How GenAI is reshaping learning approaches

Automation presents opportunity but risks learning loss. Can students ace this race?

The popular movie franchise Mad Max has a post-apocalyptic, dystopian setting and is themed around human survival against odds. It’s a mirror to societal collapse due to war and human desire to possess wealth. Those who succeed in this possession will control the rest of the world and those who are not part of the troupe will have to exhibit their exceptional survival skills. In contemporary times, our constant interaction with Generative Artificial Intelligence throws at us an important question: Are we turning into the survivors of the wasteland portrayed in the Mad Max films?

Every user in the realm of AI is a Max because we are constantly swimming in the whirlpool of information. As a race, our constant need to compete with each other is fixated as it is the fittest who survives. From children to adults, from students to academics, from corporate workers to industry peers, we have all become a part of this degenerative, transformational race to conquer AI.

Understanding whether AI platforms are fighting with each other or with the human kind is a puzzle. Nevertheless, what is evident is the shift within technological infrastructure and the traditional workflow mediated by internet networks.

The latest development in the GenAI world serves as a testimony to this argument. While ChatGPT was challenged by DeepSeek, Qwen 2.5 Max is a wild entry disrupting other GenAI tools in use. DeepSeek’s newer versions R1 and V3 lead us to unknown terrains.

The battle among these tech giants has been impacting the seriousness of the learning community. As the upgrades in automation bring a radical change, academics that were built through hard labour and time over centuries with meticulous scheduling are now lagging behind.

Peer pressure has been forcing students to disregard traditional learning approaches. The crossover between disciplines is becoming increasingly common.

We notice a steady increase in science students in humanities classes, some of them coming even from undergraduate engineering courses. As a result, there is an increasing demand for upskilling courses. Academics are compelled to include essential components of AI because the students are keen on learning – and are demanding – these sets of highly endorsed AI tools.

Students want to harness the most advanced skills that are relevant to the sectors they aspire to engage in. A couple of productive internships might help them enhance their employability but what, really, are their takeaways from these stints? – Do they learn something under the mentorship of seniors or do they merely help a startup increase its profits? In a race to enrich their profiles in the runup to their aspirational jobs, these students are losing the ability to relate to their peers and, probably, losing the opportunity to live as students, enjoying the privilege of being what they are.

Consent and regulation

For the students, escaping the pressure to embrace technology – as a tool to upgrade their employability – is becoming an increasingly tough ask. A recent case filed by a student against a university for failing him on the grounds that he submitted AI-generated assignments drives home this point. It is, again, time to address the all-important question: What role should our educational systems be playing? Should they be designed to bring about a change in society or is theirs a more functional responsibility that involves barely fulfilling the needs of a knowledge-based society?

The application of AI content in academics comes with its limitations just like it has its advantages. Some of the business giants are also predicting an AI deflation. Future roads that connect the digital world will be powered by AI which is embedded with constantly evolving learning algorithms. For every offline traffic system in the real world, we have traffic control points in the form of traffic lights that determine the pace, flow, and control of vehicles on the move. It is important to note that in the digital world, regulations are not being conceived with such intent or being implemented with the required alacrity.

India has been engaging with frameworks such as the Digital Data Protection Rules 2025. The government has pitched a model that seeks to balance innovation with regulation to protect personal data. In an emerging scenario where AI and processes involving consent are becoming central to the implementation of rules, policymakers will need to adopt a nuanced approach to regulation.

There is a huge opportunity and a learning loss taking place together. In the race to ensure new skills that are perceived as critical to employability, we could be undermining the very foundations and graduate attributes an educational institute wants among its students. There is a distinct possibility of every student becoming capable of learning any required skill while disregarding formal training. This presents an alarming situation to the academic community. The gap between the teacher and the student community is widening – concerted efforts to seek a middle ground need to be initiated. All forms of learning mediated by technology need to find boundaries through policies while the student-teacher exchanges demand a vibrant bonding as we seek a collaborative learning environment.

(The writers are faculty members in the Department of Media Studies, CHRIST Deemed to be University)