Eighteen months after we were all forced abruptly to work from home, it seems as the world cautiously opens up and employers are looking to return workers to offices, having the flexibility to work from home is an increasing demand that people aren’t willing to give up.
Earlier this year, Amazon laid out plans for most of its 60,000 workers in the Seattle area to return to the office later in the year. But, it wasn’t good news to everyone with hundreds threatening to quit. Microsoft, at Redmond in California, took a softer approach saying employees could work from home, the office or in a hybrid arrangement. Google, Hubspot and Intuit are some of the other companies that have opted for hybrid models going forward.
Others like Atlassian, Twitter, Shopify, Spotify and Slack have decided to become fully remote. Recently, Slack CEO Stewart Butterfield declared that digital life has moved too far forward during the COVID-19 pandemic for companies to return to former ways of office-based working, even if they wanted to.
While these are some of the world’s most influential companies, it’s a conversation that almost every employer is having right now.
The reality is the demand for remote or hybrid work is fast becoming part of hiring negotiations and compensation packages. For many, work flexibility has become more important than pay.
This has created a new dilemma for hiring managers that’s much deeper than offering strong commitments on flexibility as part of a job offer.
If work flexibility is the future, how do you determine who’ll thrive in this setup?
While it’s easy to guess some of the ideal attributes of a remote worker – that is they need to be autonomous, self-motivated, productive and able to collaborate online – there is another key characteristic that has proven vital to strong performance.
What we’ve seen from companies that have prioritised remote working for a long time such as Automattic, GitLab, InVision and Buffer is the importance of strong written communication. This is because you are no longer relying on face-to-face interactions that occur naturally or through formal meetings in an office. For remote work to be viable communication needs to be predominantly textual and mostly asynchronous.
When building a remote organization, Automattic CEO Matt Mullenweg has said that at some point you realise how crucial written communication is for your success, and you start looking for great writers in your hiring. For this reason, Auttomatic job interviews are conducted via text only.
Mullenweg says the true asynchronous nature of a written interview reflects the remote work reality compared to real time video interviews, which are not scalable in an organisation. I think most of us found that out the hard way during the pandemic.
So how can companies hire for remote capabilities?
In order to be effective remote and hybrid companies we need to rethink our hiring processes. To be frank, current hiring practices are just not going to cut it. CVs do not reveal the soft skills we need them to, and video is so inherently biased and stressful for candidates that many companies which opted for this early on in the pandemic are abandoning it as a top-of-the-funnel filter. We have several customers who have explicitly ditched video interviews.
The risk of making bad hires when you throw remote work into the equation is higher than if you’re bringing people into an office environment. You need to trust them from day one without any of the ‘visibility’ you get from seeing someone everyday.
We need a new way of selecting candidates that can accurately identify soft skills like accountability, autonomy, drive and writing skills. Can a text based interview reveal these qualities, while providing a great candidate experience and being highly relevant to the remote work context?
Mullenweg’s idea of a text only interview is not as radical as some might believe. We do thousands of them every day across the world, for a number of varied companies. We are able to reveal people’s character traits with over 90% accuracy (we know because we ask them).
It’s scientific, based on data and is the only accurate way you can identify both the written communication proficiency and soft skills required to work remotely.
How we do it
Our text interview includes open-ended questions on situational judgement and values, similar to a structured interview. When responses are analysed for skills that pertain to remote work it takes into account a multitude of features related to language fluency, proficiency, personality traits, behavioural traits, and semantic alignment.
This allows a recruiter to quantify and compare a candidate’s written communication skills immediately as well as their suitability to the work environment.
The revealing nature of text interviews is not just limited to the skill of writing, but also to the motivation behind expressing something in writing, which 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.
Conclusion
While many companies are already scrambling to update their remote work policies and rethink their office space needs, if they are not reconsidering their hiring processes as part of this inevitable shift, then they are exposing their company to risk.
Just because people want to work remotely, doesn’t always mean they can thrive in it. While you may be doing the right thing in offering flexibility for candidates, you also need to make sure that you are doing right by your company by understanding how well these candidates will thrive remotely.
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Wondering how our Ai recruitment assessment tool can identify soft skills in candidates? Find out here.
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Sapia.ai Wrapped 2024
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.
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Situational Judgement Tests vs. AI Chat Interviews: A Modern Perspective on Candidate Assessment
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?
1. The Static Nature of SJTs
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.
2. Richer Data Through Open-Ended Responses
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.
3. The Candidate Experience: Stressful or Supportive?
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.
4. Addressing Bias and Fairness
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.
5. An Assessment That Improves Over Time
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.
Rethinking Candidate Assessment
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.
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Keeping Interviews Real with Next-Gen AI Detection
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.
What’s New?
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.
The Challenge of AI in Chat-based Interviews
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.
For Candidates: Enabling Authenticity
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.
For Hiring Teams: Actionable Insights
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.
Built on Unmatched AI Interview Expertise
“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.
Why This Matters
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.”
Testing and Validation of the AGC Detector 2.0
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.
Fairness & Transparency in AI-Enabled Hiring
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.