The mugshot was invented in the 1880s. A century later, face surveillance has gone digital but remains as flawed as ever.
“This is not lowered expectations. It’s a wish for a mass normalization of resistance to deadly ways of looking at the world.”
"The ways in which the community itself is breaking down felt like end game capitalism."
How might we learn resilience, care and community in the face of crisis–climate, political, cultural, economic or otherwise?
Digital tech cannot stop climate change merely by “greening” individual consumption.
Landlords’, bosses’ and schools’ intrusion of surveillance technologies into the home extends the carceral state into domestic space.
Today is overwhelmingly defined by white-supremacist violence and the whiteness of AI technology. Can seeing them together help defeat them both?
“I am supposed to be writing this essay, ostensibly on technology, but not for the first time, I believe I am unable to write; and not writing, doubt that I will I ever write again.”
Machines learned racism from humans. Perhaps humans can now learn about that racism from the very machines they taught.
Climate change didn’t just wreck the planet; it closed off and reshaped the future. Even utopia—if we reach it—will be a mess.
“We can’t always explain how algorithms reach their decisions. The reasoning of algorithms, like the will of God, is unfathomable.”
How have data-centric systems perpetuated racial capitalism, and how have different communities, particularly in the global South, resisted this datafication?
Whose values get embedded into the algorithms that increasingly govern our lives? How are these data infrastructures complicating what it means to be human?
Tech promises to cure any ailment, whether an unwelcome feeling or a global pandemic. But what if tech itself is ill? And what is a cure, anyway?
What harms can result from AI and automation, and how might we address and prevent those harms?
Nobody knows what will be useful in the future. And this is why we so often find humanistic activities in the seeds and roots of STEM.
How has data been used to organize labor, and how do we make ourselves visible to data-centric systems?
How do people show up in data, and what are some of the inequalities that can result from data collection?
How long has human life been quantified as data, and in what contexts? What are some major implications of humanity being measured as data?
In the digital world, metrics mean everything. But who interprets just what they mean changes across organizations, countries, and cultures.