Amelia Wattenberger wrote a guide on how you can use the JavaScript library React with D3.js. I know next to nothing about the former, but probably should, so this was useful.

For Wired, Craig Mod writes about how he uses code as a way to find order during less coherent times:

Break the problem into pieces. Put them into a to-do app (I use and love Things). This is how a creative universe is made. Each day, I’d brush aside the general collapse of society that seemed to be happening outside of the frame of my life, and dive into search work, picking off a to-do. Covid was large; my to-do list was reasonable.

The real joy of this project wasn’t just in getting the search working but the refinement, the polish, the edge bits. Getting lost for hours in a world of my own construction. Even though I couldn’t control the looming pandemic, I could control this tiny cluster of bits.

A couple of years ago, I spoke about how FlowingData is a personal journal in disguise. I find myself turning to data and charts, because those things feel familiar and can be a source of comfort.

So while reading Mod’s essay, it was easy to substitute in data and nod my head in agreement.

Vox explains efficacy rates and why the best vaccine is the one you get now:

The New York Times collected, categorized, and linked to reports of anti-Asian hate crimes over the past year. The levels of ignorance, cowardice, and stupidity is off the charts.

Pre-pandemic, we walked around shopping areas casually browsing, but a lot of retail didn’t make it through. For Quartz, Amanda Shendruk looks at the closures on famous shopping streets, complete with a location-appropriate vehicle to drive in and a police car that appears if you scroll too fast.

For The New York Times, Kashmir Hill describes the implications of facial recognition becoming a thing that everyone just has:

Retail chains that get their hands on technology like this could try to use it to more effectively blacklist shoplifters, a use Rite Aid has already piloted (but abandoned). In recent years, surveillance companies casually rolled out automated license-plate readers that track cars’ locations, which are frequently used to solve crimes; such companies could easily add face reading as a feature. The advertising industry that tracks your every movement online would be able to do so in the real world: That scene from “Minority Report” in which Tom Cruise’s character flees through a shopping mall of targeted pop-up ads — “John Anderton, you could use a Guinness right about now!” — could be our future.

No thank you.

An anonymous source supplied BuzzFeed News with usage data from Clearview AI, the facial recognition service that was banned by many police departments nationwide. Many agencies still used and/or tried it:

The data, provided by a source who declined to be named for fear of retribution, has limitations. When asked about it in March of this year, Clearview AI did not confirm or dispute its authenticity. Some 335 public entities in the dataset confirmed to BuzzFeed News that their employees had tested or worked with the software, while 210 organizations denied any use. Most entities — 1,161 — did not respond to questions about whether they had used it.

Still, the data indicates that Clearview has broadly distributed its facial recognition software to federal agencies and police departments nationwide, offering the app to thousands of police officers and government employees, who at times used it without training or oversight. Often, agencies that acknowledged their employees had used the software confirmed it happened without the knowledge of their superiors, let alone the public they serve.

BuzzFeed News also made a searchable table so you can see if your local agencies are on the list.

Dan Bouk and Danah Boyd wrote an essay on the data infrastructure and politics behind the decennial census:

Like all infrastructures, the U.S. decennial census typically lives in the obscurity afforded by technical complexity. It goes unnoticed outside of the small group of people who take pride in being called “census nerds.” It rumbles on, essentially invisible even to those who are counted. (Every 10 years, scores of people who answered the census forget they have done so and then insist that the count must have been plagued by errors since it had missed them, even though it had not.) Almost no one notices the processes that produce census data—unless something goes terribly wrong. Susan Leigh Star and Karen Ruhleder argue that this is a defining aspect of infrastructure: it “becomes visible upon breakdown.” In this paper, we unspool the stories of some technical disputes that have from time to time made visible the guts of the census infrastructure and consider some techniques that have been employed to maintain the illusion of a simple, certain count.

This process, whether we know what’s going on or not, in turn affects voices and democracy across the country. So it’s kind of important.