Why Advaita Vedanta should shape the next generation of AI
As Western models inherit Western philosophy, India has a chance to bring its own intellectual heritage into the global AI conversation.
If AI is going to influence how we think, shouldn’t we influence how AI thinks?
Artificial Intelligence is no longer just a technological breakthrough. It is becoming a cultural force — one that shapes how we learn, work, communicate, and even make moral decisions. As AI systems grow more capable, the question is shifting from “How do we build smarter models?” to “What values and worldviews should guide these models?”
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A recent article from the MIT Initiative on the Digital Economy makes a striking observation: philosophy may be the next major frontier in LLM training. If AI systems are going to reason, interpret, and guide human behaviour, then the philosophical frameworks behind them matter as much as the data and algorithms.
Today, most large language models (LLMs) are trained on datasets dominated by Western texts, Western ethics, and Western logic. This means they inherit Western philosophical assumptions by default. That is not a criticism — it is simply a reflection of how the internet and academic publishing have evolved.
But it raises an important question for India and other Eastern societies:
If AI is going to shape our future, shouldn’t our own philosophical traditions also shape AI?
This is where Advaita Vedanta, one of India’s most influential schools of thought, offers a fresh and meaningful direction.
Why Philosophy Matters for AI
The MIT article highlights three philosophical dimensions that are becoming central to AI development:
- Teleology — What should the model aim to do?
- Epistemology — How does the model “know” what it knows?
- Ontology — How does the model understand reality?
These questions are not abstract. Every AI system answers them implicitly through its training data and alignment strategies.
For example:
- When an AI decides what is “helpful,” it is making a value judgment.
- When it decides what counts as “truth,” it is applying an epistemology.
- When it interprets human intentions, it is using an ontology.
Right now, these decisions are shaped mostly by Western philosophical traditions — from Socrates to Kant to John Rawls. These traditions emphasise individual rights, rational debate, and rule-based ethics.
There is nothing wrong with that. But it is incomplete.
The Western Leaning: A Mimansa-Like Approach
Interestingly, the way LLMs are trained today resembles the Mimansa school of Indian philosophy — even though Western developers may not realise it.
Mimansa focuses on:
- rules
- correct interpretation
- action-oriented reasoning
- structured logic
This is very similar to how AI models are optimised:
- follow rules
- avoid errors
- maximize reward
- interpret instructions precisely
This approach works well for engineering tasks. But as AI becomes more integrated into society, we need more than rule-based reasoning. We need models that understand context, relationships, and the deeper meaning behind human behaviour.
This is where Advaita Vedanta offers something unique.
Advaita Vedanta: A Different Way of Understanding Intelligence
Advaita Vedanta is one of India’s most profound philosophical systems. At its core, it teaches non-dualism — the idea that all existence is interconnected, and that separation is an illusion.
While this may sound spiritual, it has surprisingly practical implications for AI.
A Holistic View of Knowledge
Advaita does not treat knowledge as isolated pieces of information. Instead, it sees knowledge as interconnected and contextual.
This is exactly the challenge LLMs face today. They are excellent at processing individual tokens of text, but they struggle with:
- long-term coherence
- multi-step reasoning
- integrating different types of information
A Vedantic approach encourages models to see relationships rather than fragments — a shift that could significantly improve reasoning.
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