By Saumia Bhatnagar
Illustrated by Paavas Bansal
Having recently entered the job market as a media and communications graduate, my day-to-day involves navigating a labyrinth of job listings in the field, each one offering a new set of challenges. Recently, as I lost myself amidst this whirlwind of a process, I encountered something entirely unexpected: an AI-powered interview. No human recruiter, no face-to-face interaction–only me, my voice, and an artificial intelligence conducting a live, audio-based interview. Deep down, I knew that this would not land me my dream job, but curiosity got the best of me. I could not resist the chance to experience firsthand what it meant to be assessed by an algorithm, so I dove into this digital enigma, unsure of what awaited me.
The AI interview was conducted via StarsHunt, a platform proudly proclaiming itself as the “World’s Best AI Recruiter”. One of the companies I had applied to used it as a screening tool. It served as an initial filter to shortlist candidates for the next round which would be conducted by humans. The flexibility was undeniably appealing. I could schedule the interview at any time, removing the usual hassle of aligning calendars and availability.
With a few clicks, I logged in, expecting perhaps a futuristic twist on the interview process, but what greeted me was far less dramatic. No smiling face, no casual pleasantries—just a blank screen. My highly anticipated Black Mirror moment failed to materialise. A brief chat with a support bot later, I managed to restart the interview. This time, my faceless AI interviewer was ready. On the screen, I could see my own image while a glowing purple circle appeared in place of the interviewer, radiating colour with each word it spoke. The AI’s voice was that of a female and was unmistakably robotic. It felt familiar as well as unsettling at the same time. There was a button to repeat the AI’s question if needed and a ‘talk’ button that I had to press each time I was ready to respond. Over the course of the next 30 minutes, the AI interviewer asked me a series of standard questions, covering my work experience, expected salary, and the usual ‘strengths and weaknesses’ routine. The interface was smooth and intuitive, but something was missing, something I had not realised I valued so much until it was gone: the human touch.
A warm greeting, a smile, even the obligatory comment about London’s dreadful weather—all these small, seemingly trivial gestures set the tone for an interview. They build rapport, however fleeting, and create a space where you feel comfortable expressing your motivations and aspirations. In contrast, this AI-driven process was clinical, almost efficient to a fault. Question. Answer. Repeat. It was a time-saver, no doubt, but the trade-off was palpable. There was no room for dialogue, no opportunity to ask about the company culture or the team I would potentially be working with—questions I would typically pose to a recruiter. Instead, it felt like I was feeding data into a void. I was left wondering who, or what, was on the other side, and whether anyone, or any algorithm, would truly understand what I brought to the table.
After 30 awkward minutes of spilling my professional life story to a faceless algorithm, the interview abruptly ended. No feedback or follow-up. Just silence. I never heard back. Was I not a strong enough candidate for the job, or had my desperation to secure employment been exploited to train the platform’s algorithm? We’ll never know. But the experience left me with more questions than answers, particularly about the future of recruitment.
AI-driven interviews like this raise serious concerns about how companies will select talent moving forward. On the one hand, they offer clear advantages. For candidates, they eliminate scheduling conflicts and the pressure of in-person interactions, providing the convenience of flexibility. A 24/7 interview platform caters to the busy lives of applicants, especially those juggling multiple applications. From an employer’s perspective, AI can screen a high volume of candidates quickly and objectively, theoretically removing biases that can creep into human-led interviews—whether based on gender, race, or other factors. It streamlines the hiring process, potentially reducing hiring timelines and thus, saving companies money on recruiter hours.
But for all its efficiency, AI misses a fundamental aspect of recruitment: the human connection. For candidates, an interview is not just a formality, it is a conversation. It is a chance to engage with the company, ask questions, and get an idea of its culture and values. The absence of this two-way exchange reduces applicants to mere data points, their potential boiled down to a set of pre-programmed questions and algorithmic interpretations. It can feel dehumanising, like talking to a wall rather than someone who could become your future manager or colleague. This lack of interaction might also deter top talent who look for meaningful connections with their prospective employers during the interview process.
Moreover, AI’s promise of removing bias is not foolproof. The technology is only as unbiased as the data it is trained on, and there have been numerous cases where AI systems have inadvertently perpetuated the very biases they claim to eliminate. Candidates from diverse backgrounds may find themselves at a disadvantage if the AI’s training data does not adequately represent them. There is also the question of transparency. Candidates rarely understand how AI makes its decisions and there is no recourse for those who feel they have been unfairly filtered out.
One critical improvement recruiters could implement is providing greater transparency around how AI-driven interviews work. As this technology becomes more prevalent, candidates need to be better informed about what to expect and how to navigate these new systems. Facing an algorithm with no understanding of how it evaluates your responses or what criteria it uses to measure your suitability for the role forces candidates to step into the unknown.
Going forward, recruiters should prioritise spreading more information about how AI-led interviews function. This could include details on what types of questions are asked, how responses such as tone, keywords or facial expressions are analysed, and how the algorithm scores candidates. Offering insights into what the AI is specifically programmed to look for, whether it’s technical skills, communication style, or problem-solving ability, would empower applicants to prepare more effectively, just as they would for a traditional interview.
Moreover, candidates should be made aware of how their data will be used and whether their responses might serve purposes beyond the specific job application, such as training the algorithm for future recruitment rounds. Clarity on this front would help ease concerns about candidates being reduced to test subjects for AI learning. By demystifying the process, recruiters can foster more trust in AI systems and level the playing field for applicants, ensuring that they are equipped to approach these interviews with confidence rather than uncertainty.
While AI has the potential to revolutionise the future of recruitment, currently it falls short in offering the nuance and empathy that human recruiters naturally provide. The real challenge ahead lies in striking a balance between the efficiency of AI and the emotional intelligence of humans, ensuring that technology enhances the hiring process without sacrificing its most vital aspect—genuine human connection.
