Galgotias University's robotic dog fiasco: A symptom of a deeper issue in research and education
The world we inhabit today is one where universities are chasing products over concepts, prioritizing quick profits over deep theoretical research. This shift is particularly alarming in the natural sciences, where the beauty of abstract intricacies and the deep connections between science and technology are often overlooked. The introduction of the "practical PhD" in China, awarding degrees for engineering products, is a recent example of this trend. While this model may have its merits, it raises questions about the balance between product-oriented research and fundamental science.
In India, the disconnect between academia and industry is more pronounced. The Indian Institutes of Technology (IITs) have a strong presence in the industrial and corporate world through their elite alumni network, but their research labs often lack the same level of industry engagement. The start-up culture in cities like Bengaluru and Gurugram is also disconnected from nearby universities and research institutions, unlike the deep connections between Stanford and Silicon Valley or MIT and Route 128.
The recent incident at Galgotias University, where a faculty member "claimed" a Chinese-made robotic dog as designed by the university's Centre for Excellence, highlights the issue of universities prioritizing profit over creativity and research. This incident has sparked memes and laughter, but it also reveals the university's focus on for-profit ventures, often at the expense of quality and ethical standards. The impact of this approach on health and education is concerning, as 'profit' can overshadow the importance of fundamental knowledge and research.
The race for research products has reached its peak in artificial intelligence, where the quest for the most advanced 'product' may overshadow the humanity and socio-political reality of sustainable AI. Academics Arvind Narayanan and Akash Kapur suggest focusing on enabling infrastructure, governance, and citizen-friendly innovation over frontier models. While AI's trajectory seems unstoppable, there is still much to be done on the human and socio-political front, addressing issues of wealth inequality, political and social representation, and the impact on intimate relationships.
The author emphasizes the need to divert attention from the blinkered quest for the most advanced robots and instead focus on the broader implications of AI. The recent financialization of applied research at the University of Chicago, leading to significant losses, serves as a cautionary tale. The author concludes by highlighting the importance of maintaining a balance between product-oriented research and fundamental science, especially in the context of AI, to ensure a healthy and sustainable future for research and education.
