Arita ware is porcelain made in Arita, Saga Prefecture, and surrounding areas.
Production is generally divided among specialists. How can the knowledge and judgment involved in each stage be preserved and passed on to the next generation? One possible approach is to use AI to support documentation, including transcribing audio. This article explores the potential of treating AI not as a substitute for craftspeople, but as an assistant in documenting their work.
Arita Ware Is Made Through Collaboration, Not by One Person Alone
An Arita ware vessel is not made by a single craftsperson from start to finish. Production is generally divided by stage, with specialists bringing their trained eyes and hands to tasks such as forming, painting and firing. Several people’s judgments come together before a single vessel is complete.
Care is also needed when citing dates in accounts of the region’s history. The founding of Arita porcelain is sometimes given as “1616,” but the Arita Town Historical and Folk Museum explains that this date comes from a document recording the migration of Kanagae Sanbei. It is best to be cautious about directly linking the year to the founding of porcelain production and to refer more broadly to the “1610s.”
It is precisely because this production center has a history of more than 400 years that the question of how its techniques have been passed down carries such weight. How should AI be involved? In the following sections, we will consider the possibilities while distinguishing facts from proposals.
How to Document the Skills Behind Divided Labor
When production is divided into stages, the passing on of techniques must also be considered one stage at a time. The points that those who form the pieces look for are presumably different from those that painters focus on. If everything is lumped together and simply called “technique,” the crucial details of the judgments involved can be lost.
The starting point is simple: document in words what craftspeople look at, when they pause their work, and why they make a particular choice. Videos can show the steps of a task, but the reasoning behind a decision remains invisible unless someone explains it.
One point should be emphasized: everything that follows is a proposal. These are not examples of systems implemented at any particular pottery workshop, but hypothetical scenarios for considering how knowledge from the region could be preserved.
Audio Transcription Can Be a Starting Point for Documentation
A practical starting point for documentation is to transcribe recorded interviews. OpenAI’s API documentation still lists Whisper as an option for audio transcription. Transcribing conversations held during breaks in the workday or interviews with veteran craftspeople can make them searchable and available for later review.
For example, imagine a young craftsperson at a workshop asking a senior colleague, “Why did today’s firing turn out this way?” and recording and transcribing their exchange. Over several years, the workshop’s accumulated experience could take shape as a body of writing. Information once kept in paper notebooks or in people’s memories could potentially become an asset that can be shared.
However, transcription alone cannot reproduce a craftsperson’s senses. Subtle differences in heat or the feel of a piece in the hand are partly lost the moment they are put into words. Text is not the craft itself, but a map for finding one’s way to it. AI remains a tool that can help create that map.
Deciding What to Entrust to AI
Supporting documentation and reproducing the craft itself are entirely different challenges. The former is close to what AI does well; the latter belongs to the realm of experience accumulated by people. If the distinction is blurred as AI is introduced, those working on the ground will not be persuaded.
Ideas might include using image-generating AI to develop new vessel designs or AI agents to support sales overseas. But these are hypothetical examples, not established practices in Arita ware production. Even when testing such ideas, the sensible first step is for craftspeople to decide what they want to preserve and what they want to keep in human hands.
The value of using AI lies not in adoption for its own sake, but in deciding who can use the knowledge of those working on the ground and how it should be preserved. Arita ware craftsmanship is the main focus, with AI in a supporting role. It seems fitting for a production center shaped by specialized collaboration to bring AI into the process as one role among many.
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