The Ugly Side of AI Hackathons in India
People in India often say that hackathons are great places to come up with new ideas, work together, and look for jobs. Students and young professionals rush to sign up, hoping that a weekend of coding will lead to jobs, money, or fame. The possibility is interesting. But after looking at the projects, it's clear that participants use old code, like basic neural networks and SVM in machine learning, to meet deadlines and impress the judges.
Hackathons and the False Idea of Overnight Innovation
Most Indian hackathons, turn problem-solving into quick prototypes that don't work well in the real world. Judges tend to give more points to flashy presentations than to ones that are technically deep. This makes participants want to do demos that "look good" but fall apart when they get bigger.
People in this culture think that speed is great and rigor is not important. The end result is a generation of coders who are good at making presentation slides but not ready for real-world problems.
The Recycled Code Problem: SVM in Machine Learning and More
One of the biggest problems with Indian hackathons is that they depend too much on pre-written templates and GitHub snippets. People often take open-source code and make small changes to it, claiming it as their own work. People often copy algorithms like SVM directly into their projects, even if they don't understand the math behind them.
Stress, Rewards, and the False Sense of Success
Another thing that makes this situation worse is that hackathons are becoming more commercialized. A lot of events have sponsors who want a lot of people to come and talk about them on social media.
Teams often put shortcuts first because they feel pressure to get results quickly. Teams don't want to deeply engage with data, test their assumptions, or build strong architectures. Instead, they just want to get to a "working demo" as quickly as possible. For instance, at a healthcare hackathon, several teams might submit very similar prototypes—basic apps with a user interface added to a borrowed classification model—but none of them would be able to handle the complexity of real-world healthcare data.
The Long-Term Effects on India's AI Talent Pool
The effects of this culture last long after the hackathon weekend. Students and engineers who are just starting out have the wrong idea about how AI systems are built. They begin to believe that sticking with something is less important than packaging it. Recruiters have also been careful about resumes that list "wins" from hackathons because they know that many of these projects aren't very deep or new.
Also, the focus on short-term rewards keeps people from getting involved in the less exciting but more important parts of AI research. A lot of hackathon teams don't spend time cleaning data, checking their results, or thinking about how their work affects other people. These are the skills that people in the field want the most. Without them, India might end up with a workforce that only knows how to use AI systems on a basic level and isn't ready for the more advanced ones.
What Needs to Change
To get their value back, hackathons in India need to change the way they do things. Instead of making quick prototypes, the people in charge should focus more on what students learn. There should be mentorship in the structure to help participants learn not only how to make things, but also why some methods work better than others. Judges shouldn't just look at how well the presentation is done; they should also look at how original the idea is, how scalable it is, and how well the problem fits with the solution.
The challenge for participants is to stop thinking about winning prizes and start thinking about learning real skills. It is not inherently bad to use tools like SVM in machine learning, but doing so without understanding or originality goes against the point of learning.
Final Thoughts
If people keep taking shortcuts, reusing code, and chasing prizes, these activities could become pointless exercises that do more harm than good. India doesn't need more people who win hackathons; it needs people who know that real innovation doesn't happen all at once or come from other people's ideas. It takes time, depth, and something special to get it.