Remote work is not going away. The bonus of remote work becoming ‘a thing’ is it enables you to go further afield for talent. Broadening the candidate pool means you get even more diversity and can interview the world to find the best talent.
For fully remote businesses like Github, Automattic, with over 1000 remote workers spread across 75 countries, remote work is all about unleashing productivity.That comes from asynchronous work that needs asynchronous communication. Forcing people to do video meetings risks drowning out those team members who don’t thrive in a live group setting. The introverts. The deep quiet thinkers. The ones who prefer to reflect on an issue and not be forced into making a contribution because everyone else is on Zoom right now.
Make it the way you do things. The way you define a business problem, debate the key issues, and fast track from idea to execution.
Jeff Bezos cottoned on to this years ago. This new superpower, how you write, whether via text, Slack, Wiki or on Google docs also impacts your hiring processes. At what point do any of us test for written communication skills? If you want to hire people who can work autonomously, be productive and who can collaborate, you need to test their text communication.
What may not be known to many people, is that testing for all of this – written fluency, clarity of thought, can all be done via text analysis in the hiring process. Testing should not be just limited to the skill of writing, but also to the motivation behind expressing something in writing. This requires more effort and thinking than speaking it out. If someone is not motivated to express themselves in writing when a job is on the line, you can assume what it might be like once they are working in a role.
The power of Natural Language Processing (NLP) based machine learning models that can tell you all of this immediately is here today. From just 300 words, we can infer writing skills, personality traits and job-hopping motive. This really means there is no excuse for not hiring for the key skills required for remote work right now.
“Language is a mirror of mind in a deep and significant sense. It is a product of human intelligence. By studying the properties of natural languages, their structure, organisation, and use, we may hope to learn something about human nature; something significant, …” (Noam Chomsky, Reflections on Language, 1975)
You can try out Sapia’s FirstInterview right now, or click here to book a demo.
Suggested reading:
https://sapia.ai/blog/data-and-diversity-hiring-patterns/
In other news:
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To find out how to interpret bias in recruitment, we also have a great eBook on inclusive hiring.
In the late 1970s, as the world was changing around them, the Toronto Symphony Orchestra realised they had a problem. Specifically, a white male problem; the profile of nearly every musician.
In what is largely seen as the genesis of the blind interview, in 1980 the orchestra changed their audition process completely. Musicians were placed behind a screen so the auditioning panel couldn’t know the gender, race or age of the musician they were listening to. It’s said they even put down the carpet so the sound of high heels on the stage could not be heard.
All the panel could hear was the music.
Of course, the result of this blind screening was profound. Hiring decisions were made on the quality of the performance only. In just a few short years, the ‘white male’ orchestra was transformed to more equal gender representation with musicians further diversified by their cultural backgrounds.
Not only has the Toronto Symphony Orchestra continued to use blind screening ever since, but it was also quickly adopted by most major orchestras around the world.
Beyond the concert stage, blind screening and blind recruitment practices are used by government, academic and business organisations globally. Because when it comes to identifying the best qualified or best-fit candidates, all you need to hear is their ‘music’.
Are tall people more likely to get higher paid roles? Do the best looking candidates always get the job? Will Michael or Mohamed be the best fit for your team?
While it’s easy to recognise bias in other people, it’s usually harder to admit that we are biased ourselves. That’s why it’s called unconscious bias. It’s something we all have and something we can all be affected by.
Unconscious bias is about making assumptions, stereotyping or a fear of the unknown in how we assess other people. It can be innate or it can be learned and it’s created and reinforced through our personal experiences, our cultural background and environment.
Think of gender bias, ageism, racism or name bias – these are some common biases that need no explanation. However, psychologists and researchers have identified over 150 types of bias that impact the way we form opinions and make judgements about people, often instantly.
In a two year study titled Whitened Résumés: Race and Self-Presentation in the Labor Market published in the Administrative Science Quarterly in 2016, academics from the University of Toronto and Stanford University looked at racial and gender bias during resume screening.
In one US study, they created and sent out resumes for black and Asian candidates for 1,600 advertised entry-level jobs. While some of the resumes included information such as names, colleges, towns and cities that clearly pointed out the applicants’ race or status, others were ‘whitened’, or scrubbed of racial clues.
Amongst many insights, they found that white-sounding names were 75% more likely to get an interview request than identical resumes with Asian names and 50% more likely than black-sounding names. Males were 40% more likely to get an interview request than women.
Still need convincing?
Another 2016 study by The Institute for the Study of Labor (IZA) in Bonn, Germany examined how ethnicity and religion influenced a candidate’s chances of landing an interview. 1500 real employers received otherwise identical applications, complete with a photo, from Sandra Bauer, Meryem Ӧztürk, or Meryem Ӧztürk wearing a headscarf.
These are just two of many research studies that suggest bias and discrimination are rife in the hiring process. In a 2017 UK study, only a third of hiring managers felt confident they were not biased or prejudiced when hiring new staff, while nearly half of those surveyed admitted that bias did affect their hiring choice. 20% couldn’t be sure.
When it comes to hiring, we all have our own thoughts about what an ideal candidate is supposed to look like. The problem is that our own bias can get in the way of the right decision.
If you’ve already pre-determined a candidate’s suitability by their age, gender or the school they attended, then you could be missing out on employing the candidate with the best qualifications. Or while you’re thinking about the best ‘cultural fit’ for your team, you’re actually missing the opportunity for the best ‘cultural add’.
But what if you could take bias out of candidate screening and hiring process? Is that even possible?
Just as the Toronto Symphony Orchestra hid the identities of auditioning musicians behind a screen, there are several ways to bring blind hiring to your recruitment process:
Nearly all hiring decisions will involve a human to human interview. But take a step back in the process and blind screenings can ensure that all candidates are competing on a level playing field. With the opportunity to be assessed only on qualifications or skills, the best candidates for a role can be identified.
Blind screening is about making candidates anonymous – removing details from applications or CVs that reveal details that may colour the recruiter or hirer’s assessment. It makes it easier to make objective decisions about a candidate based on skills, experience and suitability without the distraction (and the damage!) of bias.
Unconscious bias can be triggered by someone’s name, their gender, race or age, the town they grew up in or the schools they attended.
Before making a final decision, many employers like to test a candidate’s skills or knowledge by setting a task or challenge. Others undertake personality or other testing to assess a range of relevant qualities such as aptitude, teamwork, communication skills or critical thinking. Candidates can be assigned an identifying number or code to retain their anonymity through blind testing, though this is often best done through a third-party service provider.
With face-to-face, phone or video interviews, it’s clearly impossible to keep candidates anonymous. Blind interviewing is possible, however, using a written QandA format or by using next-generation chatbots or text-driven interview software. Most recruiters and employers would agree, however, that there would be few if any, times it would be appropriate to make hiring decisions based solely on blind interviewing and without an in-person interview.
Read: The Ultimate Guide to Interview Automation
Sapia is a leading innovator and advocate in using technology to enhance the recruitment process. Our 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.
Firstly, you will never have to read another CV again. Especially in bulk recruiting assignments, Sapia can help recruiters find the best candidates faster and more cost-effectively. CV’s are littered with bias-inducing aggravators. With Sapia, blind interviews are at the top of the recruiting funnel, not CV reviews.
By removing bias from the screening process, we’re helping employers to increase workplace diversity. It also delivers an outstanding candidate experience.
Reviewing and screening CVs is the most time-consuming part of any recruiter’s job and Sapia can put more hours back in your day.
Sapia evaluates candidates with a simple open, transparent interview via a text conversation. Candidates know mobile text and trust text.
Our platform removes all the elements that can bring unconscious bias into play – no CVs, video hook-ups, voice data or visual content. Nor do we extract data from social channels.
What candidates do discover is a non-threatening text interview that respects and recognises them for the individual they are, providing them with the space and time to tell their story in their words.
As candidates complete and submit their interview, the platform uses artificial intelligence and machine learning to test, assess and rank candidates on values, traits, personality, communications skills and more. By bringing this blind interview into the upfront screening, recruiters can gain valuable personality insights and the confidence of a shortlist with the very best matched candidates to proceed to live interviews.
The platform has a 99% satisfaction rate from candidates and they report they are motivated by the personalised feedback, insights and coaching tips that the platform provides, along with the opportunity to provide their feedback on the process.
Free from biases of the candidate’s race, gender, age or education level, Sapia’s platform delivers blind interviewing, testing and screening in one. Helping to build workplace diversity brings benefits for everyone – it can help lift employee satisfaction, boost engagement and productivity and enhance the reputation of your business as a great employer.
We believe there is a formula for trust when it comes to interviewing …
Final human decision supported by objective data. Or more simply:
Trust = (Inclusivity + Transparency + Explainability + Consistency) – Bias
Find out more about our AI-powered blind recruitment tool and how we can support your hiring needs today. You can try out Sapia’s Chat Interview right now – here. Else you can leave us your details to receive a personalised demo
It offers a pathway to fairer hiring. Get diversity and inclusion right whilst hiring on time and on budget.
In this Inclusivity e-Book, you’ll learn:
MELBOURNE, Jan 18, 2021 – Sapia (https://sapia.ai/), an Australian technology company that has pioneered transparent AI-assisted hiring solutions, today announced the global release of its Fair Ai for Recruitment (FAIR™) framework to educate HR executives in assessing Ai technology for use in their organisations, as well as act as spark conversations for Ai developers in the space: https://sapia.ai/fair-ai-recruitment-framework/
The framework has been released to begin conversations around transparency in HR technology against an explosion of Ai solutions in the sector, with many using algorithms that operate in a ‘black box’. The absence of any form of accreditation of vendors, and the fact that regulation is light years behind tech innovation, has meant a lack of collaboration among vendors to champion Ai ethics in the sector, something Sapia hopes to help change.
The Fair AI for Recruitment (FAIR™) framework :
– Focuses on establishing a data-driven approach to fairness that provides an objective pathway for evaluating, challenging and enhancing fairness considerations.
– Includes a set of measures and guidelines to implement and maintain fairness in AI based candidate selection tools.
-For hiring managers and organisations, it provides an assurance as well as a template to query fairness related metrics of Ai recruitment tools.
-For candidates, FAIR™ ensures that they are using a system built with fairness as a key performance metric.
In launching the framework, Sapia CEO Barb Hyman said: “We have created a framework that we hope can be used as inspiration to ensure that Ai is being used to build inclusive teams – something humans are not capable of doing on their own because we cannot subvert our biases.”
“Our mission is to help HR leaders make bias interruption more than rhetoric, which is why we also published this guide to Making inclusion an HR priority, not a PR one”.
Sapia has become one of the most trusted mobile-first Ai recruitment platforms, used by companies across Australia, India, South Africa, UK and the US, with a candidate every two minutes engaging with their unique Ai chat bot Smart Interviewer.
What makes their approach unique it it’s disruption of three paradigms in recruitment -candidates being ghosted, biased hiring and the false notion that automation diminishes the human experience.
The end result for companies – bias is interrupted at the top of the funnel, your hiring managers make more objective decisions empowered by Smart Interviewer their co-pilot, inclusivity is enhanced, and your hired profile starts to look more like your applicant profile.
Barb Hyman, CEO
barb@sapia.ai
I am not a CFO but surely every CFO out there is encouraging, if not mandating, that their leaders look for investments that keep delivering business value (over those that are a sunk cost, or a one-time use).
I am a CEO though, and I like to ask the same question around meaningful data that keeps delivering value to a business. Because I am a CEO of a HR Tech company solving for human recruitment at scale, I also ask this question about meaningful recruitment data.
Sure HR departments are drowning in data, but it’s often not the right data.
Meaningful recruitment data isn’t:
Meaningful recruitment data:
Think about a candidate who completes a typical assessment and then gets hired. Usually, that’s the end of the data story. Josh Bersin reckons about $2bn a year are spent on these ‘disposable’ assessments. Each time one of these assessments is used it is a sunk cost. The data goes into the system and stagnates there, never to be used again.
Wouldn’t you love to know what your newest hire is capable of, beyond the job they’ve been hired for? What other roles they could fill as business needs change? Or say you need 1,000 contract tracers fast? Or your business plan calls for 200 agile coaches or 50 product managers immediately?
If you don’t have easily accessible data on your employees’ aptitudes, their strengths and underutilized skills, then every time you are forced to restructure you do it inefficiently–at huge cost to both your people and your bottom line.
HR teams need to be thinking about how we use data about company employees to continually improve recruitment and retention. In much the same way that marketing and advertising uses data to learn about what people want, and recommend things based on that.
Imagine the world of possibility if recruitment data was used this way. Imagine if we built an Amazon recommendation system for people’s skill sets that looked at their ability to perform in any role?
What are you waiting for? Let us show you what we can do for you.