I live in Melbourne, Australia. When I speak to customers overseas they all sympathize with the restrictions imposed on us as a result of COVID-19. We are the State that that just can’t seem to take our eyes off the numbers, being used as an invisible algorithm to drive decisions like when we can see our friends and families again, go to the footy, or have a drink at the pub.
Scott Galloway talks of Covid-19 being an accelerant, not a change agent. Organisations who were already on the path of disrupting their own business models have surged ahead. Those with unfit practices might have been able to do a fun run, but what we have now is an ultra-marathon.
Organizations need a new playbook. We humans need a new playbook. COVID-19 is transformational for organizations, and it requires transformational thinking and responses.
The lack of deep thinking on this is reflected in the exhaustion we are all feeling right now. Many of us find ourselves spending 12 hours a day on back-to-back zoom calls. We are missing out on the key benefit of flexibility, which is unleashing productivity. Which means doing more in fewer hours, not doing more by working longer hours.
Few of us have made the transformational changes required to accommodate true remote work. One of those changes has to be to embrace asynchronous working norms.
Asynchronous work needs asynchronous communication. This simply means that work doesn’t happen at the same time for everyone. Productivity and flexibility for employees come when we don’t all have to get in a room, virtual or otherwise to do our work. This usually means communicating in writing, not video.
The other change that needs to happen is less vertical decision-making, less requiring decisions to ‘go up’ to be made – and more pushing them down to the individual level as much as possible. It’s time to really empower your people. Leaders need to set the vision and trust their people to solve how to get there. This means creating cultures of trust and leaving behind cultures of control.
The good news is that a by-product of remote work will be a natural increase in accountability for performance. The reality is you can’t fake it or fudge it as easily when your actual work output, not your personality, is what is most visible to everyone. The talkers vs the doers are quickly exposed. The big ‘P’ personality types won’t survive as long as there is no place for them to entertain us with their stories and their charisma.
This new reality won’t work for everyone and demands transparency around performance and expectations from both sides. For many, this may lead to a loss of confidence and validation that they would normally get from being part of a visible tribe in the office. When you don’t have a team or a manager around you to mentor you, notice your good work, or your bad work, you need to do the noticing yourself. Self-awareness becomes crucial. As does self-motivation, the discipline to see a task through without much pushing or oversight.
Organizations need to give way more attention to hiring and promoting these qualities that will enable individuals to be independently productive. It may even mean evolving your values to reflect those kinds of new survival traits.
What makes that shift especially tough for many organizations is that we have all been doing the opposite for years. To coin a phrase from Johnathan Haidt, we have been guilty of coddling our kids and our employees. Haidt, author of “The Coddling of the American Mind’ notes the impact of all that coddling and the resulting culture of ‘safetyism’, which stunts the development of that life skill- resilience, a trait critical for all of us right now.
Simon Sinek, a speaker/writer on cooperation, trust, and change says developing better managers can help young people build better resilience. This becomes harder in a world where you’re not spending time with your manager. Rather, the individual needs to take on more responsibility for their own learning and for their own motivation and engagement.
So how do you create more individual and organizational resilience? How do you hire for and build the skill of accountability?
It requires creating an expectation via explicit conversations about the need for you to own your own work, your own career. It demands hiring people who have heightened self-awareness, to know what they need help with, to ask for what they need.
Which jobs are better suited to me? What am I good at, not good at? How do others see me so I can better manage my relationships at work or at home? What part of me is helping me or hindering me in life?
The problem is that not every type of person will do that comfortably and this is where Covid-19 risks creating another privileged class of people who do better in that environment. This is where I advocate for technology as an essential co-pilot for employees to understand themselves better and help coach them to level the playing field. Technology that can draw out the best in people and help them find their strengths and agency.
The new playbook already has a few chapters written by some well-known disruptors. For example, Jeff Bezos banning PowerPoint from meetings, Google’s money-ball approach to hiring and promotion, virtually inventing people analytics. The text-only interviews of Automattic, the company behind WordPress, with 1000+ remote workforce in 73 countries.
In short, to leaders of all domains: move to the new playbook.
Get on with experimenting with fundamentally new ways of working. And, recognise that technology will be your co-pilot in that change.
Source: Barbara Hyman, Recruiting Daily, 1 October 2020
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It’s been a year of Big Moves at Sapia.ai. From welcoming groundbreaking brands to achieving incredible milestones in our product innovation and scale, we’re pushing the boundaries of what’s possible in hiring.
And we’re just getting started 🚀
Take a look at the highlights of 2024
All-in-one hiring platform
This year, with the addition of Live Interview, we’re proud to say our platform now covers screening, assessing and scheduling.
It’s an all-in-one volume hiring platform that enables our customers to deliver a world-leading experience from application through to offer.
Supercharging hiring efficiency
Every 15 seconds, a candidate is interviewed with Sapia.ai.
This year, we’ve saved hiring managers and recruiters hours of precious time that can now be used for higher-value tasks.
Giving candidates the best experience
Our platform allows candidates to be their best selves, so our customers can find the people that truly belong with them. They’re proud to use a technology that’s changing hiring, for good.
Leading the way in AI for hiring
We’ve continued to push the boundaries in leveraging ethical AI for hiring, with new products on the way for Coaching, Internal Mobility & Interview Builders.
Choosing the right tool for assessing candidates can be challenging. For years, situational judgement tests (SJTs) have been a common choice for evaluating behaviour and decision-making skills. However, they come with limitations that can make the hiring process less effective and less inclusive.
AI-enabled chat-based interviews, such as Sapia.ai, provide organisations with a modern alternative. They focus on understanding candidates as individuals and creating a hiring experience that is both fair and insightful while enabling efficient screening and selection.
This shift raises important questions: Are SJTs still a tool that should be considered for volume hiring? And what do AI assessments offer in comparison?
Traditional SJTs use predefined multiple-choice questions to assess behavioural tendencies and situational knowledge. While useful for screening, these static frameworks lack the flexibility to adapt based on real-world performance data or evolving role requirements.
Once created, SJTs don’t adapt to new data or evolving organisational needs. They rely on fixed scenarios and responses that may not fully reflect the dynamic realities of modern workplaces, and as a result, their relevance may diminish over time.
AI-enabled chat interviews, on the other hand, are inherently adaptive. Using machine learning, these tools can continuously refine their models based on feedback from real-world outcomes such as hiring or turnover data. This ability to evolve ensures the assessments align with organisations’ needs.
One of the main critiques of SJTs is their reliance on multiple-choice responses. While structured and straightforward, these options may not capture the full scope of a candidate’s thinking, communication skills, or problem-solving ability. The approach is often limiting, reducing complex human behaviour to a few predefined choices.
AI-enabled chat interviews work more holistically and dynamically. These tools provide a more complete picture of a person by allowing candidates to answer questions in their own words. Natural language processing (NLP) analyses their responses, offering insights into personality traits, communication skills, and behavioural tendencies. This open-ended format lets candidates express themselves authentically, giving employers a deeper understanding of their potential.
SJTs often include time constraints and rigid formats, which can create pressure for candidates. This is especially true when candidates feel forced to choose options that don’t fully reflect how they would actually behave. The process can feel impersonal, even transactional.
In contrast, chat-based interviews are designed to be conversational and low-pressure for candidates. By removing time limits and adopting a familiar chat interface, these tools help candidates feel more at ease. They also frequently include personalised feedback, turning the assessment into a valuable experience for the candidate, not just the employer.
Traditional SJTs are prone to transparency issues, as candidates can often identify and select the “best practice” answers without revealing their true tendencies. Additionally, static test designs can unintentionally embed bias; due to the nature of the timed test, SJTs have been found to disadvantage some groups.
AI chat interviews, when developed ethically within a framework like Sapia.ai’s FAIR Hiring Framework, eliminate explicit bias by relying solely on the content of a candidate’s responses. Their machine learning models are continuously validated for fairness, ensuring that hiring decisions are free from subjective judgments or irrelevant demographic factors.
Workplaces are constantly changing, and hiring tools need to keep up. SJTs’ fixed nature can make them less effective as roles evolve or organizational priorities shift. They provide a snapshot but not a dynamic view of what’s needed.
AI-enabled chat interviews are built to adapt. With feedback loops and continuous learning, they incorporate real-world hiring outcomes—like retention and performance data—into their models. This ensures that assessments stay relevant and effective over time.
As hiring demands grow more complex, so does the need for tools that can capture the whole person, not just their response to hypothetical scenarios. While SJTs have played an important role in hiring practices, they are increasingly being replaced by tools like AI-enabled chat interviews.
These modern approaches provide richer data, adapt to changing needs, and create a richer and more engaging experience for candidates. Perhaps most importantly, they emphasise fairness and inclusivity, aligning with the growing demand for unbiased hiring practices.
For organisations evaluating their assessment tools, the question isn’t just which method is “better.” Understanding the specific needs of your roles, teams, and candidates will help you choose tools that help you make decisions that are both informed and equitable.
It’s our firm belief that AI should empower, not overshadow, human potential. While AI tools like ChatGPT are brilliant at assisting us with day-to-day tasks and improving our work efficiency, employers are increasingly concerned that they’re holding candidates back from revealing their true, authentic selves in online interviews.
As an assessment technology provider, we are responsible for ensuring the authenticity and integrity of our platform. That’s why we’re thrilled to unveil the latest upgrade to our flagship Chat Interview: the AI-Generated Content Detector 2.0. With groundbreaking accuracy and a candidate-friendly design, this innovation reinforces our mission to build ethical AI for hiring that people love.
Artificially Generated Content (AGC) is content created by an AI tool, such as ChatGPT, Claude, or Pi. We initially rolled out the first version of our AGC detector last year and have continued to improve it as our data set has grown and these AI tools have evolved.
Our updated AGC Detector 2.0 achieves an impressive 98% detection rate for AI-assisted responses, with a false positive rate of just 1%. This gives organisations peace of mind that they’re getting the most authentic assessment of every candidate.
This cutting-edge system builds on Sapia.ai’s proprietary dataset of over 2 billion words, derived from more than 20 million interview question-answer pairs spanning diverse roles, industries, and regions. It’s trained on real-world data collected before and after the release of tools like ChatGPT, ensuring it remains robust and reliable even as AI tools evolve.
Our data shows that around 8% of candidates use tools like GPT-4 to generate responses for three or more interview questions. While these tools may offer a quick way for candidates to complete their interview, they can inadvertently hide a person’s true personality and potential – qualities our customers are most interested in understanding through our platform. In fact, research from Sapia Labs shows that these tools have their own personality traits, which may be quite different from the candidate applying for the role.
When a response is flagged as potentially AI-generated, the system doesn’t disqualify candidates. Instead, a real-time warning pops up, allowing them to revise their answers or submit them as-is. This ensures that candidates are encouraged to present themselves authentically, reflecting their unique communication styles and sharing their genuine experiences.
Responses flagged as AI-generated are highlighted in the candidate’s Talent Insights profile, accessible via Sapia.ai’s Talent Hub or ATS integrations. These insights give hiring teams the transparency to make informed decisions, fostering trust while accelerating hiring timelines.
“Our detection model’s strength lies in its foundation of real-world interview data collected from diverse roles and regions,” says Dr Buddhi Jayatilleke, Sapia.ai’s Chief Data Scientist. This depth of understanding enables the AGC Detector to maintain its industry-leading accuracy – even when candidates subtly modify AI-generated answers to appear more human.
The AGC Detector 2.0 embodies Sapia.ai’s commitment to ethical AI that amplifies human potential. As our CEO Barb Hyman explains:
“The hiring landscape has fundamentally changed since ChatGPT, but our commitment remains clear: AI should amplify human potential, not penalise it. This breakthrough fosters authentic hiring conversations. Our real-time warning system helps candidates make better choices and gives enterprises confidence in their selection decisions.”
The new detector has been rigorously tested on over 25,000 interview responses generated by humans and leading AI models like GPT-4, Claude-3.5, and Llama-3. The results speak for themselves, reinforcing the reliability and fairness of this game-changing technology.
By detecting AI-generated content while allowing candidates to correct their responses, our AGC Detector 2.0 ensures every applicant has the chance to put their best, most authentic foot forward when applying for a role powered by Sapia.ai. For enterprises, it provides confidence in the integrity of their hiring decisions and ensures they’re connecting with real candidates at scale.