Beyond AI Hype: The Case for Basic Science
We stand at the threshold of a technological revolution globally. The nations that will lead in near future will not merely be those with abundant natural resources but those with strong scientific ecosystems. . .
We stand at the threshold of a technological revolution globally. The nations that will lead in near future will not merely be those with abundant natural resources but those with strong scientific ecosystems and highly skilled human capital in terms of artificial intelligence (AI), machine learning, robotics, biotechnology, quantum computing, and data science. Artificial Intelligence is built upon mathematics, statistics, algorithms, programming, electronics, and computational thinking. Every breakthrough in AI ultimately rests on a foundation of basic sciences. Scientists who develop large language models, autonomous vehicles, medical diagnostic systems, climate prediction models, or advanced robotics rely heavily on mathematical reasoning, scientific experimentation, and computational skills. In this context, the declining interest of majority of our students in basic sciences such as Physics, Chemistry, Mathematics, Biology, and Computer Science deserves serious attention. This discussion should not, however, be interpreted as a criticism of the humanities disciplines. Society requires historians, economists, linguists, philosophers, psychologists, political scientists, lawyers, journalists, teachers, and artists at every stage and at all time. Humanities and social sciences remain indispensable for understanding society, culture, ethics, governance, and human behavior. In fact AI itself raises ethical, legal, and social questions that cannot be answered by engineers alone. The point however is that a significant number of students choose humanities not necessarily out of passion for history, literature, political science, sociology, or philosophy, but because these disciplines are perceived as comparatively easier. Many students believe that these subjects require less mathematical ability, less mental exertion, fewer laboratory sessions, and comparatively lower academic pressure. This trend appears particularly visible in many colleges across Jammu and Kashmir, where admissions to science programmes have declined in several institutions while humanities classrooms continue to expand. Only a few years back Mathematics and Physicswere withdrawn as major subjects from 19 different colleges on account of a consistently poor enrolment. Such a shift, if driven mainly by the desire to avoid analytical rigor rather than genuine academic interest, may adversely affect both individual career prospects and the nation’s scientific capacity. Ironically, as AI becomes increasingly capable of generating essays, summarizing books, translating languages, and producing written content, many routine tasks traditionally associated with reading and writing are becoming automated. Consequently, careers that depend solely on reproducing textual information may face greater disruption than careers requiring scientific reasoning, experimentation, engineering design, and quantitative analysis. AI still depends upon human expertise for scientific discovery, engineering innovation, medical research, experimental design, and mathematical modelling. The future workforce will increasingly value people who can solve unfamiliar problems, build AI systems, verify AI outputs, design scientific experiments, interpret complex data, create new technologies and think critically beyond memorization. These skills emerge primarily through rigorous scientific and quantitative education. Therefore, students entering college today must prepare not merely for today’s employment market but for the demands of the next three or four decades. As per one of the reports of Times of India, the QS World Future Skills Index 2027 ranks India among the world’s leading AI-ready economies, placing it 13th globally. The report attributes this position to India’s growing emphasis on AI preparedness and future-oriented education. However, sustaining this position will require a continuous supply of graduates trained in science, technology, engineering, and mathematics (STEM). Studies on AI adoption in higher education also reveal the growing and obvious importance of scientific and digital competencies. A 2025 global survey by the Digital Education Council, involving faculty from 52 institutions across 28 countries, found that universities are increasingly integrating AI into teaching and research while emphasizing AI literacy for students and faculty alike. This was mentioned in Digital Education Council. Similarly as per Campbell Sites, surveys summarized in 2025 show that between 80% and 90% of university students worldwide already use AI tools in their studies. Rather than reducing the need for education, these findings highlight the importance of equipping students with deeper analytical, computational, and critical-thinking skills that enable them to work effectively alongside AI. Research focusing on Indian higher education also points to significant differences in AI preparedness across disciplines. A 2025 study involving students from various Indian institutions reported substantially higher AI literacy among technical students than among humanities students, despite widespread awareness of AI across all disciplines. The concern becomes even more pronounced in Kashmir because of inadequate research exposure. For Kashmir in particular, investing in scientific talent is not merely an educational necessity but a developmental imperative. In this context I want to bring about a strong critique of a recent report of KashmirLife asking if Kashmiri Colleges are ready for Gen Z. Instead it should have been if Gen Z is ready to take AI integrated courses offered by colleges and Universities nowadays. This is where the debate requires reorientation. Higher education institutions certainly have responsibilities to modernise laboratories, update curricula, recruit competent faculty, strengthen industry partnerships, and introduce interdisciplinary programmes. However, educational reform cannot succeed if students overwhelmingly gravitate towards subjects that require the least engagement with scientific and computational thinking while simultaneously expecting access to careers driven by artificial intelligence. There is also a deeper cultural issue. Society celebrates AI, machine learning, and data science as pathways to lucrative careers, yet many students avoid the foundational subjects that make these careers possible. No reform can shape the future, if learning and ambition drift apart. Dr. Qudsia Gani, Assistant Professor and Head, Dept. of Physics, Govt. Degree College, Pattan