John J. Kennedy | Chinese Robodog at Delhi AI Summit Exposed Failure of India’s Academia

The robotic dog that awkwardly trotted into the spotlight at the India AI Impact Summit last month is a far bigger problem for higher education than one university’s embarrassing moment. After the entire incident went viral, the institution in question apologised, explaining that a single, “ill-informed” staff member was to blame and insisted that there was no intention to deceive.

Frankly, that explanation is difficult to accept. Exhibits at a major global summit are not random. They are chosen, vetted, and approved through multiple levels of institutional review. To claim that a “clueless” staff member acted alone points to a deeper organisational failure. Either the university failed to check what it was presenting, or it assumed that it would not get caught. Both possibilities point to serious problems: failure of competence and failure of integrity.

The real issue, however, is not just about one university’s lapse; it is about the environment that makes such lapses possible, even almost predictable. Why do universities feel such a powerful need to inflate their achievements? In recent decades, they have been thrust into a fiercely competitive marketplace defined by rankings, accreditation scores, and recruitment numbers. They are not judged solely on teaching quality, but also on their ability to tell compelling “innovation stories”: how many patents were filed, how many labs were opened, how many AI centres were launched.

In this environment, how things look often matters more than what they are. Accreditation bodies play a role by rewarding tangible outputs such as patents, prototypes, and partnerships, often without digging too deep into their originality. Institutions respond by curating evidence for maximum impact. Most do so honestly. Some start to blur the line between what they actually built and what they simply bought.

This situation reveals a fundamental shift in the political economy of higher education.

Universities, especially in the private sector, where enrolment and investor confidence are critical, now operate as brands in an educational marketplace. Reputation needs to be manufactured quickly; you cannot wait decades to build a legacy. In this climate, looking capable often takes priority over actually building capability. Imported technology or purchased platforms can easily be reframed as in-house innovation. Buzzwords borrowed from the corporate world, like disruption, scaling, and ecosystem, are eagerly adopted, often without any rigorous academic verification. In a fast-moving field like AI, this blurring has serious consequences.

This is not a problem that is unique to India. Across the world, when careers and institutional reputations are built on measurable output, ethical guardrails can weaken.

International academia has seen its share of fabricated data, paper retractions from reputed universities, and exaggerated claims emerging from top labs. The root cause is the same: intense competition for prestige, supercharged by a focus on metrics. However, social media and online expert communities expose discrepancies in hours. The Galgotias story went viral precisely because its claim collided with a technically aware public that now watches these pronouncements with a sceptical eye.

The episode also points to a cultural shift: the growing temptation to confuse aspiration with achievement. Presenting potential as reality is tempting when funding, partnerships, and student interest flow to those who look the part. Regulators push for quantifiable innovation. Rankings reward publicity. Governments across the world want to bring about global competitiveness. Students want industry-ready credentials. Universities are caught in this web of incentives, and often, they internalise its logic.

The real danger is that higher education begins to mirror a broader technological trend now visible in India’s national AI push, where looking ready is mistaken for being ready, where a demonstration is mistaken for depth, and where a strong brand is mistaken for genuine capability.

In this climate, even well-meaning institutions can drift toward performative innovation, where putting on a show takes precedence over patient experimentation.

However, understanding these pressures does not excuse institutional failure. Universities are the custodians of credible knowledge. Their authority rests on public trust, the belief that their claims have been tested, not staged. If they dilute that standard, scepticism spreads beyond one institution to academia as a whole. This is a risk already visible globally. In AI particularly, credibility rests on verifiable facts: who built what, with which data, and with what intellectual contribution. Without that discipline, universities will produce graduates fluent in demonstrations yet dependent on systems designed and owned elsewhere. That path would leave India primarily as a consumer in the global AI order, not a creator of frontier technology.

How, then, to escape this trap? Accreditation systems must clearly distinguish acquisition from invention. Owning advanced technology is legitimate; misrepresenting its origin is not.

Universities need stronger internal governance over public claims, with verification processes for exhibitions and media statements that are as rigorous as academic peer review. Metrics should reward depth and reproducibility rather than raw patent counts. Leadership must champion intellectual honesty and resist shortcuts in branding. At a national level, this means sustained investment in genuine research capacity, in computing power, advanced labs, and long-term funding, so that institutions are not structurally pushed toward presenting imported goods as local innovation.

Of course, the unpleasant memories of the robot dog fiasco will soon fade. But, its significance should not. It showed how fast credibility collapses when image outruns reality and aspiration poses as achievement. It also exposed a growing fear of missing out on AI, the rush to appear AI-ready before becoming AI-capable. If Indian universities want lasting global trust, they must recall a simple academic truth: credibility cannot be branded; it must be built.

The writer is retired professor and former dean of the School of Arts and Humanities at Christ University in Bengaluru