Galgotias, Performance Culture, and the Real Lessons from India’s AI Summit

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When a short clip from Galgotias University went viral during India’s recent AI Summit, it quickly turned into a spectacle. Social media platforms looped, remixed, and ridiculed a professor’s ambitious claims about innovation. Memes flooded timelines. Comment sections filled with sarcasm. What began as a routine campus demonstration transformed into a national embarrassment.

But beneath the humor and humiliation lies a deeper question: who is really to blame? Is it one professor overstating her work? A university eager for visibility? Or a media ecosystem that no longer distinguishes between journalism and public relations?

The controversy began when DD News, India’s public broadcaster, aired a segment highlighting innovations at Galgotias. In the interview, a professor confidently described projects as “end-to-end engineering.” However, a student standing beside her hesitantly clarified that certain equipment, including a 3D printer, had been provided by the university rather than built entirely from scratch. That moment of contrast—between confident exaggeration and cautious honesty—became the clip’s turning point.

Any newsroom guided by editorial skepticism might have paused. Was this a genuine innovation story, or promotional content dressed up as reporting? Yet the segment aired without critical scrutiny. Within hours, it was viral. The professor became the face of ridicule. The university’s credibility suffered. The broadcaster’s judgment was questioned.

However, isolating blame to one individual misses the larger systemic issue. The Galgotias episode reflects a broader performance culture that has seeped into institutions across the country. In such an environment, visibility often outweighs substance. Alignment with power structures can become more valuable than intellectual rigor. Loyalty is rewarded; skepticism is discouraged.

Over the past decade, critics argue that public discourse in India has increasingly prioritized allegiance over inquiry. Television news debates frequently resemble theatrical contests rather than informed discussions. Prime-time programming, associated with personalities such as Sudhir Chaudhary, has been criticized for amplifying polarization instead of encouraging analysis. When media spaces prioritize spectacle and ideological reinforcement, the boundary between reporting and promotion blurs.

Universities are not immune to these pressures. As institutions compete for recognition, funding, and influence, some may adopt similar performance-driven strategies. Instead of nurturing questioning minds, campuses risk becoming stages for carefully curated narratives. Students have often voiced concerns about shrinking spaces for dissent, expressing fears that critical inquiry may invite labeling or backlash.

Innovation, however, cannot thrive in an atmosphere that penalizes questioning. Artificial intelligence, in particular, depends on experimentation, doubt, iteration, and peer review. A culture that values applause over accuracy may generate impressive demos, but it rarely produces durable breakthroughs.

Yet the Galgotias controversy does not define the entirety of India’s AI ambitions. Beyond the viral clip, India’s first AI Summit revealed a quieter, more promising reality. Away from headline-grabbing stalls, serious work was underway.

Organizations such as Wadhwani AI, AI4Bharat, IIT Madras, Gnani.ai, and Plenome showcased projects focused not on global spectacle but on local constraints. Their questions were practical: Can AI assist farmers facing unpredictable weather? Can it support ASHA workers managing rural healthcare demands? Can systems function effectively in regions with patchy internet connectivity? Can AI tools operate seamlessly in Indian languages, extending access beyond English-speaking elites?

Globally, much of the AI conversation is capability-driven. How realistic can generative video become? How sophisticated are large language models? How quickly can autonomous agents perform complex tasks? Viral demonstrations—such as hyper-realistic AI-generated celebrity videos—highlight technical prowess. But technological capability alone does not define progress. The more critical question is: what problem is being solved?

In India’s context, the problems are distinct. Overburdened doctors, under-resourced teachers, language barriers in governance, and uneven digital infrastructure present daily challenges. AI solutions tailored to these realities may not trend on social media, but they can create tangible impact.

The summit revealed young entrepreneurs traveling from cities like Latur and Bhopal, eager to participate in shaping this technological shift. Their ambition was not to replicate Silicon Valley or compete in geopolitical AI races against the United States or China. Instead, it was to build systems that address Indian constraints in Indian languages for Indian users.

This distinction is crucial. There is growing chatter about India’s “DeepSeek moment”—a symbolic leap that positions the country as a global AI powerhouse. Yet technological nationalism can become another form of performance culture. Competing for headlines about dethroning global giants risks overshadowing quieter, meaningful progress.

The central issue, therefore, is not whether India can produce astonishing AI capabilities. It undoubtedly can. The deeper issue is who defines the problems AI is meant to solve. If engagement metrics and viral reach dictate priorities, the result will be more synthetic spectacle—polished demos and dramatic announcements.

If, however, policymakers, educators, and technologists prioritize institutional bottlenecks and social constraints, AI will manifest differently. It will appear in agricultural advisories delivered in regional dialects. In diagnostic tools that assist rural clinics. In assessment platforms that help teachers evaluate students more efficiently. These systems may never trend on Twitter, but they could quietly improve millions of lives.

The Galgotias episode stands as a cautionary tale. It illustrates what happens when performance overtakes substance, when journalism echoes promotion, and when institutional incentives reward exaggeration. At the same time, the AI Summit’s substantive projects offer a counter-narrative—proof that thoughtful, constraint-driven innovation is possible.

India’s AI dream does not hinge solely on computational power or global rankings. It hinges on cultural choices. Will institutions reward questioning or compliance? Will media prioritize scrutiny or spectacle? Will universities cultivate thinkers or performers?

If applause becomes the primary currency, more “six is nine” moments will follow—briefly viral, quickly forgotten, but corrosive in the long term. If accuracy, humility, and problem-solving guide the journey, India’s AI ecosystem may grow more slowly—but far more sustainably.

The choice between spectacle and substance will ultimately determine whether India’s AI ambitions become a fleeting performance or a lasting transformation.