DownSide Up

Civil society organisations working on systemic change face a structural problem: industry invests heavily in coordination infrastructure incl. trade associations with shared intelligence systems, legislative tracking, rapid response capacity, and the ability to deploy knowledge at scale across actors and policy windows. Progressive movements, by contrast, tend to fund campaigns. The result is a compounding asymmetry in which well-resourced incumbents out-manoeuvre well-intentioned advocates, not because the arguments are weak, but because the infrastructure underneath them is insufficient. We believe the future of advocacy will require progressive movements to address this deficit to overcome incumbent power dynamics, and we believe AI can help us get there.

DownSide Up is an experiment in building a more efficient and collaborative approach to advocacy, leveraging e.g., RAG and knowledge graph infrastructure to better connect information and people working on similar topics in advocacy. For example: could a commons-based knowledge platform aggregate the practitioner intelligence currently trapped in individual organisations' email threads, reports, and institutional memory, and make it queryable across a movement? Could it do this in a way that respected the genuine privacy concerns of civil society actors working in adversarial environments, where sharing sensitive strategic knowledge carries real risk? Could the platform be governed democratically, so that the infrastructure itself did not reproduce the power asymmetries it was designed to address?

The starting point is building a prototype that we can deploy for organisations working on alternative protein advocacy specifically. We're exploring product-market fit, and the best pitch/positioning to help secure funding.