Keeping value where it's made.

Artisanal labor — employee-owned crafting, braiding, repair, urban farming — has high job satisfaction, higher-quality products, and sustainable practices, and it's one of the most race- and gender-diverse business sectors in the U.S. It is also, often, a low-income profession. Meanwhile the economics of automation run the wrong way: the last 30 years show stronger labor displacement and weaker reinstatement than the decades before.

Debias the model and you only change which faces the harm lands on — the extraction underneath keeps running. The lab's question was whether AI could be built to work differently that far down.

The lab's framework, generative justice, names a different success metric: "the universal right to generate unalienated value and directly participate in its benefits; the rights of value generators to create their own conditions of production; and the rights of communities of value generation to nurture self-sustaining paths for its circulation." The design question follows: what does AI look like when it's built to circulate value back to its source?

Needs-based participatory design starts by cataloguing what a community lacks. Assets-based design starts from what it already has. Either way, the power structure around it can come out untouched. We developed Generative Participatory Design (GPD) — a four-phase method: start with what the community values, map where value is being taken from them, then co-design responses together.

We also widened who counts as an artisan: any work with creative autonomy, motivated by quality, with some economic independence. That definition deliberately includes Black beauty shops, braidologists, auto detailers, neighborhood repair shops, and urban growers — sectors with deep counter-hegemonic histories that "maker culture" routinely overlooks.

The Artisanal Futures workshop ran over two consecutive days — ten hours — in June 2022, in a university facility we converted into a pop-up makerspace stocked with digital design, digital fabrication, and sensor technologies. Twenty Detroit artisan entrepreneurs joined as co-designers: a fashion designer, a sewist, a felt artist, a boutique owner, a visual storyteller, a master gardener, a landscaper, a farmer, two arts-education directors, and the co-founders of a new community gardening project.

Each participant was first interviewed (semi-structured, recorded and transcribed, then coded for beliefs, values, and goals). Bringing artisans from different worksites into one shared space was a deliberate move — when participants hear each other exchange work experiences, the workshop becomes what the PD literature calls an "occasion for enfranchisement."

The literature describes artisan entrepreneurs through an oppositional identity — defined as much by who they are not as who they are. Our participants confirmed all four dimensions, and they became design requirements:

The threat model came into focus too: industrial appropriation by marketing (the world's three largest snack companies all sell "artisan" branded products) and by the gig economy's algorithmic extraction — platforms that advertise independence while taking most of the earnings. A key fieldwork lesson: empowerment is often non-digital first. Before laser cutters, our makers needed felt-pressing machines, heat sealers, and solar photovoltaics for the urban farms' sensors.

The lab's lineage runs through Culturally Situated Design Tools (csdt.org) — Eglash's NSF-funded suite where students discover the "heritage algorithms" inside cultural practices: the transformational geometry of cornrow braiding, the stamped symmetries of tooled leather, the iterative logic of quilting and beadwork. These practices already contain the computation; the tools make it visible.

The recreations below are working miniatures of three CSDT tools. Every pattern is generated by rules you can read, adjust, learn, and teach.

The theory side published as "Counter-hegemonic AI: the role of artisanal identity in the design of automation for a liberated economy" (in AI and the Future of Creative Work, Routledge, 2023). The empirical side — workshop themes on artisans' perceptions of success and their relationships with technology — produced design principles now guiding the lab's Artisanal Futures platform development.

Twenty artisans spent two days teaching us what they wanted from technology, and almost none of it was a screen. What they kept returning to was ownership — of the platform, and of where the tools got pointed. The interface mattered, but only after that.