Author: Buddhi Jayatilleke, Chief Data Scientist, Sapia.ai
We all know the value of company culture. Culture forms the shared values, beliefs, and practices that shape the behaviors and interactions of employees within an organization. It is like the collective personality of a company that shapes everything from employee satisfaction to customer experiences.
While culture is a collective outcome, it isn’t something that just happens automatically. Leaders are responsible for defining the underlying values and must remain intentional about sustaining the desired organizational culture. A key part of culture is who you hire and how you hire them. We hear phrases like “Culture Fit” and “Culture Add” in the hiring process. These are part of “who” you hire and are used to both accept and reject candidates. But “how” you hire reflects your culture and creates the virtuous (or vicious) cycle that amplifies (or derails) an organizational culture.
“If you hire people just because they can do a job, they’ll work for your money. But if you hire people who believe what you believe, they’ll work for you with blood and sweat and tears.” – Simon Sinek
The above quote, attributed to Simon Sinek, makes a great point, but how do you find people “who believe what you believe”? In other words, how do you attract and hire individuals who will thrive in and uplift your culture? The experience through the candidate’s journey plays a key role.
And today we have a new enabler. Artificial Intelligence (AI).
AI certainly can not create culture. Culture is innately a human construct. However, AI as a tool can help sustain, project, and amplify culture through effective engagement with employees and candidates. From job description writing to employee coaching, new generative AI tools, built on ethical principles, can help organizations instill their culture through sourcing to onboarding.
Here I highlight four key steps that leaders should pay attention to for building the right “hiring culture” and how AI can help. Due to my own experience in the selection process, more emphasis is placed there, but all 4 steps are equally important.
1. First Impressions Matter: The Job Description and Career Site
The job description is often the first interaction potential employees have with your organization. The language used, the values highlighted, and even the requirements listed can say a lot about your culture. For instance, emphasizing teamwork and collaboration suggests a culture valuing collective success over individual achievements. Using gender-neutral language can help attract a candidate pool that is gender diverse. These indicators give candidates an upfront understanding of what you prioritize and allow them to self-select based on fit.
Companies can enhance this first impression by providing more interactive means to get to know the organization rather than using static career websites filled with a lot of content. While some organizations do a great job in structuring the content and including more engaging content such as videos from existing employees, FAQ’s etc, these approaches fail to address questions a potential applicant might have in a timely manner. In a high-volume recruitment scenario, it is impossible to have human recruiters answer thousands of questions via phone or text chat.
This is where smart chatbots built on top of generative AI like Sapia.ai‘s Phai, a careers site assistant, can help. Phai can ingest all the relevant content on a website (or other sources) and then provide fast personalized responses to candidate queries, 24/. Phai not only enhances the experience but also increases the chances of a candidate completing the application process. Chat with Phai yourself by clicking the blue icon in the bottom right of your browser.
2. The Selection Process: What You Value in Candidates
The selection criteria and the selection process are reflections of what the organization values. Prioritizing skills over experience may indicate a culture that values continuous learning and potential. An interview is a common step in the selection process and most of the time it is unstructured and fraught with bias. We can all fall victim to various unconscious biases at this stage (and sometimes practice conscious ones too, unfortunately). As an example, here are 4 common ones that I have noticed in fast-paced growth environments like startups:
- Urgency bias: Rushed decisions to prioritize immediate needs over long-term goals when making hiring decisions. (We need to fill this role this week!)
- Confirmation bias: The tendency to interpret or favor information that confirms one’s preconceptions and ignore other relevant details. (This candidate comes from ABC Inc. They must be good!)
- Halo effect: Tendency to base an overall impression of a candidate on one positive trait or experience. (Wow! Their presentation slides looked amazing!)
- Dunning-Kruger effect: Individuals with limited skills or experience might overestimate their abilities in an interview and this overconfidence can sometimes be persuasive. Leaders who are inexperienced in a specific subject matter, for example, a non-technical founder who is recruiting an engineering manager, can be susceptible to this bias.
One way you can interrupt these human biases is to include an AI assistant in the process. This is where tools like Sapia.ai’s Chat Interview™ can help. Chat Interview™ conducts a chat-based structured interview that is scored by AI. Structured interviews are found to be high in validity and low in bias among the many options available to assess candidates. Hiring managers get access to a detailed report called Talent Insights (Ti) that can challenge some of their biased views and help them make better hiring decisions. For instance, independent research conducted using the Sapia.ai Chat Interview™ found a 36% reduction in the gender gap relative to recruitment without AI. One of the practices the Sapia.ai Chat Interview™ encourages is asking value-based interview questions to gauge alignment with company values. For example “Could you tell me about a time when you went above and beyond to help a team member at work?”.
3. Onboarding: The Introduction to Culture
The onboarding process is a critical stage for instilling organizational culture in new hires. Effective onboarding programs that align new employees with organizational values and expected behaviors can have a lasting impact on their integration and success within the company. As more companies become distributed and rely on remote work, part of company culture can be collaborating effectively over tools like wikis, and messaging apps like Slack and email. This requires making sure a new hire knows how to use these tools well and content norms specific to the company. This also brings to light the importance of “connection” as part of building culture, as in a remote work environment you have to be more intentional in building connections than when working together in an office. You can read more on this in “HR for the world of tomorrow“ where we discuss the changing landscape of work and how smart chat is the new medium for building connections.
4. Feedback and Continuous Improvement: Sustaining the Culture
How feedback is provided during the hiring process and the onboarding period can also be a cultural indicator. A culture that values growth and development is likely to provide constructive feedback to candidates (whether they are hired or not) and to new employees in an effective manner. This is the philosophy that Sapia.ai Chat Interview™ follows with My Insights, a feedback email every candidate gets after completing the chat interview that includes personality insights and coaching tips. The Sapia.ai Talent Insights report provides similar insights to the hiring managers that help them prepare for onboarding a new hire.
In essence, every aspect of the hiring process – from the job description to the final decision – is a reflection of your organizational culture. By being mindful of this, organizations can ensure they not only attract the right talent but also reinforce the culture they aspire to maintain and develop. AI can be used as a tool to mitigate biases, form a consistent process, and enhance the candidate experience to better reflect the company culture.
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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.
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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.