Written by Nathan Hewitt
Introducing InterviewBERT: A world-first algorithm for better interviews
Sapia labs, our R&D department, has developed a world-first innovation that will help us deepen our understanding of the contextual meaning of words in written job interviews. Called InterviewBERT, this algorithm combines Google’s model for Natural Language Processing (NLP) with our proprietary dataset of more than 330 million words. BERT, meet Smart Interviewer. Together, they’ll usher in a new generation of pre-employment assessment tools and recruitment software solutions.
Put simply, InterviewBERT makes Smart Interviewer, the most sophisticated conversational Ai in the world. Ours is no simple chat-bot – already, Smart Interviewer is capable of discovering personality traits and communication skills, accurately and reliably, using a candidate’s written responses. With InterviewBERT, Smart Interviewer will learn more about candidates than ever before, faster than ever before. With this speed and accuracy also comes reductions to the unfairnesses and biases that plague the hiring process.
Why, and how, are we the first to transform pre-employment assessment technology with BERT?
Through sound Ai infrastructure, we have been able to accumulate a vast and accurate dataset. This dataset grows by the minute – we interview a new candidate every 30 seconds – and, coupled with the expertise of our Sapia labs team, we can assess candidate suitability for a role in milliseconds.
“The smartest companies know that the fairest and most accurate way to assess someone’s suitability for a role is through a structured interview,” our CEO, Barb Hyman, said. “Text increases accuracy and speed of assessing candidates, while removing biases that come through voice or video interviews.”
Dr Buddhi Jayatilleke, Chief Data Scientist and head of Sapia labs, said the team is excited at the finding that InterviewBERT had such a profound impact on trait accuracy.
“Written language encodes personality signals predictive of ‘fit’,” Dr Jayatilleke said. “The ability to understand people through language has limitless applications, and we are excited to keep inventing more ways to use language data for our customers.”
Dr Jayatilleke said decades of research had confirmed that language has long been seen as a source of truth for personality.
“What our R&D team has proven is just how powerful language data is when you combine it with enormous data volumes and scientific rigour,” he said. “This capability can be used for assessment and for offering personalised career coaching – a game changer for job seekers, universities, and employers.”
Sapia labs will present its findings from a new research paper, Identifying and Mitigating Gender Bias in Structured Interview Responses, at a SIOP symposium in April.
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When unconscious bias becomes a conscious bias
unconscious bias
A perfect example of unconscious bias manifesting in a conscious and damaging way.
At Sapia we are attuned to research and stories around bias – for most of us, it’s the reason we work here.
Our team has observed the speed with which the blame for Coronavirus has targeted an entire ethnicity.
In this case, I’ve heard some say, “it’s not racism, people are genuinely scared of the spread of the virus. It’s a deadly virus. As it originated in China people naturally worry about anyone from China”.
Unfortunately, this is the very definition of bias.
A flawed logic that seems sensible on the surface, nothing but pure stereotyping underneath. Simply, everyone who looks Chinese are not recent travels from China.
Australia is home to 1.2mil Chinese origin Australians according to the 2016 Census. Should we worry about all of them? Bias has no place in fighting any problem, even when it is a deadly virus. It only creates stress and disharmony.
The irony is this: the virus is a true fair operator. It has no racial preferences.
At the beginning of this week, one of our team who had come down with a cold shared he would work from home, to keep the team safe from his contagion.
We laughed at the time about him being a carrier of Coronavirus. By the end of the week, members of our team with holidays booked to visit family and travel in China during the Easter break had cancelled their trip.
They did this before Qantas stopped their direct flights and before the Australian government announced that Chinese people won’t be allowed back into Australia.
The team member who had a cold this week is Sri Lankan by birth. I guess that means we would have all been safe if he turned up to work as he is the ‘right’ ethnicity.
We are on a mission: To solve issues of bias in hiring
As a white immigrant myself, I don’t experience those prejudices. I have had career and life opportunities beyond my dreams, unfettered by racial bias.
Building a technology that gives equivalence to such career opportunities is why we work for our company. Some of our team have been screened out of job openings. Maybe they had the wrong name, went to the wrong school or just didn’t look like a cultural fit?
Unfortunately, AI hiring tools can be biased
Not all AI is equal. HireVue, an AI-driven recruitment company, has recently been taken to the US Federal Trade Commission with a prominent rights group claiming unfair and deceptive trade practices in HireVue’s use of face-scanning technology to assess job candidates’ “employability.”
Using video is an obvious problem as a data source for reasons around race and gender and their associated biases, but you might be surprised to know that CV’s can be just as flawed and are in much broader use as a first parse for algorithms.
How does AI solve the issues of discrimination and bias in recruitment?
At Sapia, we rely on a simple open, transparent interview via a text conversation to evaluate someone for a role. No visuals, no CV data. No voice data as that too carries the risk of bias. Neither do we take data from Facebook. Using nothing that the candidate does not know about.
Bottom line, testing for bias and removing it from algorithms is possible. Whereas for humans, it’s not.
If you want to learn more about how we test for bias and why bias testing is critical to an AI screening tool get in touch here.
No amount of bias training will make you less biased. Maybe that’s one reason why using machines to augment and challenge decisions is fast becoming mainstream.
It certainly helps to reduce the impact of unconscious bias in hiring decisions.
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Four ways recruitment automation is giving candidates a more human experience
To find out how to improve candidate experience using Recruitment Automation, we also have a great eBook on candidate experience.
New insights from Aptitude Research suggest recruitment automation can play a much greater role in talent acquisition than just improving efficiency for hiring managers, it can also make the interview process more human for candidates.
The research shows that when you shift the focus from an employer-driven view to a candidate-first view, then it is possible to reduce bias in hiring and improve the overall human element of talent acquisition.
For most companies, the value of automation is perceived through the recruiter and hiring manager experience, with the benefits to the candidate often ignored. However, recruitment automation has to be about more than simply moving candidates through the process quickly to have any significant benefit to a company.
When you focus on the impact and experience of the candidate, the benefits to both recruiters and candidates can significantly improve through recruitment automation. This approach has given rise to a movement called humanistic automation technology.
But humanistic automation sounds like an oxymoron right? Is it even possible?
The Aptitude Research showed not only is this possible, but that when Ai is used this way, it creates personal connection at scale, and works to reduce bias, something no other technology or even human-centred solution can deliver.
So, how exactly does it do this?
Here are four main areas of talent acquisition that candidate-focussed recruitment automation improves on,and how it achieves this:
1. Connection
There have been some slight improvements in building connections through the hiring process recently, but only 50% of companies have a single point of contact for communication, which results in candidates feeling engaged or valued through the process.
Recruitment automation with a candidate-focus means that communication is personalised for high-engagement with the ability for the conversation to adapt to what it learns about a candidate almost immediately.
As a candidate finding out that you are not successful is tough, and worse, most companies just ghost those they don’t wish to move ahead with. Automation can ensure that every candidate is engaged and cared for even when they are not moving forward in the process – and that doesn’t mean a standard rejection email. Ai can deliver highly personalised communication that builds connection even for those unsuccessful in their application.
2. Inclusivity
Although some companies have made efforts to remove bias from resumes, companies still have a lot of work to do on inclusion. For starters, many are relying on training programs, which have shown to be largely ineffective in delivering long-term change.
It’s true that recruitment automation can amplify bias, but automation that works to reduce bias is continually testing against biases in the system and has been shown to be effective in reducing the impact of bias in hiring decisions. Somethings humans cannot do (we’re inherently biased, whether we like it or not).
When you have the right data input gathered through blind screening and blind interviews – that don’t rely on CV data – then you can help companies achieve an equal and fair experience to all candidates.
Want to remove bias from recruitment and not just talk about it?
Download the Inclusive Hiring e-Book here
Inclusive hiring is not limited to gender and race. Companies need a broader view of diversity, equity, and inclusion that includes individuals with disabilities and neurodiversity. This requires the right digital tools and technology to ensure that candidates have a positive experience. In many cases, chat and text are more inclusive over video or even phone screening and interviews for these candidates.
3. Feedback
Most companies see feedback as a risky area and something they have no ability to do in a fair and timely manner. Essentially this is a lost opportunity for learning and development.
When you see feedback as a value proposition of an employer brand, its power in transforming your TA strategy becomes clear. Recruitment automation allows companies to deliver personalized feedback building trust and strengthening your employer brand.
Personalized feedback with tangible action items, means that candidates feel empowered even if they are rejected. Technology can help to deliver these action items in a human way, that even humans are not able to do at scale or even very well.
These insights are only made possible through natural language processing and machine learning that work in the background to reveal important information about the candidate. When a candidate feels like they are ‘seen’ that can be a transformational moment in their career paths.
Only recruitment automation can deliver individual feedback to everyone who takes time to do a job interview.
4. Trust
In an era of growing awareness around the privacy of data, only 1 in 4 candidates trust the data being will be used to drive hiring decisions. As companies look at recruitment automation through a candidate-centric lens, they must consider both the quality of the data they use and how to build trust between employers and candidates.
The biggest mistake that most companies make is using the wrong data. Resume data is not necessarily an indicator of performance or quality of hire.
Ethical Ai is something that hiring managers need to understand and use to evaluate providers. Providers using ethical Ai operate transparently, are backed by explanations, describe their methodology, and frequently publish their data.
Aptitude Research found that when data is transparent, it increases the trust in talent acquisition leaders, hiring managers, and senior leaders. With data transparency, 84% of talent acquisition leaders stated that they trust the data, and 78% of senior leaders trust the data.
Talent acquisition transformation has accelerated the demand for recruitment automation.
55% of companies are increasing their investment in recruitment automation this year. These companies recognise that automation can improve efficiency, lift the administrative burden, reduce costs, and enable data-driven decisions.
This report focuses on a new look at automation through the eyes of the candidate
After all, automation is more than moving candidates through a process quickly. It should also enable companies to communicate in a meaningful and inclusive way and build trust between candidates and employers.
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Top 3 recruitment trends for 2020
The must-know trends for smart HR professionals in 2020
1. Employers are prioritising the candidate experience
In an increasingly competitive market for talent, organisations need to create beautiful recruitment experiences that turn top candidates into employees.
The working landscape is changing: Gen Z are entering the workforce and millennials are expected to make up 50% of the workforce by 2020. They have grown up with technology and expect a seamless, tech-enabled recruitment journey. Mobile plays a key role in effective recruitment strategies. 46% of Gen Z and 38% of employed millennials have applied for a job via a mobile device, and candidates read 98% of text messages – compared to just 22% of emails.
Gerard Ward is no stranger to creating a great candidate experience. As the CEO of video interviewing platform Vieple and co-founder of psychometric assessment platform Testgrid, he’s seen how leading organisations use technology to craft candidate journeys.
“Candidates expect to have a great experience. When we try to buy something online, if the experience is not mobile optimised it turns us off,” says Ward. “Candidates expect the same consumer-level experience across the board from every organisation. A mobile-optimised experience has got to be at the front of an organisation’s recruitment model.”
Employers that are able to create an exceptional candidate to employee experience have their pick of talent. People who are satisfied with their candidate experience are 38% more likely to accept a job offer. An astounding 87% of candidates say a great recruitment experience can change their mind about a company. Also, 83% of talent say a negative interview experience can change their mind about a role/company they liked.
2. Organisations are hiring for soft skills
Organisations are shifting their focus to hire for soft skills as a number of factors converge to drive demand for agile, collaborative thinkers.
It’s been debated how appropriate the term ‘soft skills’ is to refer to crucial attributes like collaboration, agility and communication. Some propose a move to calling them ‘essential skills’, while researchers at Deloitte, prefer ‘skills of the heart’.
Faced with a national skills shortage that’s predicted to grow to 29 million skills in deficit by 2030, soft skills are the currency of the future. In fact, two-thirds of jobs created in the next ten years are expected to be strongly reliant on skills like communication and empathy.
Candidates who exhibit essential skills are being hired into flexible organisational structures – rather than a specific team. In an age of automation, where 25-46% of current work activities in Australia could be automated in the next decade, the role you hire into may not exist in a year. Flexible, agile workers will be able to upskill and cross-functionally move into new and emerging roles in response to industry disruption.
Ward observers there’s one major barrier to hiring for soft skills: hiring managers themselves. “Hiring managers want candidates from the right unis, with the right test scores and degrees,” he says. “Recruiters need to educate hiring managers. Additionally, they need to bring them on the journey about why it’s okay to bring talent in from different industries and backgrounds.”
3. AI matures – but still has a way to go
With up to 46% of current work activities in Australia under threat of automation in the next decade, there’s clearly some anxiety about the future of work. But rather than seeing that as a threat to our jobs, researchers at McKinsey go as far as to say this will “help drive a renaissance in productivity, personal income and economic growth.”
Despite the great promise of AI, 23% of HR professionals surveyed in recent IBM research were concerned that AI in HR could perpetuate or even increase biases in hiring and talent development. While AI does not bring biases to the candidate screening process, this does not mean it makes wholly unbiased decisions. AI is still reliant on the programming choices of the people building it, as well as biases that exist in the datasets it’s modelled on. If carefully designed, AI can reduce overt and unconscious biases in the recruitment process.
AI can be leveraged throughout the candidate journey to free HR teams from tedious, manual processes and enhance the candidate experience.
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