An AI-Ready Knowledge Framework

Sanzhi: An AI-Ready Knowledge Framework

Recently, I have come to realize that what I am doing is more than simply collecting local historical materials. By putting into writing every memory, observation, and piece of knowledge I can recall, I am not merely documenting the past. In many ways, it feels as though I am preparing for a future in which AI will conduct oral history interviews with me.

In the past, I often wondered whether someone would continue my work. Now, however, I am beginning to see that the real issue may not be finding a successor, but ensuring that knowledge itself can be passed on.

In an era of rapid AI development, what truly matters may not be how much information we leave behind, but how we build a system of local knowledge that AI can understand, interpret, and utilize.

For this reason, I have started to record as much as possible of my fieldwork experiences, methods of judgment, and local memories. These writings are more than personal notes; they are the foundations of a future knowledge base.

My hope is that even those who have never walked these mountain trails or spoken with the elders of these communities will still be able to understand what happened on this land through the combination of my blog and AI. Perhaps one day, blogs and AI will become new transmitters of knowledge, and every record I leave behind today will serve as an important clue for understanding the local world.

What will ultimately remain is not merely the stories themselves, but a method for understanding place.

From the perspective of Local Studies, this represents a fundamental shift in thinking. The goal is no longer simply to be a guardian of local memory. Instead, it is to transform fieldwork experience into a local knowledge system that future AI can inherit and continue to develop.

In other words, what is left behind is not only the stories of Sanzhi, Shimen, or Taiwan's North Coast. It is a living system of local intelligence, one that can continue to grow, continue to answer questions, and continue to generate new understanding long into the future. Such a system may carry far greater long-term significance than merely finding a single human successor.