From Kathmandu to Kremsegg: a philosopher's year in Buddhist thought and AI

This year took Tina Röck, Senior Lecturer in Philosophy at Dundee, from a monastery outside Kathmandu to a castle in Upper Austria, following a single thread: what classical Buddhist thought has to say about mind, knowledge, and the questions now being raised by AI.

The trip began at Tergar Osel ling (Tergar Institute) in Nepal, where Tina Röck studied pramāṇa – the Buddhist tradition of epistemology founded by the logicians Dignāga and Dharmakīrti, which asks what counts as a valid means of knowledge and why. The tradition's rigorous, centuries-old debates about perception, inference, and the nature of mind are increasingly being read alongside contemporary questions about machine cognition.

In July, she took part in the opening of a new centre for Buddhist studies at Schloss Kremsegg in Upper Austria, established by the Gomde Foundation for Tibetan Buddhist Studies as, in the foundation's words, "a home for wisdom in action". A place where education, culture, and dialogue meet the challenges of the present.

That interest in AI was already on display: just before the opening Gomde Austria was hosting Dharma Sun's "Buddhism and AI Collaborative Summit," a four-day online and in-person seminar running from 9 July to 12 July featuring the scholar John Dunne alongside Khenpo Pema Namgyal and an international line-up of contemplatives and technologists, addressing consciousness, ethics, and agency in the age of artificial intelligence.

The trip grew out of Tina Röck’s existing work in process philosophy and phenomenology, fields that share more with Tibetan Buddhist thought than is often recognised: a common suspicion of the substance-based, thing-first metaphysics inherited from Aristotle, and a shared insistence that what is real is relational, processual, and dependently arisen rather than fixed and self-standing. Putting Whitehead, Heidegger, or Merleau-Ponty in dialogue with Dharmakīrti's on the momentariness of the real, his reading of pramāṇa, or the Madhyamaka account of emptiness and dependent origination, is thus not as as far-fetched as it might initially seem.

This lens matters for how we think about AI. The temptation is to treat a large language model as an intelligent entity, or as a thing that produces intelligent outputs – as a bounded object to be evaluated on its own. Tina Röck's emerging view, sharpened by this summer's conversations, is closer to a processual or Buddhist picture: intelligence here emerges interdependently rather than being located in any single node. A model's "intelligence" is inseparable from the corpus of human thought and language it was shaped by, from the humans who train, prompt, interpret, and act on its outputs, and from the physical infrastructure – energy, hardware, environment – that sustains it moment to moment. On this view, human and machine do not simply use one another; they co-create intelligence together, in a way that is as embodied and embedded as it is computational. The question this raises is not merely what AI can do for us, or what we can accomplish using it, but what these collaborations make of us.