NOTES ON AI

Data experience design

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.

For my piece, I have situated myself between three spheres of overlapping labor, which I name loosely as engineering, analytics, and data experience design. 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, and/or with adequate information that is poorly interpretted. 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. In the AI parlance, I’m concerned with human in the loop systems, but I have a particular slant on how humans might best participate in the loop.

To kick things, off I thought it best to start with a collection of images demonstrating how humans have externalized their representations of complex systems, and to begin to trace the intuitions these systems have given rise to.