Neeraj Saxena, Pro-Chancellor – JIS University, Kolkata

As we speed into a future shaped by Artificial Intelligence (AI), education is undergoing a profound transformation. Traditionally, technology has supported human learning—now, we’re entering a world where AI doesn’t just assist; it leads. This shift has turned the tables: humans are no longer just users of intelligent systems but part of the system itself.

1. The AI-Driven Learning Ecosystem

AI is no longer just a helper in education—it is becoming the main architect of the learning experience. Whether it’s a personalized lesson on quantum physics or a language-learning module tailored to a student’s pace, AI systems are increasingly efficient in curating and delivering educational content. What once required a team of curriculum designers and subject matter experts can now be automated with algorithms that evolve in real time.

What AI Can Now Do:

Example:

• A student learning calculus in a traditional classroom waits for weekly quizzes.
• In an AI-powered system, the platform generates real-time problems, tracks eye movement for attention, adjusts difficulty dynamically, and offers video explanations tailored to confusion points.

This ecosystem uses AI to curate content, generate critical questions, and even evaluate emotional responses to maintain engagement. AI doesn’t stop at content—it now crafts questions that assess deeper levels of cognition and can adapt to the learner’s progress, identify gaps in understanding, and recalibrate the learning path.

 2. The Great Inflection: From Human-Led to Machine-Led

Historically, humans created tools to help themselves: from the wheel to the computer. But with AI, tools are now learning from us—our teaching methods, content, and behavior become data for AI’s growth.

Throughout history, tools and machines have served as extensions of human capability—enabling us to generate knowledge, advance civilization, and improve quality of life. From the printing press to computers, technology has amplified human potential while remaining fundamentally under human direction.

Key Shift:

Example:

Teachers who upload thousands of lessons on platforms like YouTube or Coursera are indirectly training AI systems like ChatGPT or Khanmigo to generate similar or even better explanations.

This is the inflection point—AI evolves by consuming and reorganizing our intellectual output, flipping the traditional knowledge hierarchy. The machine is learning from us as we learn from it, creating a feedback loop where human learning becomes training data for the next generation of AI.

3. Humans as Tools in the AI System

With AI capable of delivering instruction, humans risk becoming the supporting cast in their own educational narratives.

Scenario:

Imagine a virtual classroom:

• A student logs in.
• The AI assesses their prior learning, emotional state, and attention span.
• It designs a personalized SPRINT (Self-paced, Problem-based, Reflective, Innovative, Navigated, Transformative) module targeting Bloom’s levels 5 (Evaluate) and 6 (Create).
• The teacher? Possibly analyzing data on the dashboard or resolving edge-case issues.

In this setup, the machine is the main teacher. The human becomes a monitor, analyst, or emotional anchor. The teacher’s role, once exalted as the cornerstone of education, becomes that of a facilitator, observer, or interpreter. Even learners may find themselves responding to AI-generated stimuli, nudged and guided by intelligent systems.

4. From Authority to Ethics and Empathy

Humans aren’t being removed—they’re being repositioned. The new-age educator must evolve into a mentor, an ethical guide, and a human interface for emotional intelligence—qualities that AI still struggles to replicate meaningfully. The teacher of tomorrow must focus on:

• Mentorship and emotional intelligence
• Ethical reasoning and guidance
• Helping students question AI outputs

Example:

An AI may suggest a solution that is technically correct but ethically questionable (e.g., a business decision that increases profit but causes layoffs). Here, a teacher’s role is crucial in fostering moral judgment.

Thus, education shifts from information delivery to wisdom cultivation. Teaching will become less about delivering knowledge and more about fostering judgment, values, and a sense of purpose.

5. The Paradox of Control

There’s a deep irony: We built AI to serve us. Now, in education, we are following its lead—responding to prompts, completing pathways it sets, and validating its suggestions.

Critical Reflection:

Who is in control now? If learners simply react to AI prompts and follow machine-suggested paths, are they still autonomous?

The paradox becomes even more profound when we consider that the AI systems directing our learning were themselves trained on human-generated knowledge. We created these systems, fed them our collective wisdom, and now find ourselves guided by the product of our own creation—a digital offspring that has synthesized human knowledge in ways we could not have manually accomplished.

6. Rethinking Educational Design

To avoid being tools, humans must reclaim agency in education.

Heutagogy as the Answer:

Heutagogy emphasizes:

• Self-determined learning
• Learner autonomy
• Exploration over instruction
  
  

AI + Heutagogy Integration Table:

Example:

A journalism student uses AI to:

• Discover misinformation trends (AI data)
• Choose a topic of public concern (learner’s choice)
• Write an article (learner’s work)
• Receive AI feedback on bias, tone, and structure (collaborative review)

If we align AI with heutagogical principles—enabling learners to define their goals, paths, and pace—we may preserve human agency in this digital renaissance.

7. The Data Exchange: Who Really Benefits?

Each time a learner interacts with AI, data is created—about attention span, question patterns, learning preferences.

Key Questions:

• Are students informed their data is being harvested?
• Who owns this data—student, institution, or platform?
• Are learners being compensated or benefitting?

This is where data ethics and educational justice must be brought into policy and practice. Are learners aware that their educational journey, their mistakes, their breakthroughs, and their questions are becoming fodder for AI optimization? Do they benefit proportionally from this data extraction?

8. Conclusion: Becoming More Human, Not Less

The reversal of roles—from AI as servant to AI as guide—doesn’t have to mean human redundancy. Instead, it demands that we become:

• More creative
• More emotionally aware
• More critically engaged

The future of education is not about humans serving AI but about using AI to become more human—compassionate, curious, wise, and self-aware.

Final Reflection:

Are we ready to co-lead this educational future? Do we have the vision and courage to build systems that amplify human potential rather than diminish it?