Links, November 22, 2024
Fedi Moderation Tooling Research
Over the past few months I’ve been contributing to Letterbok by putting on my UX Interviewing hat and talking to a variety of people doing moderation work in the fediverse space, as a part of figuring out what good moderation tooling interface design for the space would look like.
We learned a lot about problems and obstacles to this kind of work. I summarized that, and offer some recommendations for people interested in the topic could contribute towards moving things forward.
Against the Dark Forest
More from Erin Kissane about creating safe spaces.
I think our failure to remember that the mega-platforms are just intentionally extractive constructs run by brainmelted but very human weirdos is a failure of accountability, but our failure to remember that it doesn’t have to be this way is a failure not only of imagination, but of nerve.
Expert agencies and elected legistlatures
A regulation that works might well produce no visible sign that it’s working. If your water purification system works, everything is fine. It’s only when you get rid of the sanitation system that you discover why it was there in the first place, a realization that might well arrive as you expire in a slick of watery stool with a rectum so prolapsed the survivors can use it as a handle when they drag your corpse to the mass burial pits.
More Doctorow, sorry. I feel fortunate to have a partner who developed a special interest around what are the things that will help us be self-sufficient when the system breaks down.
Surveillance Self-Defense
The Electronic Frontier Foundation collected a bunch of guides for keeping your computing environments and practices more secure.
The Invisible Man
I sleep at Walmart that night, but the police will continue to come as if I’m some kind of one-man crime wave.
A brutal story of a former reporter’s experience with homelessness.
Don’t call it a Substack.
Email’s been here for years. But the reason Substack wants you to call your creative work by their brand name is because they control your audience and distribution, and they want to own your content and voice, too. You may not think you care about that today, but you will when you see what they want to do with it.
On Being an Outlier
When we ask a statistical aggregate to infer probabilities of human action, human worth, and human life, that model will harm the most vulnerable every time. These are the people whom, when considered as data points, represent outliers — unexpected, inconvenient, or otherwise neglected exceptions or eccentricities to the neat rule of parametric normality. You see, to receive the promise of these systems, you must agree to the terms:
- These systems are built on data that includes historic and contemporary legacies of systemic racism, ableism, and gendered violence.
- These systems are built to solve problems or offer answers to questions that reflect an ongoing cultural ignorance about the nature of those problems or the motivations behind those questions.
After flunking Calculus my first year in college and (for a variety of other reasons as well) subsequently giving up on my childhood dreams of a career in Architecture, I still had to take a math class to satisfy degree requirements. For some reason I can’t remember now, I chose statistics, and despite not having a calculator with statistical functions, I got the higest grade in the class.
The professor tried really hard to get me to change majors, citing my “natural talent” and “outlier performance”. I told her I’d think about it if she could satisfactorally answer me this: If, as you’ve said repeatedly, we are supposed to ignore the outliers for looking at a population, why should an outlier care about the population? About the person asking the question? She couldn’t.
A large part of my work over the last decade has involved helping people make meaning from statistics, and the sentiment behind that question has stuck with me.
Like all human intellectual and cultural pursuits, AI can neither be apolitical nor ahistorical. We must account for our eugenicist past and present when designing and deploying AI in medicine, justice, finance, and all sociopolitical domains.
Dreaming Awake
To engineer is to design or construct something. To engineer consent is to both subvert the agency necessary for consent to exist and to make plain that the person being engineered is seen as a device or a product, a thing to be manipulated or arranged.
If you don’t yet subscribe to Mandy’s blog, you should.
Foursquare Open Source Places: A new foundational dataset for the geospatial community
we are announcing today the general availability of a foundational open data set, Foursquare Open Source Places (“FSQ OS Places”). This base layer of 100mm+ global places of interest (“POI”) includes 22 core attributes (see schema here) that will be updated monthly and available for commercial use under the Apache 2.0 license framework.