Making Relations Visible

Digital systems often appear frictionless because the infrastructures that sustain them remain out of view. With three proposed data centers within a ten-mile radius, residents of the El Paso region again have a front row seat for intrusive infrastructure and extractive practices. This cluster invites work that makes infrastructures visible as cultural, political, ecological, and social formations that distribute resources, opportunities, risks, and power. Whose values will become embedded in infrastructure? Whose communities bear the costs or receive its benefits? How might digital humanities help communities visualize, critique, resist, or re-imagine infrastructures rooted in social justice, sustainability, local knowledge, identity, and collective well-being?

Every expression draws boundaries. Archives decide what merits preservation. Metadata determines which characteristics matter. Algorithms classify, rank, weigh, and exclude. Maps define and scale centers and peripheries. Datasets establish categories. This cluster explores classification itself as a humanistic problem of interpretive meaning making given how digital systems define, oversimplify or challenge inherited identity, knowledge, evidence, language, history, and value. How can trans-border knowledge, forged in multilingual and multicultural contexts and rife with contested histories, help shape digital and data practices in ways that resist universalizing assumptions and essentializing practices?

Maps organize relationships, values, and ways of knowing. They are not only tools to represent space. This cluster welcomes work that explores mapping as an epistemological practice of visualizing cultural worlds that resists flattening into coordinates and challenges the assumption that Western cartography is the default language of spatial knowledge. What becomes possible when mapping moves beyond the cartographic and toward forms of representation that can hold memory, story, kinship, emotion, ceremony, movement, uncertainty, and multiple, sometimes competing, understandings of place?

The largest datasets are not always the richest ones and many of the questions most urgent to communities are locally grounded. This cluster explores what is gained by working at smaller scales. Oral histories, neighborhood archives, family collections, local newspapers, community organizations, and ephemeral records often resist the logics of aggregation because gaining scale is not worth losing contextual richness. How can small data help us reconsider what counts as data, reveal ways qualitative evidence can be represented digitally, and redesign computational methods around care, context, and accountability?

It seems artificial intelligence is on an inevitable trajectory of expansion. But instead of assuming technological progress indicates innovation, we invite contributions that ask what digital futures can we build that we would want those that follow to inherit. This cluster interrogates AI as a cultural, historical, rhetorical, and political phenomenon that reconfigures our present and has the capacity to imagine alternative futures. What kinds of intelligence, judgment, interpretation, and care should remain irreducibly human, and how might humanistic scholarship shape the futures of AI in ways that center human flourishing, plural epistemologies, public accountability, and community values?