constant. Consider, too, that some people are better at dealing with uncertainty – or, in technical terms, they are higher-than-average in the HEXACO personality traits Flexibility (or Adaptability, as it’s sometimes known).

This hypothesis is supported by at least one study, published last year in the International Journal of Social Psychiatry. It suggested that, “…due to the outbreak of ‘Fear of COVID-19’, people are becoming depressed and anxious about their future career, which is creating a long-term negative effect on human psychology.”

How this translates to good (or not-so-good) candidate experience

The traditional face-to-face interview is typified by stilted small talk and a general air of nervousness. If a candidate is low in Extraversion, high in Agreeableness, or high in the Anxiety and Fearfulness scales of the Emotionality personality domain, their experience of walking into a blind interview is likely to be worsened by the additional stressors left by COVID-19. 

Consider, as is likely to be the case, that the candidate might possess a combination of all three traits, in the proportions laid out above. These people, especially if they are young, may not even bother to apply for a job in today’s climate. 

The ramifications of this are obvious: You risk, at best, filling your workforce with open, disagreeable, type-A employees. At worst, you risk baking unfairnesses or bias into your recruitment process, at the cost of good candidates who don’t shine in awkward face-to-face situations.

How good candidate experience data, and talent analytics, can help you ease gender biases at the top of your hiring funnel

Take this small data visualisation from our TalentInsights dashboard as a key example. Please note here that the following results apply to the outcomes of the hiring process, and not Smart Interviewer’s recommendations.

HEXACO personality data in recruitment | Sapia recruitment Ai software

It presents an assessment of candidate hiring outcomes according to key HEXACO personality traits. The red dots represent female candidates, the blue dots male. Immediately, we can see that when it comes to Conscientiousness – one of the best predictors of workplace success – females and males are more or less identical.

The main differences between the two genders occur, however, in the domains of Agreeableness and Emotionality. Combined, these two traits are good predictors of anxiety and/or aversion to fear. As you can see, females tend to be higher in Agreeableness and Emotionality than males. 

Though the difference is not incredibly significant, it is still present – and it may require a slight change to the way you bring female candidates into your hiring process. The data proves, of course, that your best candidates are just as likely to be female as male – but your recruitment tactics may be producing outcomes that favour males.

How to account for fear, anxiety, and Agreeableness in your recruitment process

We’ve said it before, and it’s the whole reason we exist: A blind, text-based Chat Interview with a clever, machine-learning Ai. Smart Interviewer is our smart interviewer, and it has now analysed more than 500 million candidate words to arrive at the kinds of data points you see above. It helps you combat bias at the top of your funnel, and gives you the Talent Analytics you need at the bottom.

And it works. Take it from the candidates high in Agreeableness:

“I have never had an interview like this online in my life… able to speak without fear or judgement. The feedback is also great to reflect on. I feel this is a great way to interview people as it helps an individual to be themselves and at the same time the responses back to me are written with a good sense of understanding and compassion also. I don’t know if it is a human or a robot answering me, but if it is a robot then technology is quite amazing.”

– Graduate Candidate A

“[It was] approachable, rather than daunting. I found the process to be comprehensive and easy to complete. I also enjoyed that the range of questions were different than those commonly asked. The visual aspects of the survey makes the task seem approachable rather than daunting and thus easier to complete.”

– Graduate Candidate B

The future of work is uncertain. But with a fair and unbiased assessment tool, you can prevent the best talent from being lost under the dust of the Great Reshuffle – and save a lot of time and money doing it.

Read Online

The North Star in Graduate Recruitment – Hiring For Values

When you search ‘hire for values’ on Google, about 424m search results come up. HBR, and every other respectable HR journal has covered this topic at length.

But what does it mean and how do you do it at scale? And then how do you signal your values to incoming applicants?

For some organisations, ‘hiring for values’ could translate as including your values video on your careers page, showing the video at campus presentations or do as Atlassian does and hand out your values as temporary tattoos!

None of those PR stunts helps you hire for your values. What CHROs and their CEOs crave is the ability to embed their organisation’s values in their key people processes – in hiring and promotion decisions where values-driven decisions make the biggest impact on your culture. In graduate recruitment, that can be challenging given the hiring rates can be 2-5% of your applicant pool. This is where technology can help. Read on to see how easy it is to embed your values in recruitment using AI-led assessment technology.

Embedding your values in your hiring decisions typically means hiring for traits, based on the proposition that who you are as a person counts for as much as what you know at any point in time.

In graduate recruitment, this usually means looking for qualities like grit, curiosity, drive, emotional intelligence and the willingness to take accountability to make things happen.


See how AI can reveal these traits for every graduate applicant from analysing text responses to 5 open-ended questions. Contact us here

Read Online