🪴 Scaling Synthesis

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Project Mission and Impact

Last updated April 28, 2022


Through our research, we plan to generate insights and questions that enable the creation of decentralized tools for networked thought that improve the thinking of all participants. We hope to connect the research and knowledge of academics and practitioners across disciplines and professions, fueling interdisciplinary synthesis the likes of which the world has never seen before. In doing so, we will fight against the trend of technological discourse software that overwhelms us with noise we can’t even trust and leaves us fried as we mindlessly scroll through it.

Over the last three years of my (Rob Haisfield) career in applied behavioral science, I have learned a ton. Most of this learning came from reading papers and working with clients, and it has all gone into my personal notebooks. One of the most important realizations I have had as a practitioner is that the findings from academic research don’t always map 1-1 with what works in practice. I have learned the boundary conditions of various theories and synthesized my own through attempting to apply the theory to real life, across multiple situations.

Here’s the thing: it’s not just me. Every practitioner is learning a lot through their work, connecting the dots. Many of them use a personal knowledge management system in some form or another. Practitioners don’t have a proper feedback loop to update the academic knowledge base, and barely even talk to each other. What would happen if we unleash the knowledge of individuals and groups into a decentralized knowledge graph built to facilitate synthesis? How can that technology and behavior be actualized? How can we lower the barrier to access, contribute, and arrange research? What structure can make knowledge graphs interoperable across fields of study and professions, and what will be necessarily domain-specific?

This is not a new mission. The semantic web has long eluded us, largely due to problems of human behavior. If we are to create a decentralized knowledge graph, we have to figure out a structure that doesn’t break if individual people don’t manually tag information consistently and honestly. In order for this to work, we need to figure out the right implicit metadata, and in order to do that we need to learn how people interact with knowledge graphs today. What behavioral conventions are necessary to create and maintain a decentralized knowledge graph at different scales so the edges and nodes are composable and able to propagate changes? We aim to learn what data structures and interfaces can facilitate people in this necessary knowledge work.