To find out how to interpret bias in recruitment, we also have a great eBook on inclusive hiring.
Once upon a time we were all happily employed and worked in our jobs until we reached the age of 65. Then we retired with a gold watch and lived happily ever after.
While that’s not quite the way it really happened, the reality is aging workers are faced with a very different story today. While the ability to ‘retire’ seems to move further out of reach, many people are faced with the challenges of needing to work longer.
A 2020 report conducted by LinkedIn found that nearly half of the baby boomers engaged in their survey believed that their age was the main reason their job applications had been rejected by an employer.
Earlier, a 2015 survey by the Australian Human Rights Commission found that 27 per cent of older people had recently experienced or witnessed age discrimination in the workplace, most often during the hiring process.
When you think that many of those will need to work for a further 20 years, their classification as older workers seems discriminatory in itself.
While ‘ageism’ tends to be more of a problem for older workers – shouldn’t we be calling them more experienced workers? Age discrimination can also affect younger workers. Employers might discriminate against younger job seekers, for example, because they believe they won’t be committed to the role or will move on to another job quickly.
Over the past 20-25 years, the number of post-graduates achieving master’s degrees has almost doubled.
But does a potentially over-qualified ‘green’ hire necessarily trump the experience that an older employee has gained through the university of life and years working in a role?
What ‘qualifications’ have they earned and learned that formal education could never provide?
A textbook definition of age discrimination from the website of Shine Lawyers is “where a person is treated less favourably than another person of a different age in circumstances that are the same or not materially different. The person may be treated differently due to their actual age, or due to a characteristic that pertains or is imputed to pertain to persons of that age. Further, age discrimination can occur when an employer places conditions, requirements or practices that are not reasonable and have the effect of disadvantaging a person or persons of a certain age.”
While in Australia employment laws are in place to protect employees from all forms of discrimination at all stages of employment – from recruitment through to redundancy or retirement – age discrimination can creep in at any time. It can happen when decisions are being made about:
Direct discrimination is when someone is treated differently or less favourably than another person in the same situation because of their age.
For example:
Indirect discrimination can be less obvious than direct discrimination. It describes the situation where an organisation has a particular policy, job requirements or way of working that would appear to apply to everyone but which puts a person or group of people at a disadvantage because of their age.
For example:
This is when discrimination crosses a line to become dangerous – for those being discriminated against, of course, but also for the employer that risks potential criminal charges and reputational damage. Harassment happens when employers, managers or colleagues make people feel humiliated, offended or degraded.
For example:
A step up from harassment, victimisation is when individuals are treated poorly because they have made a formal complaint about age discrimination and the way they have been harassed, overlooked for promotion or otherwise discriminated against. Colleagues or co-workers who have also supported someone in their discrimination complaint may also be victimised by their managers or employers.
In a range of global jurisdictions including the US, the EU, UK and in nations across Asia-Pacific such as New Zealand and Australia, discrimination laws are designed to protect all people from age discrimination in many areas of life – getting an education, accessing services, renting a property, accessing and using public facilities… and protecting people from discrimination at work.
The laws cover all sorts of employers and employees across private sector and government, charities and associations and all part-time, full time or casual workers and contractors.
Taking positive steps to address age discrimination can help organisations attract, motivate and retain good staff while building your reputation and brand as an equal opportunity employer.
Starting with legal obligations, there are a few key areas that employers and recruiters should address to minimise age discrimination:
Perhaps the most important place to tackle age discrimination head-on is where it potentially begins and ends – in the recruitment process.
The ultimate goal in overcoming discrimination in the workplace is to build a culture that thrives on diversity and a team that values the benefits diversity brings.
Sapia helps organisations start where they intend to finish by removing the potential for a wide range of biases – including age discrimination – from top-of-funnel interview screening.
Our Artificial Intelligence enabled chat interview platform offers blind screening at its best. It solves bias by screening and evaluating candidates with a simple open, transparent interview via an automated text conversation. Candidates know text and trust text and questions can be tailored to suit the requirements of the role and the organisation’s brand values.
People are more than their CV and their age. Candidates tell us they appreciate the opportunity to tell their story in their own words, in their own time. In fact, Sapia only conversational interview platform with 99% candidate satisfaction feedback.
Unlike other pre-employment assessments, Sapia has no video hookups, visual content or voice data. No CVs and no data extracted from social channels. All of which can be triggers for discrimination and bias – unconscious or otherwise.
Sapia’s solution is designed to provide every candidate with a great experience that respects and recognises them as the individual they are. It won’t know (or care) whether a candidate is 18 or 58, male or female, tall or short, Asian or Caucasian. What it will know is whether a person is a right fit for your organisation.
This case study graph demonstrates the effectiveness of Sapia’s platform in removing age bias from the candidate shortlisting process. While Sapia specifically excludes age data from the screening process, the data listed here was extracted from the client’s ATS after the hiring process was complete to check for any bias. This data comes from HIRED people, hence the high YES rate.
The left-hand column shows the number of applicants sorted by age groupings. In this sample, there are ±500 people over 50 – a group that often reports age discrimination.
The middle column shows the percentage of people in each group who were allocated a green for go ‘yes’ recommendation for the role, an amber ‘maybe’ or a red ‘no’.
The predictive model (and corresponding Sapia scores) reveals no age bias in the process – with an equal percentage of candidates receiving a ‘yes’ recommendation in the over 60s as the under 20s. Without blind screening, and without the removal of age bias, the value and brilliance of the older candidates might otherwise have been easy to overlook or, at worse, wilfully disregarded or ignored.
While Sapia offers one of the easiest ways to provide a level playing field for all candidates, it’s one part of your overall process that should be reviewed to check for built-in age discrimination and other biases as well. Some other important considerations:
It offers a pathway to fairer hiring in 2021 so that you can get diversity and inclusion right while hiring on time and on budget.
In this Inclusivity e-Book, you’ll learn:
Download Inclusivity Hiring e-Book Here >
Find out how Sapia can help take age discrimination and other biases out of the equation in screening interviews.
It’s been a year of Big Moves at Sapia.ai. From welcoming groundbreaking brands to achieving incredible milestones in our product innovation and scale, we’re pushing the boundaries of what’s possible in hiring.
And we’re just getting started 🚀
Take a look at the highlights of 2024
All-in-one hiring platform
This year, with the addition of Live Interview, we’re proud to say our platform now covers screening, assessing and scheduling.
It’s an all-in-one volume hiring platform that enables our customers to deliver a world-leading experience from application through to offer.
Supercharging hiring efficiency
Every 15 seconds, a candidate is interviewed with Sapia.ai.
This year, we’ve saved hiring managers and recruiters hours of precious time that can now be used for higher-value tasks.
Giving candidates the best experience
Our platform allows candidates to be their best selves, so our customers can find the people that truly belong with them. They’re proud to use a technology that’s changing hiring, for good.
Leading the way in AI for hiring
We’ve continued to push the boundaries in leveraging ethical AI for hiring, with new products on the way for Coaching, Internal Mobility & Interview Builders.
Choosing the right tool for assessing candidates can be challenging. For years, situational judgement tests (SJTs) have been a common choice for evaluating behaviour and decision-making skills. However, they come with limitations that can make the hiring process less effective and less inclusive.
AI-enabled chat-based interviews, such as Sapia.ai, provide organisations with a modern alternative. They focus on understanding candidates as individuals and creating a hiring experience that is both fair and insightful while enabling efficient screening and selection.
This shift raises important questions: Are SJTs still a tool that should be considered for volume hiring? And what do AI assessments offer in comparison?
Traditional SJTs use predefined multiple-choice questions to assess behavioural tendencies and situational knowledge. While useful for screening, these static frameworks lack the flexibility to adapt based on real-world performance data or evolving role requirements.
Once created, SJTs don’t adapt to new data or evolving organisational needs. They rely on fixed scenarios and responses that may not fully reflect the dynamic realities of modern workplaces, and as a result, their relevance may diminish over time.
AI-enabled chat interviews, on the other hand, are inherently adaptive. Using machine learning, these tools can continuously refine their models based on feedback from real-world outcomes such as hiring or turnover data. This ability to evolve ensures the assessments align with organisations’ needs.
One of the main critiques of SJTs is their reliance on multiple-choice responses. While structured and straightforward, these options may not capture the full scope of a candidate’s thinking, communication skills, or problem-solving ability. The approach is often limiting, reducing complex human behaviour to a few predefined choices.
AI-enabled chat interviews work more holistically and dynamically. These tools provide a more complete picture of a person by allowing candidates to answer questions in their own words. Natural language processing (NLP) analyses their responses, offering insights into personality traits, communication skills, and behavioural tendencies. This open-ended format lets candidates express themselves authentically, giving employers a deeper understanding of their potential.
SJTs often include time constraints and rigid formats, which can create pressure for candidates. This is especially true when candidates feel forced to choose options that don’t fully reflect how they would actually behave. The process can feel impersonal, even transactional.
In contrast, chat-based interviews are designed to be conversational and low-pressure for candidates. By removing time limits and adopting a familiar chat interface, these tools help candidates feel more at ease. They also frequently include personalised feedback, turning the assessment into a valuable experience for the candidate, not just the employer.
Traditional SJTs are prone to transparency issues, as candidates can often identify and select the “best practice” answers without revealing their true tendencies. Additionally, static test designs can unintentionally embed bias; due to the nature of the timed test, SJTs have been found to disadvantage some groups.
AI chat interviews, when developed ethically within a framework like Sapia.ai’s FAIR Hiring Framework, eliminate explicit bias by relying solely on the content of a candidate’s responses. Their machine learning models are continuously validated for fairness, ensuring that hiring decisions are free from subjective judgments or irrelevant demographic factors.
Workplaces are constantly changing, and hiring tools need to keep up. SJTs’ fixed nature can make them less effective as roles evolve or organizational priorities shift. They provide a snapshot but not a dynamic view of what’s needed.
AI-enabled chat interviews are built to adapt. With feedback loops and continuous learning, they incorporate real-world hiring outcomes—like retention and performance data—into their models. This ensures that assessments stay relevant and effective over time.
As hiring demands grow more complex, so does the need for tools that can capture the whole person, not just their response to hypothetical scenarios. While SJTs have played an important role in hiring practices, they are increasingly being replaced by tools like AI-enabled chat interviews.
These modern approaches provide richer data, adapt to changing needs, and create a richer and more engaging experience for candidates. Perhaps most importantly, they emphasise fairness and inclusivity, aligning with the growing demand for unbiased hiring practices.
For organisations evaluating their assessment tools, the question isn’t just which method is “better.” Understanding the specific needs of your roles, teams, and candidates will help you choose tools that help you make decisions that are both informed and equitable.
It’s our firm belief that AI should empower, not overshadow, human potential. While AI tools like ChatGPT are brilliant at assisting us with day-to-day tasks and improving our work efficiency, employers are increasingly concerned that they’re holding candidates back from revealing their true, authentic selves in online interviews.
As an assessment technology provider, we are responsible for ensuring the authenticity and integrity of our platform. That’s why we’re thrilled to unveil the latest upgrade to our flagship Chat Interview: the AI-Generated Content Detector 2.0. With groundbreaking accuracy and a candidate-friendly design, this innovation reinforces our mission to build ethical AI for hiring that people love.
Artificially Generated Content (AGC) is content created by an AI tool, such as ChatGPT, Claude, or Pi. We initially rolled out the first version of our AGC detector last year and have continued to improve it as our data set has grown and these AI tools have evolved.
Our updated AGC Detector 2.0 achieves an impressive 98% detection rate for AI-assisted responses, with a false positive rate of just 1%. This gives organisations peace of mind that they’re getting the most authentic assessment of every candidate.
This cutting-edge system builds on Sapia.ai’s proprietary dataset of over 2 billion words, derived from more than 20 million interview question-answer pairs spanning diverse roles, industries, and regions. It’s trained on real-world data collected before and after the release of tools like ChatGPT, ensuring it remains robust and reliable even as AI tools evolve.
Our data shows that around 8% of candidates use tools like GPT-4 to generate responses for three or more interview questions. While these tools may offer a quick way for candidates to complete their interview, they can inadvertently hide a person’s true personality and potential – qualities our customers are most interested in understanding through our platform. In fact, research from Sapia Labs shows that these tools have their own personality traits, which may be quite different from the candidate applying for the role.
When a response is flagged as potentially AI-generated, the system doesn’t disqualify candidates. Instead, a real-time warning pops up, allowing them to revise their answers or submit them as-is. This ensures that candidates are encouraged to present themselves authentically, reflecting their unique communication styles and sharing their genuine experiences.
Responses flagged as AI-generated are highlighted in the candidate’s Talent Insights profile, accessible via Sapia.ai’s Talent Hub or ATS integrations. These insights give hiring teams the transparency to make informed decisions, fostering trust while accelerating hiring timelines.
“Our detection model’s strength lies in its foundation of real-world interview data collected from diverse roles and regions,” says Dr Buddhi Jayatilleke, Sapia.ai’s Chief Data Scientist. This depth of understanding enables the AGC Detector to maintain its industry-leading accuracy – even when candidates subtly modify AI-generated answers to appear more human.
The AGC Detector 2.0 embodies Sapia.ai’s commitment to ethical AI that amplifies human potential. As our CEO Barb Hyman explains:
“The hiring landscape has fundamentally changed since ChatGPT, but our commitment remains clear: AI should amplify human potential, not penalise it. This breakthrough fosters authentic hiring conversations. Our real-time warning system helps candidates make better choices and gives enterprises confidence in their selection decisions.”
The new detector has been rigorously tested on over 25,000 interview responses generated by humans and leading AI models like GPT-4, Claude-3.5, and Llama-3. The results speak for themselves, reinforcing the reliability and fairness of this game-changing technology.
By detecting AI-generated content while allowing candidates to correct their responses, our AGC Detector 2.0 ensures every applicant has the chance to put their best, most authentic foot forward when applying for a role powered by Sapia.ai. For enterprises, it provides confidence in the integrity of their hiring decisions and ensures they’re connecting with real candidates at scale.