What signals should we attend to when studying a system? If we capture everything, how will we filter out the noise to listen to what matters? How do we know what matters? Does that change over time? How will we engage with what matters? Will it be on single metric? A two-dimensional chart? A 3D display? A 3D display that moves with color and sound adding further dimensional context?
These are the questions I think throughout my days with, until now, little context for exploring their histories and futures in the broader scope of analytics, interaction design, human computer interaction, and feminist computing. And yet, I became a data engineer precisely to explore such questions. For me, the big data revolution extends far beyond how Fortune 500 companies can track consumer behavior to create “stickier” products. No shade, but I believe humans are capable of exploring more humanity along the axes of care, trust, collaboration, healing, joy, service, and contentement than along the axis of consumption. I’ll leave politics out of the equation, and present more of my thesis.
In this context, I am situating myself between three spheres of overlapping labor: engineering, practices of meaning making, and human computer interaction. I engage in this labor in service of the questions above, and in response to the imperitive that compels them - people make important decisions that impact myriad beings without adequate information. We have yet to see the extant we can make rational, loving, compassionate, and deeply caring decisions as individuals and as people. We have been context-impoverished not only because of limited access to data, but also limited shared imagination regarind the potentials of thining with our systems. A dangerous sort of hubris, or over-prioritzation of our human minds divorced of context-rich, responsive systems.
Rather than bemoan human ignorance, and throw my hands up to the sky, I’m putting my hands (and entire mind-body) to work on developing new possiblities for leveraging the kinetic-perceptive-cognitive abilities that are core to our species in novel ways to draw more meaning from the data we generate and engage with. I’m interested human in the loop systems, including human in the loop in bio-ecosystems, cyber-ecosystems, and meaning-making systems. I’m also interested in empathic AI that will enhance our ability to relate compassionately to ourselves and others, as sound decision making is predicated on the kinds of values and ethics that a healthy, balanced, awake human can engage in.
I’ve enjoyed my weekend visits to Dynamicland, and it may be helpful to start this research thesis with a collection of images demonstrating how humans have representated their location within complex systems. Perhaps from there we can trace scaffolding we’ve collectively been working with, which may spark fresh thinking on what else might be possible.