Our machines are disturbingly lively, and we ourselves frighteningly inert”
Harraway (1985)
Trying to start a project on what is not or what could be, or how things could be otherwise is slippery, messy but exciting. I find myself becoming continually stuck and unstuck between networking, reading, writing, desk work, connecting and scribbling out on colourful sheets of paper strewn across my desk. Not inert but ebbing and flowing through gasps of solidity and moments of conceptual panic. Through constant introductions and reintroductions to new colleagues cementing but at the same time reorienting myself—scholar, artist, engineer, ethnographer, other. Deliberate unbounding, from texts, contexts, technologies, motivations, formations and resifting through to be grounded. We start low, close, proximal and cautious.
values?
Nissenbaum (2001) writing in Computer direct to engineers implores them to be reflective (reflexive a step too far?) by posing a series of questions quoted below. Reflection asks us to pause, but also to question ourselves, others, the apparent benign, unquestionably objective. And we can ask and do nothing or be told to do nothing still. Does reflection act as a bounds to the great riches that technocapitalism promises? Where speed, automation, productivity and economics are prioritised over bodies, trust, equity, sustainability and fairness.
What values do they embody?
Is their locus of control centralized or decentralized?
Are their workings transparent or opaque?
Do they support balanced terms of information exchange?
Do they unfairly discriminate against specific sectors of potential users?
Do they enhance or diminish the possibility of trust?
Nissenbaum 2001
Yet here we are in 2022 already rebooting social media. Maybe this is why we need a slow tech, technology that reckons with values, entertains them, reflects on them towards shifting computational possibility.
still unbound
What does a slow, low or no tech even really look like? Is it political, creative, playful, exploratory, discursive, social, activist, archival, ontological and/or epistemic. What could it mean outside of contexts where its values cannot be valued?
How do we make it materially? Is it local, global, networked, physical, interface, sensory, datalogical, algorithmic, automated, representation, infrastructure, being, expression, material, open, articulated through time and space, ambient, dialogical?
reparation?
Can a social media itself be reparative? Davis, Williams and Yang (2021) outline algorithmic reparation within ML systems. Attending to harms intersections, institutional and beyond imagining.
Fair machine learning seeks to de-bias algorithms and make them fairer. In contrast, a reparative approach assumes and leverages bias to make algorithms more equitable and just.”
Davis, Williams and Yang (2021)
Could rebooting social media bring with it reparation—how would that texture infrastructure, interface, application and possibility?
To be further thought through next week.