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The Psychology of Interviews: They Want to Hire You

Every placement season at IIM Ahmedabad, companies would arrive on campus looking for people to hire. As a professor of communication, I had the privilege of watching this process from a vantage point very different from that of the students preparing for interviews.

For students, understandably, the interview could feel like a high-stakes evaluation. What if I say the wrong thing? What if I don’t know an answer? What if they find a reason to reject me?

But from the other side, something was equally apparent. These organisations had come to campus precisely because they wanted to hire. They had invested time and resources in recruitment. They wanted to find someone.

Recruiters want to hire you.

It sounds obvious. But it is almost the opposite of the psychology with which many of us approach interviews.

We imagine the interviewer sitting across from us looking for weaknesses. A difficult question feels like a trap. A moment’s hesitation feels disastrous. We enter the room thinking that our job is to avoid giving them a reason to reject us.

But think about the situation from the recruiter’s perspective.

They have a position to fill. They have spent time identifying candidates, reading applications, and conducting interviews. If you are sitting across from them, they already think you could be good for the role. They hope the conversation goes well. They would like you to turn out to be the person they came looking for.

That doesn’t mean they aren’t evaluating you. Of course they are. However, do not make the mistake of conflating evaluation with hostility. That distinction can change the way you experience an interview.

If you assume that the interviewer is looking for reasons to reject you, you begin anticipating traps. You become defensive. You overthink questions. You may become so preoccupied with producing the “correct” answer that you stop listening to what is actually being asked.

Instead, try asking yourself:

“What does this person need to know in order to feel confident hiring me?”

Then prepare accordingly. Think “What anecdotes, story buckets can help the interviewer see me in this position?”

Your task is not to produce a flawless performance. It is to help them understand what you can do, how you think, what you might bring to the role, and see you in that role.

A difficult question can then become something other than a threat. Perhaps there is an uncertainty they are trying to resolve. Perhaps they want to see how you think. Perhaps they are trying to understand whether something you have done before translates to what they need.

There is another psychological shift that follows from this:

You are not asking someone to do you a favour by hiring you.

They need something. You offer something. And the interview is a conversation in which both sides are trying to determine whether those things match.

And it really is both sides. While they are deciding whether they want to hire you, you are also learning about them. Do you want to work with these people? Does this role offer what you are looking for? Are their expectations compatible with yours?

Of course, none of this means you will always get the job.

You can have an excellent interview and still be rejected. Fitment is incredibly important. Recruitment is not necessarily a ranking exercise in which the “best” candidate wins. It is often about finding the person whose skills, experience, interests, and ways of working align most closely with the requirements of a particular role. A rejection, therefore, does not automatically mean that you performed poorly or were somehow inadequate. In fact, sometimes this can work in your favour, keeping you from ending up somewhere that clashes with your personality or working style.

What is important to remember is this: rejection is a possible outcome of an interview. It doesn’t have to be the assumption with which you enter one.

So the next time you walk into an interview, try replacing:

“They are looking for a reason to reject me.”

with:

“They are hoping I might be the person they are looking for.”

Because very often, they are. They want to hire you. Give them the opportunity to do so.

Peddi, Infrastructure, and the Politics of Visibility

One day, my husband casually wondered whether his village would even exist in a few decades. In that passing remark, I caught a melancholy that lingered long after the conversation ended. A nostalgia for a place that is still t/here, yet increasingly difficult to return to when life pulls us elsewhere. That moment expanded my understanding of what it means to belong to a place, and of what is at stake when a community fears losing its identity.

It was with this understanding that I watched the Telugu film Peddi.

My husband’s experience is not entirely comparable to Peddi’s. He does not occupy the kind of marginalised position the film depicts, and I do not mean to collapse those very different realities. But his reflections gave me a frame of reference through which the film’s central yearning — for recognition, for continuity, and the very right to exist as one’s own community — became emotionally legible. My husband has helped expand my world, giving me new ways of seeing and understanding experiences beyond my own.

Much has already been written about Peddi’s problematic representation of women and its treatment of consent . I won’t revisit those critiques here, but this review offers a thoughtful example. Suffice it to say, there are storytelling choices that are wholly unnecessary, distracting, and that substantially diminish what is, to me, its most compelling idea. Instead, I want to dwell on the idea that stayed with me long after the film ended.

At its heart, Peddi is about a village fighting for its rightful identity. Not merely being given a name, but everything that follows from being recognised: dignity, belonging, rights, and a place within the imagination of the state. The struggle is not just about daily survival but about being acknowledged in a way that counts and affords dignity, about identity. That is what makes the film’s central premise so powerful. And the train is at once a powerful narrative device and an evocative symbol.

As a media and communication scholar whose work draws on Science and Technology Studies (STS), I found myself thinking about the train in ways that extend beyond the film itself.

The train is, of course, a mode of transport. Yet, it does more than enable movement. Railways connect villages to markets, schools, hospitals, employment, and wider networks of mobility. They also connect communities to systems of administration and recognition. A railway station can put a village on the map. It can bring greater visibility, a recognised address, administrative connections, investment, and opportunities. It becomes part of the process through which a place is acknowledged by institutions that distribute resources and rights.

This is where STS offers a useful way of reading the film. Infrastructures are not neutral systems that simply enable movement. They are sociotechnical arrangements that shape who becomes visible, who is connected, who is counted, and who risks being forgotten.
The train, the railway line, the station in Peddi are part of the material infrastructure through which identity itself is produced and legitimised.

A village is more than a collection of houses and people. It is also a name on a map, an address in a database, a stop on a railway line, a place that institutions know how to locate (and send a gold medal to). Infrastructure helps transform a place from something inhabited into something acknowledged.

That, to me, is where the film is at its strongest.

Peddi stayed with me despite its flaws because it is about belonging, about whether a community is seen, remembered, and recognised. The train, railway line, and the station carry the possibility of visibility and being acknowledged.

It is a shame, then, that storytelling choices (such as the objectification of Achiamma) weaken the film’s political argument. A film about recognition, dignity, and the right of a marginalized community to be seen undermines itself when it refuses those same principles to its principal female character. These choices are wholly unnecessary. They distract from a reality many village(r)s continue to face 78 years after India’s independence and, ironically, reinforce another: even when communities secure recognition, it is often men who benefit from it while women continue to bear the brunt of invisibility. Across the country, communities still struggle for recognition, connectivity, and the basic infrastructures that make citizenship meaningful. That struggle, too, is intersectional. Recognition is not experienced equally; it is shaped by gender as much as it is by geography, caste, and class.

Managerial Communication in the age of AI

Someone I know remarked, “Now that we have AI, there is no need for Communication courses, right?”

I laughed.

At institutions like #IIMA and #ISB, communication faculty emphasize that we are not vocational schools and that Communication theory is central. How you translate theory into application and make it part of your skill set is ultimately up to you. However, there will be people who conflate communication with vocational skills.

Given the expectations placed on management education, institutes (understandably) want to integrate AI to ensure students are future-ready.

Since many people now use AI to generate emails, I designed an AI-integrated persuasive email-writing exercise and had all communication faculty conduct it across sections.

We chose a case that could be used for both “managing down” and “managing up.”
Basis this, students were asked to generate a persuasive email using AI. They were asked not to upload the case directly into any AI tool but to summarise the case themselves, provide context, and articulate the ask.

Once they generated the first email, faculty unpacked the case in class. We discussed persuasion, organisational dynamics, leadership communication, and relevant communication concepts. Armed with this understanding, students generated another email.

The first version: students were confident and happy with what AI generated.

I heard a couple of them and there were the tell-tale signs of AI-generated content, of course. But beyond that, AI completely flattened voice. Most emails read either profusely apologetic or authoritative.

So I asked: “Do you really think either Lisa or Daniel (the protagonists of the case) would be this apologetic? What do we know about them from the case? Would Lisa or Daniel, for the purpose of one email, suddenly change their entire personality? Even if they did, would the intended receiver believe this overnight change in personality?”

A collective oooh, that’s right!

Within organisational contexts, where interpersonal relationships and dynamics matter, people believe they know you as a person. They associate you with a certain leadership style, emotional range, tone, and managerial approach. When your AI-generated email sounds nothing like you, the receiver notices.

Students then inevitably asked:
“But ma’am, wouldn’t being warmer work?”

Context matters!

When you hand communication over to AI, and you are not generally an apologetic person, yet the AI-generated email makes you sound apologetic, or presents you as a collaborative leader when you are not, you are likely to create a much bigger problem for yourself.

Once this was done, they went back to their keyboards to generate a fresh email.

After about five minutes, one vexed student remarked, “It would have taken me much less time to draft one myself!”

Ha!

Persuasion, consensus-building, negotiation, and crisis management are deeply human activities rooted in judgment, relational understanding, and knowing what moves another person. AI cannot do this for you.

#ManagerialCommunication #AI #ISB #CommunicatingintheageofAI

The AI Rush: Organisations Holding the Key and Searching for the Door

A student in my (BPGP) class recently described how companies are investing heavily in AI tools and pushing employees to adopt them. These companies, he said, seem convinced that they are holding an important key, but are not yet sure which lock it opens.

The metaphor was funny, but also remarkably accurate.

Across industries, organisations sense that AI matters. There is urgency, investment, experimentation, and, increasingly, pressure to adopt quickly. Yet beneath this acceleration lies a quieter uncertainty. Many organisations still struggle to articulate where the real value of AI lies, what specific problems it is meant to solve, and how it meaningfully fits into existing systems of work and decision-making.

This is why metaphors matter. Good metaphors often reveal what people already intuitively feel but have not yet fully articulated. They translate ambiguity into something immediately recognisable. In this case, the metaphor captured something central about the current AI moment: confidence in the importance of the technology coexisting with uncertainty about its actual purpose.

In Science and Technology Studies (STS), scholars such as Bruno Latour, Langdon Winner, and Madeleine Akrich have long argued that technologies are never neutral tools. Technologies shape participation, distribute power, and organise social life. They enable action, yes, but more important that that, technologies structure the very action it seemingly only enables.

One useful way to think about technologies is as doors. Every technological “door” quietly raises political and social questions: Who is allowed in? Who is excluded? Who gets to decide? What behaviours become easier, rewarded, or even mandatory? And whose participation becomes impossible in the process?

Seen through this lens, the student’s metaphor becomes even more revealing. If organisations believe they possess an important key but do not yet know which lock it opens, then the uncertainty runs deeper than implementation strategy or return on investment. The uncertainty concerns purpose itself.

What kinds of problems are organisations actually trying to solve with AI? What forms of work are they attempting to optimise or replace? What assumptions about efficiency, productivity, creativity, or expertise are being built into these systems? And what kinds of institutional “doors” are being constructed as AI becomes embedded into everyday organisational life?

These questions matter because infrastructures tend to become invisible once normalised. By the time their consequences become obvious, patterns of access, exclusion, and authority are often already deeply embedded.

The current AI race frequently frames adoption as inevitable. Organisations worry about being left behind, employees feel pressure to adapt quickly, and markets reward visible experimentation. But speed can sometimes substitute for clarity. Adopting AI without deeper reflection risks creating systems whose social consequences are only recognised retroactively.

None of these concerns are entirely new. Social scientists, historians of technology, and STS scholars have long examined how technologies reorganise labour, identity, expertise, and power. From industrial machinery to algorithmic management systems, technological shifts have always carried questions about participation, authority, and institutional control.

What feels different today is the scale and speed of adoption combined with the cultural narrative surrounding AI itself. AI is often discussed simultaneously as inevitability, opportunity, disruption, and existential necessity. Under such conditions, critical reflection can easily appear secondary to implementation.

Yet this is precisely the moment when reflection becomes most necessary.

One of the privileges of teaching working professionals is encountering moments when participants, drawing directly from organisational life, articulate insights that resonate far beyond the classroom. Sometimes a single metaphor captures an entire historical moment more effectively than a long theoretical explanation.

The image of organisations holding an important key without yet knowing which lock it opens may be one of those metaphors.

#IIMA #BPGP #VUCA #AI #workplace #AItools