Projects (Spring 2026)

Origin

When I was a graduate student, I considered trying to build a platform where people could attach information to specific locations — text, images, documents, poetry — visible through augmented reality to anyone standing in that place. The idea stayed with me because it connected to work I was already doing in community arts and education in Roanoke, Virginia. I was really interested in experimental ways to teach people about where they lived and focused on constructing meaning from the city around you: through research, wandering, and paying attention to what places hold. At the time I did not have the technological skill set to build such a technology platform that could provide information about specific locations. But today, technologies exist that can simplify the process of building something that I’ve temporarily been calling the Meaning Machine. And in another piece of serendipity I am living in Tbilisi, Georgia, a city with thousands of years of rich historical meanings.

What is it

Basically, the Meaning Machine is a location-aware platform/app that generates interpretive narratives about places and allows users to contribute their own observations, memories, and reflections. When someone opens the app, the system detects their location, produces a short situational report drawing on historical and geographic data, and invites them to add their own voice. Those contributions are stored and become visible to future visitors at the same location. One way to understand the Meaning Machine is by contrasting it with the kinds of platforms people already use to navigate cities. Applications such as Google Maps aggregate functional information: business locations, hours of operation, ratings, routes, and real-time traffic. They help people move efficiently through space. The Meaning Machine aggregates something different: the meanings that can be found in locations. It gathers historical context, hidden layers, personal memory, and interpretive reflection attached to specific places. Ending up in Tbilisi, Georgia has been a great opportunity to explore this project because the city is loaded with history, architecture and changing meanings. A Google Maps pin on a street in Tbilisi might tell you that a restaurant closes at 10 p.m. The Meaning Machine might tell you that the same street once housed a clandestine printing press used by revolutionaries in the early twentieth century. Both pieces of information are useful, but they serve different purposes. The difference also appears in the kinds of contributions the platforms invite. Google reviews are largely transactional: Was the food good? Was the service slow? The Meaning Machine encourages a different type of participation. Users are invited to contribute observations, feelings, memories, interpretations, and fragments of local knowledge. Instead of accumulating ratings, the system accumulates narratives. Over time, ideally, this creates a fundamentally different kind of archive. Conventional mapping platforms collect evaluative data about businesses and infrastructure. The Meaning Machine collects qualitative traces of human experience. The current prototype generates a structured report with five layers: Place — the immediate physical environment History — documented historical context Hidden — overlooked structures, patterns, or forgotten stories Reflection — a narrative perspective on the location AI Synthesis — a reflection connecting the layers Users can then add their own notes, building a shared record of human experience attached to that coordinate.

Technologies Involved and The Role of AI

I developed a prototype using: Next.js, Vercel, Open Street Map, Wikipedia, OpenAI and Supabase. AI in the Meaning Machine functions as a co-interpreter of the explored spaces— connecting historical context to present environments, and synthesizing contributions as they accumulate. The goal of course is not to replace human insight but to help users notice patterns and meanings that might otherwise stay invisible.

Educational Applications

The platform has natural applications as a learning tool. Students can use it for urban fieldwork, local history documentation, environmental observation, and collaborative knowledge-building beyond the classroom. Rather than treating learning as something confined to an institution, the Meaning Machine invites students into the environments around them and asks them to take those environments seriously. Possible uses include urban studies fieldwork, digital humanities projects, community history documentation, and reflective writing assignments grounded in place.

Connection to Previous Work

Through my arts and community efforts in Virginia I explored how storytelling, and community engagement could be found in everyday spaces — through installations, historical traces, and public participation. Those projects were mostly temporary. The Meaning Machine creates a permanent digital infrastructure for a similar goal: a participatory archive that grows rather than disappears. Tbilisi is an extraordinarily layered city — within a few blocks you might find a sixth-century basilica, Soviet modernist architecture, the site of a 1907 bank robbery organized by Stalin, and a secret printing press in the Isani neighborhood. The Meaning Machine is, in part, an attempt to make that kind of layering visible and shareable anywhere in the world.

Long-Term Vision and Why it Matters

It would be interesting to test its instructional capabilities. Or, at scale, the platform could become a global map of collective memory — a digital humanities archive of place-based stories, an educational tool connecting students with local environments, and a community storytelling infrastructure for cities and neighborhoods. It could also generate a unique dataset of geography, culture, and meaning: evidence of how people actually experience the places they inhabit. Most digital tools treat the world as infrastructure — something to move through efficiently. The Meaning Machine treats it as something to read and possibly find meaning in. Every city contains layers that most people never see: decisions made by people long ago, systems that shaped streets and buildings, experiences that left no official record. The Meaning Machine is an attempt to make some of those layers visible again through the accumulated observations of people standing in specific places, and paying attention. It is, at its simplest, a tool for noticing. Whether it develops into an educational platform, a digital humanities archive, or something else entirely, the underlying question stays the same: what would it mean to move through a city and actually understand where you are? A I stay in Tbilisi, I will continue to notice these layers and continue to build in this idea.