In his book Influence: The Psychology of Persuasion, author Bob Cialdini explains how the contrast principle can unfairly distort our perceptions of quality and value. By comparing a really good thing to something that is just okay, we tend to judge the latter as far worse than it is. It works the other way, too: when presented with a host of bad options, the best of the bunch – the lesser of all the evils – looks disproportionately attractive.
Cialdini gives us myriad examples: Realtors who show you a couple of dingy properties to make the target property look better, and retail salespeople who suggest a really expensive coat to get you to settle for the cheaper belt. The principle also turned a series of bad management decisions into the Watergate incident, if you can believe that.
It doesn’t stop there, however. The contrast principle is a natural and inextricable part of the traditional face-to-face interview.
Janie is bright, exuberant, and chatty. The interview starts strongly. She strides proudly into your office, hand outstretched, smiling warmly. Her clothes are fashionable. Her resume is colourful and well-designed. You like her right away, as does everyone, because she’s a ray of sunshine. She probably plays the harp and makes her own muesli.
The interview goes well. Janie knows what to say, and because she is extraverted, she knows how to deftly circumvent tricky technical questions. There’s a slight concern in the back of your mind that she is not sufficiently experienced, but you figure that her outgoing, can-do attitude will more than make up for that (and you might be right).
Alice is your next appointment. She’s a lot quieter than Janie. She speaks a lot less, too. Her smile is genuine, and she is perfectly well spoken, but Alice is clearly nervous. Her manner is cautious, full of apprehension.
You notice that her resume is excellent. Ticks all the right boxes. She’s a veteran in the field. But there’s something amiss: She’s just not like Janie. As a result, you’re probably not going to call her back for a second interview.
This is one of the most common ways the contrast principle plays out: If the second candidate does not match the energy of the first, if her presence does not illicit the same rise in dopamine, then we are likely to favour the first candidate. Objectivity quickly goes out the window.
There are many suggestions out there for mitigating or removing the contrast principle, but the truth is this: If humans do your face-to-face interviews, you cannot prevent the potential for contrast bias. Even conducting what’s called a ‘blind resume review’ will not help. Yes, you can assess resumes stripped of identifying characteristics, like race or gender, but you cannot account for the fact that the details themselves are easily doctored and falsified. Don’t forget that 78% of people lie.
The bottom line is this: You need a blind, non-human smart interviewer to do your first-round interviewing for you. It’s the only way to be free of biases, compromise hires, and the intractable likeability factor. We can help with that.
This research paper is part of our accepted submission to SIOP, and will be presented at the 2023 SIOP Conference in Boston.
Bias and discrimination against candidates and employees with disabilities continues to be an increasingly important topic 30 years after the Americans with Disabilities Act of 1990 (ADA) was passed. The unemployment rate for those with a disability (10.1%) in 2021 was about twice as high as the rate for those without a disability (5.1%) (U.S. Bureau of Labor Statistics, 2022).
So what are the barriers for individuals with disabilities trying to gain employment and how can they be reduced or eliminated?
Traditional face-to-face or video interviews in particular create potential barriers for individuals with disabilities due to the well-documented stigma and prejudice against those with disabilities (Scior, 2011; Thompson et al., 2011). An experimental study found less interest for job applicants that disclosed a disability, despite being equally qualified (Ameri et al., 2015).
Another concern is that certain selection methods may cause candidates with disabilities stress or anxiety, therefore not allowing them to put their best foot forward. For example, one study found less than 10% of those with Autism Spectrum Disorder believe they’re able to demonstrate their skills and abilities with in-person or video interviews (Cooper & Kennady, 2021).
Candidates with disabilities may also struggle with timed online assessments (Hyland & Rutigliano, 2013). For example, candidates with dyslexia or other learning and language disabilities may struggle with reading or spelling and may need extra time.
Sapia’s approach to removing these barriers is our blind, online, untimed, chat-based interview that can not only help reduce discrimination against those with disabilities but also create a more positive candidate experience for them. This format is particularly helpful for individuals with disabilities where traditional in-person interviews, video interviews, or timed assessments may cause stress or discomfort, therefore not allowing them to adequately demonstrate their skills.
We examined the adverse impact statistics (effect size, 4/5ths ratio, and Z-test) for over 15,000 candidates applying to a retail store associate role who self-reported having a disability, compared to those who reported no disability. We found no major or consistent adverse impact flags for the full sample of candidates with a disability or the majority of individual disability groups.
Additionally, candidates with disabilities had positive reactions to the chat-interview, with a candidate happiness score of 8.9/10 and 95.8% leaving either a positive or neutral comment (For example, “Being dyslexic, this interview gives me a fantastic opportunity to think and re-read my responses before delivery.” and “I really enjoyed this unique interview experience. I am autistic so voice and face-to-face interviews have always been a bit daunting, but this felt natural and enjoyable.”)
This research demonstrates that using online, untimed, chat-based interviews could help reduce bias and discrimination against candidates with disabilities. Additionally, examining score differences and candidate reactions by type of disability can help guide product enhancements to make the experience even more enjoyable, accessible, and fair.
References:
Ameri, M., Schur, L., Adya, M., Bentley, S., McKay, P., & Kruse, D. (2015). The disability employment puzzle: A field experiment on employer hiring behavior. National Bureau of Economic Research (NBER) Working Paper Series, Working Paper 21560.
Cooper, R., & Kennady, C. (2021). Autistic voices from the workplace. Advances in Autism, 7(1), 73–85.
Hyland, P., & Rutigliano, P. (2013). Eradicating Discrimination: Identifying and Removing Workplace Barriers for Employees With Disabilities. Industrial and Organizational Psychology, 6(4), 471-475.
Scior, K. (2011). Public awareness, attitudes and beliefs regarding intellectual disability: A systematic review. Research in Developmental Disabilities, 32(6), 2164-2182.
Thompson, D., Fisher, K., Purcal, C., Deeming, C., & Sawrikar, P. (2011). Community attitudes to people with disability: Scoping project No. 39). Australia: Disability Studies and Research Centre, University of New South Wales.
U.S. Bureau of Labor Statistics (2022). Persons with a Disability: Labor Force Characteristics— 2021. News Release USDL-22-0317, U.S. Bureau of Labor Statistics, Feb 24.
Being able to access interview automation just got so much easier inside Tribepad, with Sapia. To explore the use cases for Sapia, let’s chat.
Here’s a quick rundown:
And now that we are integrated into Tribepad, you get all of these smarts inside your existing Tribepad application. At Sapia, we interview every applicant in-depth and at scale for you. Overall, this is by using a text chat that helps you find the best people fast. Our underlying data science has been accepted and published in international journals.
Firstly, no one’s time is served well by screening thousands of CVs. With every additional applicant costs your business an extra $20 in screening if you are doing it the old way, automating the screening process is the commercial decision companies are now making.
Once your vacancy is created in Tribepad, a corresponding interview link will also be created.
Candidates click this link to enter their text-based interview. This is known as the ChatInterview.
As soon as candidates complete their interview their results are displayed inside Tribepad. You also get to see the candidate’s personality assessment. With the pre-assessment already done for you, it makes shortlisting much faster. Thus, by sending out one simple interview link, you nail speed, quality and candidate experience.
The SmartInterview experience is most commonly used for high-volume recruiting. Our customers typically use it in frontline customer-facing roles (like contact centres, customer service) and/or for low-skill roles.
We help manage the disconnect between attraction and retention. This is all done by allowing Recruitment Teams to work more efficiently to hire the best talent. All is done whilst ensuring the applicants feel good about applying for a job role.
Sapia solves the time problem of managing a large applicant pool. It also tackles the quality problem of pin-pointing the best people from that pool. Additionally it solves the candidate experience problem by offering every applicant a fair chance at the opportunity (everyone gets an interview) on platforms they love to use. Simultaneously every candidate gets something of immense value in return for their application.
We are glad you are asked! The first thing to note is Sapia is a paid app and sold separately. Next, to explore the pricing that suits your organisation, let’s chat. Lastly, our team can take you through the integration process and describe how the interview automation experience works.
Also, to keep up to date on all things “Hiring with Ai” subscribe to our blog!
Finally, you can try out Sapia’s SmartInterview right now, or leave us your details here to get a personalised demo.
Any leader with P&L accountability knows that tracking margin (ie the difference between your revenue and what it cost you to earn that revenue) is pretty damn important to your economics. Margins of 60%+ for tech companies is what gives them insane valuations because the cost of adding the 10,000th customer is not much greater than adding the 1000th customer. If you believe that the economics and ROI of your talent business model are as important as your core business model, then you may find applying these two business metrics a useful lens to analyse the ROI of your talent business model.
Applying these metrics to your talent business model can help identify where to invest your HR budget to drive better ROI.
3 factors drive your CAC:
1. Direct recruitment costs i.e. how many recruiters do you have on the tools
2. The productivity and speed of your recruitment team (that is, it’s scaleability) i.e. the amount of candidates they screen in an hour, day, week, month
3. The layers of assessment in your recruitment and their costs i.e. are you doing CV screening, phone screening, video screens, 1:1 interviews, panel interviews, group assessments, coffee chats?
All of these layers of assessment, some with some science behind them, most with no science, add to your CAC. We analysed CAC for our customers comparing their ‘old’ recruitment process and the impact of using our AI to do their screening and assessment.
The results are stunning.
PHAI (PredictiveHire AI) can screen 100,000 applicants in around 6 hours, what it would take a team of 5 recruiters 476 working days to do. A massive 600 x faster. This is based on conservative assumptions like every recruiter screening 7 hours a day, CV screening of 10 minutes per applicant, and 10% of those CV screened with phone screens of 30 minutes in duration. Those speed differentials compound when the numbers grow because humans can’t scale but technology can.
You can see what the scale of impact is when you look at the cost and time differential for 1000 applicants and 100,000 applicants. The case for AI in recruitment is a no brainer for enterprise and government, and compelling even for smaller businesses with more modest volumes.
Suggested Reading
https://sapia.ai/blog/hr-job-metrics/