COVID has taught us that on reflection the focus on individual action with a community benefit as a goal is really a focus that leads to the greater good. In our home state of Victoria, Australia now 7 straight days with ZERO new cases. It has been an effort founded on facts and science over misinformation. In Victoria, many sacrificed a lot for their well-being for ALL. If anything, there is now proof, thanks to Victorians, that when we see facts, listen to science and let data show you how to lead that change, you can make it happen.
AI, especially predictive machine learning models, are an outcome of a scientific process, it’s no different to any other scientific theory, where a hypothesis is being tested using data.
The beauty of the scientific method is that every scientific theory needs to be falsifiable, a condition first brought to light by the philosopher of science Karl Popper. In other words, a theory has to have the capacity to be contradicted with evidence.
There are three decisions that are made by a human in building that scientific experiment.
One can argue 2 and 3 are the same as if the methodology is not sound the data collection wouldn’t be either. That’s why there is so much challenge and curiosity as there should be about the data that goes into an algorithm.
Think of an analogy in a different field of science: the science of climate change.
A scientist comes up with a hypothesis that certain factors drive an increase in objective measures of climate warming, eg CO2 emissions, cars on the road, etc. That’s a hypothesis and then she tests it using statistical analysis to prove or disprove that her hypothesis holds beyond random chance.
The best way to make sure you are following a sound scientific approach is to share your findings with the broader scientific community. In other words, publish in peer-reviewed mediums such as journals or conferences so that you are open to scrutiny and arguments against your findings.
Or to put it another way, be open for your hypothesis to be falsified.
In AI especially, it is also important to keep testing whether your hypothesis holds over time as new data may show patterns that lead to disproving your initial hypothesis. This can be due to limitations in your initial dataset or assumptions made that are no longer valid. For example, assuming the only information in a resume related to gender are name and explicit mention of gender or a certain predictive pattern such as detecting facial expressions are consistent across race or gender groups. Both of these have been proven wrong*.
The only way to improve our ability to predict, be it climate change or employee performance, is to start applying the scientific method and be open to adjusting your models to better explain new evidence.
Therefore the idea that a human can encode their own biases in the AI — well it’s just not true if the right science is followed.
* Amazon scraps secret AI recruiting tool that showed bias against women (https://www.reuters.com/article/us-amazon-com-jobs-automation-insight-idUSKCN1MK08G)
* Researchers find evidence of bias in facial expression data sets (https://venturebeat.com/2020/07/24/researchers-find-evidence-of-bias-in-facial-expression-data-sets/)
You can try out Sapia’s Chat Interview right now, or leave us your details to get a personalised demo
Right now, you’re probably focussing on how to get more of the best talent into your funnel as the global talent shortage squeezes hiring teams.
That’s why we’ve made some small (but significant) improvements to our experience, to make it even easier to access and use our platform, both for candidates and hiring teams.
Standalone Video Interview
Last year we created a world-first frictionless hiring experience, enabling incredible speed and immediate efficiency gains for our customers. An automated workflow that interviews every candidate using Ai over chat, and auto progresses the shortlist to a non-Ai Video Interview.
Our customers want to empower Hiring Managers to make the final hiring decision while eliminating wasted time that manual screening processes create, and giving every single candidate an empowering experience with their brand.
The results have blown us away. When combined with Chat Interview, Video Interview has achieved the following outcomes for our customers, across 30k candidates:
“This interview was really great since I had 5 chances to record my responses, and that I had time to prepare my answer. The interview was not rushed and I was able to say everything I had to say”
“I like that this system gives people the opportunity to express how they really feel, and streamlines the interviewing process.”
Given the market demand for asynchronous video solutions, we’re delighted to announce that Video Interview is now available as a standalone solution.
We remain committed to hiring that minimizes human bias and always recommend using our Ai Chat Interview as the first step in your main recruitment process. It’s fair, engaging, and the most efficient way to assess your candidate pool.
However, this development suits the following scenarios:
In both of these scenarios, candidates can still have an engaging experience with your brand by completing a Video Interview for your hiring team to review, in their own time.
For customers wanting to interview non-English speakers, or provide reasonable accommodations for candidates unable to provide written responses, you can now offer Video Interview as a standalone assessment stage.
To be clear: we always advocate for our Ai Chat Interview to be used as the main assessment stage in your standard hiring process. It’s faster, fairer, and a more engaging candidate experience at the top of the funnel.
However, for scenarios where it doesn’t work to use an English language written interview, now you can offer Video Interview on its own.
Ethnicity & Gender Source visible in DiscoverInsights
To be able to measure diversity through the funnel, and help you to pinpoint bias across your business, we report on the ethnicity and gender of candidates.
The source of this data comes from two places:
Now you’ll be able to see the percentage breakdown between these two sources, to better understand the overall accuracy with which these data points are reported.
Ask questions using video in Video Interview
To create an even more engaging Video Interview experience, customers can now pre-record the questions asked in video format, so your candidates have more of a ‘conversation’ and get to know your team.
Our Customer Success team manages this process, so if you want to use this feature, just get in touch.
Edge 3 MFA token timeout increased
We take security at Sapia seriously. The use of MFA is key to keeping our customer’s data safe, however, some customers were having some issues with the 5 min token timeout.
To address this, we’ve increased the time limit to enter your MFA code from 5 to 10 minutes, to make it easier to log in to our platform, and to give some slower email delivery systems time to get your code to you.
Planned delay in sending My Insights reports ⏰
Our Ai is fast.. Some could say, too fast!
To set a more human cadence of communication, we’ve introduced a planned delay of around an hour in sending My Insights reports to candidates after they’ve submitted their Chat Interview responses.
All in the spirit of creating a human, intuitive experience with our Smart Interviewer.
In my career, I have been involved in either leading or managing countless restructures. The driving force behind these restructures ranged from offshoring capability to migrating to new or emerging skill requirements, right-sizing a particular function, or the basic need to reduce operating cost.
While each of these projects delivered on their outcomes, I would argue they had varying levels of success in preserving the organisational talent and corporate memory required.
More often than not, organisations will work towards a target – this could be FTE, Headcount, or Cost Reduction for example. Choices to achieve this target are often made in isolation of critical information.
I have seen situations where the people who kept their jobs vs lost their jobs was made on relationship merit, not on skills, capability or cultural alignment. I have also seen examples where it is a numbers game. Here, the end goal is purely to achieve the target. This leaves some organisations scrambling for contractors and consultants to backfill their critical skill gaps.
With the world in economic freefall (cue the dramatic music) we are going to see more and more organisations looking to right-size their workforce in-line with consumer confidence and spending.
Personality and behaviour.
So, with this in mind, how can an organisation make choices which are informed by data, unpinned by fairness, while still being efficient?
Personality and behavioural assessments have long been used in the recruitment and promotion of individuals. However, they are rarely used when right-sizing or restricting an organisation. This seems like a glaring and obvious opportunity. In right-sizing, you are effectively making hiring and promotion decision within your existing workforce.
When comparing the apples with apples, personality and behavioural assessments allow you to focus on the attributes which will differentiate your workforce for the next phase of your organisational journey . Then depending on what this journey is, you have the opportunity to codify the critical capabilities required.
Sapia has been partnering with many organisations locally and globally. Together we not only re-imagine how our partners use personality and behavioural assessments in recruitment, but also its application to the entirety of the HR lifecycle.
Unlike traditional personality & behavioural profiling, Sapia is powered by AI, utilising conversational text to assess individuals. Not capturing any protected attributes, this process removes the opportunity of bias creeping in. Thus, it allows you to make informed, a data-driven decision about your future workforce on culture & values alignment.
Yes, personality is widely accepted as an indicator of job performance.
Until now, the only way to accurately measure personality was through long and repetitive personality tests. The Sapia team breaks new ground disrupting decades of assessment practice. This is done by showing that answers to standard interview questions, through a text-based mobile interview can be used to reliably infer personality traits.
Get the published research here
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You can try out Sapia’s Chat Interview right now, or leave us your details here to get a personalised demo.
On 26th August, our CEO Barb Hyman facilitated a webinar on “Hiring with Heart” in collaboration with The Recruitment Events Network.
To our surprise, Jeff Uden who is the Head of Talent and L&D for Iceland Foods also joined the webinar.
During the session, Jeff offered some wonderful comments. We took a transcript of Jeff’s input and have jotted it here. It offers insights on dealing with enormous volumes of candidates, offering positive candidate experience and communicating culture from a candidate’s first experience with a brand.
Thanks for your insights, Jeff. Incredibly valuable.
At Iceland Foods, we have started working with Sapia. That was as a result of a couple of things. One was the element of the mass recruitment that we were doing. Just to put it in perspective, in the first four months of this year, we received over five hundred thousand applications.
We wanted to find a way that delivered a level of fairness, a level of consistency around how we sift those applications that then enabled store managers to reduce that amount of time that they are spending on doing the recruitment.
The other thing that we wanted to do was significantly enhance our candidate experience. One of the challenges that I had around the experiences that we had within the business is that it felt like it was really standard. It felt like it was cold; it felt like it came from a computer. We wanted to change how we did that and more importantly give something back to the candidates.
Often nowadays people apply for jobs, and there’s the standard ‘bulk’ response that says if you haven’t heard anything from us in two weeks take it that you haven’t been successful.
As big companies or companies of any size we have a duty to help those individuals to understand why they haven’t been successful and to help them to be successful in the next role for which they apply.
The fact that they won’t be hired into your business is probably the right decision because they wouldn’t have been the right fit given the testing that they have gone through. However, that doesn’t mean they are a bad individual. What we need to do is to help them to understand where their strengths are and where their development needs are, and certainly, that was a massive appeal of working with Sapia.
Going through and reading some of the feedback that we’ve had from the candidates, it’s having a huge effect on the candidate experience.
We had a swift implementation planned. But probably one of the lengthiest parts of it was about actually getting the questions right and getting the language right. We really did spend a decent period doing that.
I just had a quick look at one of the pieces of feedback here, and this is completely unedited:
That’s what’s coming over from the way in which we put the language across within the questions.
We are genuinely really chuffed about how they are engaging far more with us as a brand and how they are feeling like they are getting something back. They genuinely don’t feel like this is a computer process in any way whatsoever; they genuinely feel like they are talking to people.
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You can try out Sapia’s FirstInterview right now, or leave us your details here to get a personalised demo.
If there was ever a time for our profession to show humanity for the thousands that are looking for work, that time is now.