Dylan’s job interview scene in 'Severance' is too relatable. Shall we skip this part of hiring?

If you've recently been watching Apple’s dystopian, sci-fi series Severance, you may recall a sequence in which one of the characters, Dylan, undergoes an absurdly dull interview. This takes place with the ‘Great Doors’ manufacturing company (after Dylan was let go by Lumon Industries — the corporation the show revolves around).

The scene is surreal yet painfully relatable; a cumbersome Q&A filled with awkward pauses, hollow and generic questions, and a recruiter who seems as disengaged as the candidate in parts. It makes for great entertainment, of course, but unfortunately it's an exaggerated portrayal of what many job seekers endure: interviews that feel more like scripted performances, rather than meaningful assessments of skills or fit.

What's the ‘Severance’ series about?

‘Severance’ is a sci-fi thriller series that explores a dystopian workplace, where employees undergo a medical procedure to separate their work and personal memories. By doing so, their "work selves" — known as 'innies' — have no recollection of life outside the office, while their 'outies' remain unaware of what happens at work. It’s an exaggerated, uncanny (and sometimes, comical) take on corporate culture, and the eerie mundanity of classic office life.

The standard interview: an awkward, unnecessary grind

For job seekers, these interviews often become exercises in endurance, repeating rehearsed answers about strengths, weaknesses, and future aspirations. For recruiters, the process can be equally frustrating, often failing to surface the best candidates or, worse, advancing those who aren't the right match.

Traditional hiring models often rely on these outdated methods that waste time for both parties. But what if we reimagined this process entirely? Instead of slogging through unproductive interviews, we could leverage technology to uncomplicate hiring and make it more precise. With AI-based recruitment tools already here, the early stages of hiring can be a smarter, faster, and fairer process.

The early interview process needs an overhaul

Despite the best efforts of recruitment teams, early-stage interviews often fall into the kinds of predictable, ineffective patterns depicted in Severance. Some of the most common pitfalls include:

1. Unstructured interviews that don't assess the right skills

Many first interviews rely on casual conversation rather than structured, competency-based questions. While this more relaxed approach has its positives, it can also lead to hiring decisions based more on personality fit than actual ability to perform the job.

Research indicates that unstructured interviews have a lower predictive validity (0.23) compared to structured interviews (0.31), suggesting they are less effective in forecasting job performance.

2. Bias in hiring that skews the process

Even with the best intentions, unconscious bias can infiltrate hiring decisions. Factors like a candidate's background, appearance, or even the interviewer's mood can influence outcomes. Unstructured interviews are especially susceptible to these biases, which can result in less suitable hires, and the overlooking of highly qualified candidates.

3. Redundant and repetitive hiring stages

Many companies subject candidates to multiple rounds of interviews, often covering the same ground. While this is about finding the best match, it can also lead to fatigue on both sides, making it harder for recruiters to differentiate candidates, and for job seekers to remain engaged.

4. Failure to gauge real-world performance

Some roles need specific technical or problem-solving skills that traditional interviews can't adequately assess. Companies that rely too heavily on hypothetical questions may end up hiring based on communication skills alone, rather than actual ability to perform the job.

With all these in mind, it's unsurprising that hiring decisions often don't yield the desired results. But re-thinking the process entirely — and bringing in intuitive tech — can help companies and candidates find better matches, in a less stressful format.

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How smart tech can improve hiring

Rather than replacing human recruiters, AI and innovative tech boosts the hiring process by taking over tasks that are inefficient or prone to bias. By integrating these tools in the early stages of recruitment, your company can make hiring more objective and data-driven. Here’s how:

1. AI-fuelled screening for skills matching

Before a candidate reaches an interview, AI can analyze resumes and portfolios against job descriptions to identify top matches. However, unlike traditional keyword-based applicant tracking systems (ATSs), modern AI tools assess experience, past projects, and even written responses to understand a candidate's actual capabilities. This approach reduces mismatches and results in a higher-quality talent pool — before the first conversation even occurs.

2. AI-led pre-interviews to filter for fit

Instead of subjecting candidates to tedious first-round interviews, AI-driven conversational tools can conduct initial assessments. These AI interviews use natural language processing to ask relevant questions, gauge responses, and analyze tone and engagement.

This would all be personalized to a candidate’s resume and experience, doing away with tedious cover letters. This process removes the wasted time element of basic screening calls, so hiring teams can focus on the best fits.

3. Structured AI-based assessments to reduce bias

AI can standardize early-stage assessments, focusing purely on skills and qualifications rather than unconscious biases. By automating parts of the decision-making process with clear, measurable criteria, AI can help candidates progress based on merit rather than subjective impressions.

Notably, 68% of recruiters believe that AI can help eliminate unintended bias in the hiring process, although it’s important to note that AI is only as fair as the data it learns from. If trained on biased hiring patterns, it can (and has) reinforce discrimination rather than eliminate it. 

To mitigate this, it’s important that AI used in early stage hiring processes is built with diverse, representative data, and regularly audited for fairness. By designing AI to actively counter bias — not replicate it — employers can create a hiring process that is both efficient and genuinely equitable.

It’s also essential that AI is used in combination with real team interaction, rather than replacing it altogether when hiring.

Maybe the cover letter should be dead

Cover letters have long been a job application staple, but are they really efficient — for either party? For roles where writing ability isn’t a key element, could this early stage of the application process be more effective, if not reformulated entirely?

AI-driven questionnaires: a smarter way

Instead of forcing candidates through the outdated cover letter ritual, companies can use AI-powered, targeted questionnaires to assess fit for many roles. These role-specific prompts can quickly gather relevant skills, experiences, and problem-solving approaches, offering recruiters a clearer picture of each candidate — without making applicants write a self-promotion essay that doesn’t speak to their skills in action very well.

This can work through:

• More relevant insights: Structured, job-specific questions provide real data, not fluff.

• Faster screening: AI-driven assessments speed up hiring without sacrificing depth.

• Fairer evaluation: Candidates are assessed on responses and skill, not writing style.

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Work sample tests might be a better way to predict job performance

If the goal of an interview is to assess a candidate’s ability to do the job, why not have them actually do part of the job? Work sample tests — where candidates complete tasks that mirror real job responsibilities — are one of the most reliable predictors of future performance.

A meta-analysis published in Personnel Psychology found that work sample tests have a predictive validity of 0.54, significantly higher than unstructured interviews (0.23)​. This means they are much better at forecasting job success than traditional Q&A sessions.

This method is also more inclusive, particularly for neurodivergent candidates. Traditional interviews tend to reward candidates with strong verbal skills, quick social responses, and confident eye contact — none of which are totally necessary for all types of job performance. By focusing on actual work output instead of interpersonal performance, work samples can help to create a more fair candidate analysis.

To implement it, you can:

• Set simulated projects: Give candidates a small-scale version of a real task they’d encounter on the job. This could be writing a press release, debugging a piece of code, or creating a marketing plan.

• Enable flexible submission formats: Allow candidates to present their work in different ways — written, recorded, or through slides — so they can showcase their skills in the medium they are most comfortable with.

• Set clear expectations: Provide explicit instructions and extra processing time, which benefits all candidates but is especially helpful for neurodivergent applicants.

If it's time for a live interview, structure it

Most interviews are wildly inconsistent. One candidate might get asked about their technical expertise, while another is grilled on cultural fit. This lack of structure allows unconscious bias to creep in — whether it’s favoring people who “feel like a good fit” (often code for shared background and interests) or penalizing those with different communication styles.

Structured interviews offer a solution. In this format, every candidate is asked the same set of predefined, job-relevant questions. Their responses are then scored standardized metrics, reducing the influence of subjective impressions.

A landmark study in the Journal of Applied Psychology found that structured interviews have a predictive validity of 0.51— more than double that of unstructured interviews​. Companies that implement structured interviews often see more equitable hiring outcomes, and stronger long-term retention.

To implement it:

• Use a scoring system. Define clear criteria for evaluating answers and rate candidates consistently.

• Ask behavioral and situational questions in multiple formats. Instead of vague “tell me about yourself” queries, ask “Can you describe a time when you handled [specific challenge]?” Also, allow written responses for those who process information differently.

• Train interviewers on neurodiversity inclusion. Traditional hiring norms can be exclusionary. Teach recruiters to recognize and accommodate different communication styles rather than unintentionally marking candidates down for them.

Making hiring neurodiversity-friendly: beyond one-size-fits-all 

Hiring processes are often unintentionally designed for neurotypical candidates, assuming comfort with face-to-face conversations, rapid-fire questioning, and ambiguous social cues. But for autistic candidates, those with ADHD, or other neurodivergent thinkers, these setups can be major barriers — especially when they don’t reflect the actual job demands.

Studies show that companies that actively accommodate neurodivergent candidates not only build more diverse teams but also outperform their peers. A report from JP Morgan found that their Autism at Work program led to 48% higher productivity in certain roles compared to their neurotypical counterparts​.

To implement it:

• Offer alternative interview formats. Instead of forcing candidates into traditional interviews, provide options like pre-recorded video responses, written answers, or problem-solving exercises.

• Provide interview questions in advance. Spontaneous, high-pressure Q&A formats can disadvantage neurodivergent candidates. Giving questions ahead of time allows them to process and respond thoughtfully.

• Adjust environmental factors. Fluorescent lighting, background noise, or crowded interview spaces can be distracting or overwhelming. Offer quiet, controlled settings or remote interviews when possible.

• Rethink ‘culture fit’ as ‘culture add’. Many hiring managers default to choosing people they “click” with. Instead, focus on how a candidate’s unique strengths will enhance the team, not just blend in.

By expanding beyond rigid, neurotypical-centered processes, companies tap into an often-overlooked talent pool and create a workforce that succeeds because of diverse perspectives.

Do something different, hire more effectively 

Hiring shouldn’t feel like an endurance test — for candidates or recruiters. Instead of subjecting job seekers to redundant, anxiety-inducing interviews that fail to measure actual skills, companies can adopt research-backed methods that make hiring faster, fairer, and more effective. 

As AI tools become more advanced, HR teams that leverage them can make better hires — in less time — without subjecting job seekers to unnecessary hurdles. In practice, this means:

• Smarter hiring cycles: Work sample tests and structured interviews eliminate wasted time on subjective, meandering conversations that don’t predict job performance. Instead, they focus on real-world abilities from the start.

• Faster hiring cycles: AI can rapidly evaluate applications and conduct pre-interviews, significantly reducing the time to hire. 

• More accurate candidate assessments: Research consistently shows that structured interviews (0.51 predictive validity) and work sample tests (0.54 predictive validity) outperform unstructured interviews in predicting job success. Companies that use these methods make better long-term hires​.

• Reduced bias and greater inclusivity: Standardized assessments minimize the influence of gut instincts and unconscious bias. Neurodivergent candidates, who may struggle with traditional interview formats, can thrive when given clear, structured evaluations or alternative formats. Plus, standardized AI assessments minimize subjectivity and focus on data-driven hiring decisions.

• More accurate matches: AI-led evaluations focus on actual skills and experience rather than gut feelings, leading to better long-term fits. Approximately 86.1% of recruiters using AI technology have reported a faster hiring process.

• A better experience for job seekers: Candidates aren’t forced to perform social gymnastics in high-pressure interviews. Instead, they are evaluated on their actual work and given the opportunity to showcase their strengths in a way that makes sense for them. They also wouldn't have to deal with redundant or poorly structured interviews that don't meaningfully assess their skills.

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Skipping the bad parts, keeping the best

The interview depicted in Severance may be an exaggerated satire of today's hiring processes, but it resonates so much because it reflects real frustrations. Interviews don't need to be dull, awkward, or inefficient — especially when technology can step in to improve them.

By integrating AI into the early stages of hiring, your company can eliminate the frustrating, ineffective parts of the process while preserving the human elements that truly matter. This shift isn't just about making hiring faster; it's about making it better for both job seekers and recruitment teams.

Perhaps it's time to rethink how we hire. By leveraging technology to streamline and enhance the process, we can create a system that works for everyone — a future less dull and dystopian, and one worth interviewing for.