Introduction

Artificial Intelligence (AI), particularly generative models like ChatGPT and Gemini, has become both a boon and a challenge in higher education. Students increasingly rely on AI for assignments, summaries, coding, and even emails, while faculty members grapple with maintaining originality, academic honesty, and critical thinking. With AI growing faster than existing regulatory or pedagogical frameworks, Indian institutions are experimenting with varied approaches, ranging from outright bans to integration into curricula. The choices made today will determine not just the future of learning but also India’s knowledge economy and workforce readiness.

The Changing Landscape of Education with AI

How widespread is AI usage among students and teachers

1. IIT Delhi Survey (2024): Four out of five students admitted to using AI, often several times a week. One in ten subscribed to premium versions.
2. Faculty usage: 77% of surveyed teachers used AI for summarising papers, creating slides, or drafting communication.
3. Student motivations: Simplification of concepts, summarisation of material, mind maps, and scenario simulations.
4. Concerns: Errors in math, flawed debugging, weak context handling.

The integrity dilemma in classrooms

1. Blurred lines: Students question whether using AI counts as “cheating” or “time-saving.”
2. Academic honesty: IIT Delhi’s committee recommended rewriting plagiarism policies to require disclosure of AI use.
3. Critical thinking loss: Faculty fear students may accept AI answers as “Truth” without questioning them.

Institutional responses in India

• Policy innovations:
  1. IIT Delhi – integration of AI/ML in curricula, AI workshops, campus-wide licenses.
  2. IIIT Delhi – shifted evaluation to 90% exams, 10% assignments.
  3. IIM Ranchi – evaluation rubric for responsible AI integration.
  4. Shiv Nadar University – five-level “Gen AI Assessment Scale” from prohibition to responsible autonomy.
  5. Ashoka University – AI literacy courses, foundation modules, ethics of AI curriculum.
  6. Strict resistance: Some universities (Delhi University’s Dept. of Education) enforce “No AI” policies, insisting on handwritten assignments.

• Pedagogical experiments with AI

1. 1. Classroom integration: AI tools are increasingly used to automate routine tasks like code generation, freeing classroom time for higher-order problem-solving.
   2. Assessment innovation: Institutions are shifting towards interactive methods such as AI-assisted viva voce, project-based evaluation, and scenario testing to ensure genuine understanding.
   3. Ethics in curriculum: Courses on “Ethics of AI” and AI literacy modules are being introduced to sensitise students towards responsible and transparent usage.
   4. Balanced usage: AI is deployed after core concepts are taught, ensuring students retain critical thinking and do not outsource judgment entirely.

Global responses and comparative perspectives

1. USA: Princeton provides ChatGPT licenses; Oxford mandates disclosure but allows professors to decide; assignments redesigned to integrate AI.
2. Australia: TEQSA guidelines legitimise AI but require mandatory disclosure; oral exams and viva voce are making a comeback.
3. UK: Universities pilot TeacherMatic to ensure sector-wide learning models.

Conclusion

Generative AI has irreversibly entered the Indian classroom. The challenge is not whether to allow or ban it but how to regulate, integrate, and ethically harness it. From IITs’ committees to global universities’ adaptive models, the world is learning that AI can either weaken critical thinking or be a catalyst for higher-order learning. For India, the stakes are especially high: with its demographic dividend and growing tech economy, how students learn today will define the nation’s competitiveness tomorrow.

PYQ Relevance

[UPSC 2023]  Introduce the concept of Artificial Intelligence (AI). How does AI help clinical diagnosis? Do you perceive any threat to privacy of the individual in the use of AI in the healthcare?

Linkage: AI’s growing role in education parallels its use in healthcare, where it aids efficiency but raises ethical and privacy concerns. Just as AI in clinical diagnosis demands accuracy, transparency, and accountability, AI in classrooms requires disclosure, integrity, and critical oversight. Both contexts highlight the larger governance challenge of balancing innovation with responsibility.

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