Written by Nathan Hewitt
Avoiding biases and adverse impact in predictive hiring
Part of our job here in the workforce science team is to keep up to date with new research in Organisational Psychology. This might sound boring to some people – but we love it!
As massive nerds, we find nothing more exciting than seeing new progress in our field. This time, our knowledge-cravings took us all the way from Melbourne to Orlando, Florida, to this year’s SIOP conference.
The issue of Adverse Impact
An important issue within our field – and within the US in general – is adverse impact and hiring for diversity.
We are passionate about ensuring people are not discriminated against in selection methods, whether it is because of gender, age, ethnic background or sexual orientation.
(Actually, this is also one of the key values and driving forces behind why Paul, our CEO, founded Sapia.)
One key topic at this year’s conference was the combination of data science and behavioural science. Specifically, there were a lot of discussions around how these sciences can work together to minimise bias and discrimination in the hiring process.
The standard recruitment selection process
To give you some background as to why this is important, let’s explore what a standard selection process might look like today.
If you ever have applied for a job, it is likely you have gone through a process involving;
- your resume
- a cover letter
- a psychometric test (personality/intelligence)
- an interview
- reference checks
As mentioned, pretty standard. This is typically the different pieces of information that recruiters would use to assess your suitability for a role.
However, from an adverse impact perspective, this isn’t good enough.
The reason is that humans are biased (there are a plethora of studies out there proving this). And even if our biases (in most cases) are unconscious, we still base discriminatory decisions on them.
Does your name predict future performance?
A research study by The Ladders found that recruiters only spend about 6 seconds looking at a resume. Using gaze-tracking technology they identified that recruiters spend almost 80% of this time on only a few items:
- name
- current title/company
- previous title/company
- previous position start and end dates
- current position start and end dates
- education
To most people that would seem reasonable. Our previous professional and educational experience should be predictive of future performance, right?
If you agree, it might surprise you that past job experience only has a 0.13 validity when used to predict performance (and your name certainly has nothing to do with how you would perform).
So not only is the information recruiters look at not actually predictive of performance, but it also has the potential to adversely impact minorities.
An eye-opening example
In the 1970s, the Toronto Symphony Orchestra was composed of almost all white males. A few years later, they caught on to their diversity issue and decided to do something about it.
One initiative was to introduce ‘blind auditions’. Individuals would perform from behind a screen, making the assessors ‘blind’ to who was performing. This meant that the performance was in the center of the assessment, not the individual.
The result?
The proportion of women within the orchestra increased from 5% to 35%.
Individuals within racial minority groups are also discriminated against based on resumes.
Research found that applicants with ‘traditional’ english names received an interview for every 1/10 resumes sent out. This is in contrast to applicants with African-American names, who only got an interview for every 1/15 resumes.
As the resume is one of the most common determinators of whether an applicant progresses to the next stage – it is alarming that this method can adversely impact minority groups.
Luckily, some progress is definitely being made to combat this.
Different techniques, for example blind recruitment, are increasing in popularity. Some progressive businesses have leap-frogged and started using artificial intelligence (AI) driven algorithms as a first step in their assessment process.
Important to keep in mind with AI and Adverse Impact
When using AI, it is very important to understand that the data put into the algorithm is of great importance. AI is often touted as the solution to the biases inherent in our thinking, but if not executed properly, AI can also become biased.
This is because an AI algorithm is only ever as bias-free as the data we used to build it.
It can be difficult to make sure AI is increasing diversity, and at the same time maintaining its predictive power. The predictive power is basically how good a model is at predicting good performance – and weeding out those who wouldn’t do so well.
To ensure best chance of success it is crucial that the data we put into AI recruitment tools is bias free.
One way is to control what you put into your AI models. Big Data can for example be dangerous, as it looks at adding all possible data sources of information to predict performance.
This could mean that the AI model learns that ethnic background is a predictor for success, which we clearly want to avoid.
To combat this issue at Sapia, we make the following decisions:
Targeted variables:
- we only choose variables that minority groups do not answer differently to other groups
(if we did the model could learn to discriminate against these groups if the variable was considered predictive)
Test our predictors:
- Are they in fact adversely impacting anyone?
- Conduct adverse impact studies
When considering a new assessment tool, you should always ask your test provider the following;
How do you ensure the assessment isn’t biased against any gender, age or racial category, whilst remaining highly predictive of performance?
If they can’t give you a satisfying answer, it is definitely worthwhile considering another vendor.
Liked what you read? For further reading on how we minimise bias in our algorithms, head here.
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Egy HR-algoritmus Képes Megmondani, Milyen Gyakran Fogsz Munkát Váltani
A koronavírus-járvány kezdete óta számos vállalat fordult okos algoritmusokhoz, hogy kiderítse, ki a legjobb jelölt a nyitott pozíciókra. Leggyakrabban arckereső programokat, játékokat, kvízeket és más vizuális vagy nyelvi mintázatokat vizsgáló szoftvereket vetnek be, hogy eldöntsék, ki kerül be az interjúkörbe.
A jelek szerint a 2013 októberében alapított, ausztrál PredictiveHire nevű cég ennél is sokkal tovább ment: olyan gépi tanuláson alapuló algoritmust fejlesztett, amellyel felmérhető, hogy egy adott jelölt esetén mekkora a gyakori munkahelyváltás valószínűsége – írta a héten az MIT Technology Review.
Barbara Hyman, a HR-cég ügyvezető igazgatója szerint ügyfeleik olyan munkáltatók, akiknek rengeteg jelentkezést kell feldolgozniuk, és egyebek mellett az ügyfélkiszolgálás, a kiskereskedelem, az értékesítés vagy az egészségügy területén aktívak.
Első körben chatbot dönt a jelentkezőkről
Amikor valaki a HR-cégen keresztül jelentkezik állásra, először egy chatbotot kell „meggyőznie” értékeiről. Az algoritmus nyitott kérdések sorát teszi fel, és olyan személyiségjegyeket elemez, mint a kezdeményezőkészség, a belső motiváció vagy az ellenálló képesség.
Sőt, az algoritmus a jövőben a gyakori munkahelyváltás valószínűségét – vagy ahogy a PredictiveHire honlapján reklámozza, a „menekülés kockázatát” – is vizsgálhatja, még teljesen pályakezdő jelöltek esetén is. A HR-cég legújabb tanulmányának fókuszában ugyanis egy olyan gépi tanuló algoritmus fejlesztése áll, amely kifejezetten ezt igyekszik előre megmondani. A kutatás keretében 45899 jelöltet vizsgáltak meg, akik korábban a PredictiveHire chatbotján keresztül válaszoltak a tapasztalataikról és helyzetmegítélő képességeikről szóló 5-7 nyitott kérdésre.
Ezek olyan személyiségjegyekre kérdeztek rá, amelyek korábbi kutatások – például a PredictiveHire saját kutatása – alapján szoros összefüggésben lehetnek a gyakori munkahelyváltásokkal, például az új élmények iránti nagyobb nyitottság vagy a gyakorlatiasság hiánya.
Algoritmusok a béremelés ellen
Nathan Newman, a New York-i John Jay College of Criminal Justice egyik egyetemi docense, aki 2017-ben arról írt tanulmányt, hogy a nagymintás adatelemzés a munkavállalók diszkriminációján felül hogyan használható a bérek letörésére, az MIT Technology Review-nak azt mondta, a PredictiveHire legutóbbi munkája
az egyik legkártékonyabb módja a big data munkaügyi alkalmazásának.
Ide tartoznak a gépi tanuláson alapuló, egyre népszerűbb személyiségtesztek is, amelyek azokat a potenciális munkavállalókat igyekeznek kiszűrni, akik nagyobb valószínűséggel támogatnák a szakszervezetekbe tömörülést, vagy hajlamosabbak béremelést kérni. Mindezt úgy, hogy az MIT Technology Review szerint a munkáltatók egyre jobban szemmel tartják dolgozóik e-mailjeit, online beszélgetéseit és minden olyan adatot, amelyből leszűrhetik, hogy az adott kolléga távozni készül-e, és kiszámolhatják, mi az a minimális béremelés, amellyel még adott esetben maradásra bírhatják.
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Workday + Sapia = Faster, fairer hiring
Want to find out more about how our Workday integration works? Reach out!
An ‘unfair’ advantage is obtained for Recruiters by adding Sapia’s interview automation to Workday with faster, fairer and better hiring results.
Make a difference
As the first gate to employment, the hiring team has a huge influence on candidate experience, diversity and inclusion and overall business success. The way you hire can make someone’s day. It can set your business up to overtake the competition. It can be one step towards designing a fairer world for everyone.
Hiring is more complex than ever
There’s a lot expected of recruiters these days. Attracting candidates from diverse backgrounds and delivering exceptional candidate care whilst selecting from thousands of candidates isn’t easy.
Recruiters are expected to:
- Find the right people, ensuring a diversity of candidates
- Fill roles quickly and efficiently
- Interrupt bias in hiring and promotion
- Ensure every person hired amplifies the organisation’s values
- Create a candidate experience that is engaging and rewarding
Technology is more powerful than ever
The good news is that technology has advanced to support recruiters. Additionally, integrating Sapia artificial intelligence technology with the powerful Workday ATS facilitates a fast, fair, efficient recruitment process that candidates love.
Are you ready to:
- Reduce your screening time by up to 90%
- Increase your candidate satisfaction to near 100%
- Achieve interview completion rates over 90%
- And reduce screening bias for good
Your advantage: Sapia + Workday
Gone are the days of screening CVs, followed by phone screens to find the best talent. The number of people applying for each job has grown 5-10 times in size recently. Reading each CV is simply no longer an option. Thus, the attributes that are markers of a high performer often aren’t in CVs and the risk of increasing bias is high.
We’ve created a quick, easy and fair hiring process that candidates love.
- Create a vacancy in Workday, and a Sapia interview link will be created.
- Include the link in your advertising. Every candidate will have an opportunity to complete a FirstInterview via chat.
- See results as soon as candidates complete their interview. Each candidate’s scores, rank, personality assessment, role-based traits and communication skills are available as soon as they complete the interview. Every candidate will receive automated, personalised feedback.
By sending out one simple interview link, you nail speed, quality and candidate experience in one hit.
Integrate Workday and get ahead
Get ahead of your competitors with Sapia’s award-winning chat Ai available for all Workday users. Automate interview, screening, ranking and more, with a minimum of effort. Save time, reduce bias and deliver an outstanding candidate experience.
The interview that all candidates love
As unemployment rates rise, it’s more important than ever to show empathy for candidates and add value when we can. Also using Sapia, every single candidate gets a FirstInterview through an engaging text experience on their mobile device, whenever it suits them. Every candidate receives personalised MyInsights feedback, with helpful coaching tips which candidates love.
Together, Sapia and Workday deliver an approach that is:
- Relevant—move beyond the CV to the attributes that matter most to you: grit, curiosity, accountability, critical thinking, agility and communication skills
- Respectful—give every single person an interview and never ghost a candidate again
- Dignified—show you value people’s time by providing every single applicant personal feedback
- Fair—avoid video in the first round interviews and take an approach that’s 100% blind to gender, age, ethnicity and other irrelevant attributes
- Familiar—text chat interviewing is not only highly efficient, it’s also familiar to people of all ages
There are thousands of comments just like this …
“I have never had an interview like this in my life and it was really good to be able to speak without fear of judgment and have the freedom to do so.
The feedback is also great. This is a great way to interview people as it helps an individual to be themselves.
The response back is written with a good sense of understanding and compassion.
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.”
Take it for a 2-minute test drive here >
Recruiters love using artificial intelligence in hiring
Recruiters love the TalentInsights Sapia surfaces in Workday as soon as each candidate finishes their interview.
Together, Sapia and Workday deliver an approach that is:
- Fast—Ai-powered scores and rankings make shortlisting candidates quicker
- Insightful—Deep dive into the unique personality and other traits of each candidate
- Fair—Candidates are scored and ranked on their responses. The system is blind to other attributes and regularly checked for bias.
- Streamlined—Our stand-alone LiveInterview mobile app makes arranging assessment centres easy. Automated record-keeping reduces paperwork and ensures everyone is fairly assessed.
- Time-saving—Automating the first interview screening process and second-round scheduling delivers 90% time savings against a standard recruiting process.
HR Directors and CHROs love reliable bias tracking
Well-intentioned organisations have been trying to shift the needle on the bias that impacts diversity and inclusion for many years, without significant results.
Together, Sapia and Workday deliver an approach that is:
- Measurable—DiscoverInsights, our operations dashboard that provides clear reporting on recruitment, including pipeline shortlisting, candidate experience and bias tracking.
- Competitive—The Sapia and Workday experience is loved by candidates, ensuring you’ll attract the best candidates, and hire faster than competitors.
- Scalable—Whether you’re hiring one hundred people, or one thousand, you can hire the best person for the job, on time, every time.
- Best-in-class—Sapia easily integrates with Workday to provide you with a best-in-class AI-enabled HRTech stack.
Getting started is easy
Lastly, let’s chat about getting you started – book a time here >
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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.
Join the conversation
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