There is something slightly strange about the way Hollywood makes films today. We have reached a point where studios can analyse audience preferences, track streaming habits and use predictive algorithms to estimate which stories are most likely to succeed, sometimes before a camera has even been switched on. On paper, this sounds like progress. Why spend millions on a film nobody wants to watch when data can help identify what audiences enjoy? Yet I wonder whether, in our eagerness to understand what people want, we have become a little too comfortable giving them what they already know.

The endless sequels, familiar franchises and recycled storylines are not exactly new, but the technology behind filmmaking has made predicting audience behaviour increasingly sophisticated. Machine-learning models identify patterns in historical data, helping studios assess which genres, actors and narrative structures might generate returns. The problem is that recognising a successful pattern is not the same as understanding why it succeeded. When commercial decisions become too dependent on historical performance, experimentation begins to look like an unnecessary risk. Hollywood starts behaving less like a creative industry and more like an algorithm optimising for predictable outcomes.

Perhaps the most interesting way to understand this is through the concept of a feedback loop. Recommendation systems use our viewing history to suggest films we might enjoy, and our subsequent choices provide more data for future recommendations. This is not inherently harmful, but it can reinforce existing preferences at the expense of discovery. The Truman Show offers an interesting parallel: Truman’s carefully constructed world is designed around predictable behaviour, leaving little room for experiences beyond its boundaries. Real algorithms are hardly Truman’s producers, but the comparison raises an important question about how much our environments influence what we come to expect.

Yet some of cinema’s most memorable experiences emerge precisely from uncertainty. Before watching Inception, we might never have imagined that a complex narrative about dreams could become such an engaging cinematic experience. Its layered storytelling challenges audiences rather than simply reproducing familiar formulas. This illustrates a fundamental distinction in computer science: exploitation involves using what is already known to work, while exploration involves testing possibilities whose value remains uncertain. An industry that prioritises the former indefinitely risks overlooking the latter.

There is also a deeper problem with measuring success. Opening-weekend revenue, streaming completion rates and audience ratings are useful metrics, but they remain proxies for something far more complicated. Interstellar, for instance, offers spectacular science fiction while exploring time, grief and human connection. A model can measure engagement with a film, but those measurements cannot fully explain why its ideas might remain with someone for years. The issue is not that human responses cannot be studied; it is that no single metric can adequately represent artistic value.

I understand the logic. Studios have employees, investors and financial risks to consider, and data can help unconventional films find their audiences. But there is a difference between using technology to inform creative decisions and allowing measurable outcomes to determine the boundaries of imagination. Perhaps cinema’s greatest strength lies in its ability to change our preferences rather than merely satisfy them. The real danger is not that computers will eventually become capable of predicting what we want to watch, but that we might become so dependent on their predictions that we stop discovering what we never knew we wanted.

Gaming is often seen as a distraction from learning, yet it involves strategy, collaboration and problem-solving. Do you think gaming is overlooked as a space where students can develop skills that classrooms may not always nurture?

Gaming is often seen as just a distraction, yet it builds skills that classrooms oftentimes overlook. Strategy games demand quick thinking, planning, and risk management under pressure. Online multiplayers need communication, leadership, and collaborative problem-solving, teaching players to work well within teams to achieve their objectives. Unlike normal learning environments where failure often carries punishment, gaming normalizes trial and error. It trains people to find their mistakes, refine strategies, and keep pushing through setbacks. This builds a resilient, growth-oriented mindset. By gamifying challenges, gaming transforms instruction into active learning, developing crucial real-world skills perfect for the modern workforce.

Having been recognized for your teaching methods, what do you think is the key stepping stone in making a connection between students and teachers?

I believe the key stepping stone in building a strong connection between students and teachers is trust, patience and understanding. Teaching is not just about sharing knowledge it is about creating a surrounding where students feel heard, valued and gets encouraged to express themselves without any fear of being judged. A teacher should connect with  each and every student individually and understand them on a personal level and make them comfortable enough to be themselves, because ultimately students learn best from their teachers and when they know that the teacher has faith in them and believes in their potential and is always there to guide and support them both academically and personally.

Technology devices offer enormous educational value but also constant distraction. What is one thing that students should keep in mind to maximize the best of both worlds?

Ans) Students should remember that a device is only as useful as the intention behind each tap. Before opening any screen, ask a simple question: “What am I here to do?” If the answer is to research, write, or learn, stay on that task and close everything else. The same tablet that delivers world-class lectures also holds games and endless feeds, and the difference lies in who is steering. Treat attention as a limited resource worth protecting. Silence notifications, set a clear goal for each session, and take real breaks away from the screen. When purpose guides use, technology becomes a powerful tutor rather than a tempting distraction, and learning gets the best of both worlds.

As a teacher who has watched students take on these responsibilities, what changes do you see in them when they’re accountable for an event with real stakes, and how do you decide when to step in and when to let them figure it out on their own?

Over the years, I have seen a gradual change in the nature of responsibilities handled by students. Earlier, these used to be restricted to department-specific work like Design, Quizzing, Sudocrypt, etc., but today, students handle almost everything – from sponsorship and administrative work to printing and even ushering.

This has broadened the way students work and handle responsibility. As their horizons widen, they learn not only about the world, but also about themselves – their strengths, limitations, and ability to take ownership.

As a teacher, it also teaches us when to step back and let them figure things out – when to fail, learn from their mistakes, and grow – and when to step in and guide them. As the saying goes, “Teachers can open the door, but you must walk through it yourself.”

With technology evolving so quickly, how do you see the role of school clubs changing from platforms for learning and collaboration to spaces where students can actually build and implement their ideas, and what do you think makes that transition possible?

Ans) Having taught Mathematics for over 35 years and now serving as a Vice Principal, I believe school clubs must evolve from being merely platforms for learning and collaboration into launchpads for innovation, experimentation, and real-world problem-solving.

In a rapidly changing technological world, students should not just learn about technology; they should use it to identify problems, develop solutions, build prototypes, and create something meaningful. Whether it is a Mathematics Club, Robotics Club, Coding Club, or a Computer Club (like Exun in our school), every club should encourage students to move from “What can I learn?” to “What can I create?”

This transition becomes possible when schools provide three essentials: freedom to explore, guidance from mentors, and opportunities to implement ideas. Students must be encouraged to experiment, collaborate across disciplines, learn from failures, and refine their solutions.

Technology provides the tools, but curiosity provides the spark, and perseverance turns ideas into reality.

The true success of a school club is not measured by the activities it conducts, but by the ideas it inspires and the impact its students create.

Coding is often taught as a rulebook, but many programmers say the real skill is breaking a big problem down into smaller steps. If you had to teach one, what would it be, to code or make them think like a coder? How would you teach them to tackle problems?

Ans) Don’t Just Teach Children to Code. Teach Them to Think Like Coders.
Having taught Computer Science and trained teachers for 36 years, I firmly believe that logic, reasoning, and problem-solving are abilities that exist within a child from birth. Our responsibility as educators is not to create these abilities, but to nurture and help them to use these to solve problems..

Long before children encounter a computer, they recognise patterns, understand cause and effect, make choices, and find ways to overcome everyday challenges. Coding simply provides them with another language to express their thinking.

If I had to choose between teaching children how to code and teaching them how to think like coders, I would choose the latter without hesitation. Programming languages may change, technologies may become obsolete, and AI may generate code, but logical thinking and problem-solving will always remain valuable.

Start with problems, not programming languages –
 Ask children how they would organise their school day, plan a journey, or prepare for an unexpected situation. Such activities naturally introduce sequencing, decision-making, and logical reasoning.

Teach them to break big problems into smaller units.
A complex task becomes manageable when divided into simple, solvable steps. This is the essence of computational thinking.

Encourage them to ask “Why?” and “What if? – Questions develop curiosity, challenge assumptions, and help children anticipate different possibilities.
Let them make mistakes.  An error is not a failure; it is feedback. Instead of immediately correcting a child’s code, ask what they expected, what actually happened, and how they can identify the difference. This builds resilience, confidence, and independent thinking.

In the era of AI, the teacher’s role becomes even more important: to help children evaluate solutions rather than blindly accept answers.

After 36 years in education, my conviction remains unchanged: When you teach a child to code, you teach a skill, which helps  a child to think like a coder, and you equip them to solve problems for life.

We, Not I, the belief that you have instilled in us says that a  team achieves more than its most talented individual. Can you tell us about a time when a brilliant individual, who depicted this very idea in some instance by exhibiting teamwork?

Ans) Every day at Exun is a living testament to the power of collaboration, where mentors and members inspire one another to grow, create, and achieve together. At the heart of this journey lies the club’s timeless motto, “We, Not I”—a powerful reminder that true success is not about individual achievements alone, but about the collective strength, shared learning, and lasting bonds that make a team extraordinary.