Sasha’s Project Journal (2/25/2026)

Revising the project proposal turned out to be more clarifying than I expected. What started as an exercise in tightening our language became a real opportunity to interrogate the “what” and “why” behind what we’re actually building. The revision also gave us a chance to solidify something we’d been leaning toward: expanding beyond the original Black Knowledge Erasure Dataset (BKED) to include a parallel dataset on Puerto Rican history. We deliberately narrowed it there. Latin American history is a whole can of worms on its own, and questions like what even counts as ‘Latin American’ could swallow the project whole if we let them. Puerto Rican history gives us a focused, specific entry point without opening up more scope than one semester can reasonably hold. Putting it into the formal proposal made the reasoning click into place. Comparing how epistemic erasure operates across different diasporas gets us much closer to saying something meaningful about the pattern, rather than just documenting isolated incidents. It also raises another question: does erasure look the same across different communities, or does it take distinct forms depending on how a group has been historically represented (or misrepresented) in the sources these models were trained on?

Furthermore, working through this revised proposal with the team has been really eye-opening, because having three people invested in the same problem brings out angles I wouldn’t have caught on my own. The research lead is keeping our sourcing rigorous and our historical grounding solid. The design and UX ideas are already pushing us past the “spreadsheet” version of this project toward something that could function as a real public-facing archive. And the outreach and documentation brainstorming is something I think often gets underestimated: making our work legible to people outside the digital humanities world. If we want this to land as an Open Educational Resource, that translation will matter enormously. I’m feeling excited about the direction we’re heading and feel genuinely more confident about our momentum now. And it’s great that everyone is running with their piece of this and running with it well.

Side note – a conversation I had outside of class this week has been sitting with me in a way that keeps complicating things, in the best way. I’ve been thinking about the tension at the core of this project: we’re using archival sources as a “gold standard” to fact-check AI, but history itself has never been a neutral body of objective facts. Who tells a story, from where, and with what stakes all shape what gets recorded and what gets left out. That’s pushed me to think more carefully about the difference between asking who the AI fabricates versus why it fabricates the way it does. The “who” gives us our dataset. The “why” is where the deeper argument lives. We’re not here to ding AI for getting things wrong. We’re here to document how these systems imagine race, gender, and sexuality through an unexamined kind of creative writing, and to make that visible in a way that’s genuinely useful.