The Bureau of Labor Statistics revised job counts down by almost a million:

The preliminary estimate of the Current Employment Statistics (CES) national benchmark revision to total nonfarm employment for March 2025 is -911,000 (-0.6 percent), the U.S. Bureau of Labor Statistics reported today. The annual benchmark revisions over the last 10 years have an absolute average of 0.2 percent of total nonfarm employment. In accordance with usual practice, the final benchmark revision will be issued in February 2026 with the publication of the January 2026 Employment Situation news release.

Each year, CES employment estimates are benchmarked to comprehensive counts of employment from the Quarterly Census of Employment and Wages (QCEW). These counts are derived primarily from state unemployment insurance (UI) tax records that nearly all employers are required to file with state workforce agencies.

I am sure all interested parties will consider uncertainty through estimation, as is common in statistics that require timeliness and accuracy.

For NYT’s the Upshot, Aatish Bhatia, Francesca Paris, and Rumsey Taylor show how zodiac signs were determined by the position of constellations relative to Earth and the Sun thousands of years ago. That probably seemed like a good idea at the time, but more accurate measurements and records show that if we continued to go by the relative positions, our zodiac signs would be different.

The interactive elements and animations illustrate the shifts well. Enter your birth date to see how your sign would change, and a night sky moves to show how our perspective changes because of Earth’s wobble.

NPR enlisted the band Bettis And 3rd Degree to sonify rising temperatures in New Orleans. As the temperature rises from 1980 to present, listen as the music tempo speeds up.

Between 1980 and 2000, the average annual temperature in New Orleans goes up by more than a quarter of a degree, and it may not seem like much if you’re just looking at the data in a spreadsheet, but it is significant.

And between 2000 and 2015, it jumps up again, almost a full degree warmer than the first 75 years of data. This is where things really start to pick up.

Over the last decade, the temperature increase has accelerated even more, almost two degrees Fahrenheit more than the 1980s. And many climate scientists say temperatures are increasing faster.

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The Bureau of Labor Statistics released monthly jobs data, but after the firing last month, some might be wondering how much we can trust future BLS data. For the New York Times, Ben Casselman asked economists how they’re feeling these days, who mostly said that the data can still be trusted.

In any case, Ms. Groshen and other experts said, even a commissioner with ill intentions would not be able to meddle with the data, at least not in the short run and not without anyone’s noticing. The monthly jobs report is produced on a tight schedule using a highly automated and decentralized process. Most of the data that underlies the monthly payroll figure is reported directly by companies through an electronic system that is subject to strict access limitations. The commissioner, who is the agency’s only political appointee, does not have access to the numbers until they have been made final.

“There’s not like one person in a room who can manipulate things,” said Aaron Sojourner, an economist at the W.E. Upjohn Institute for Employment Research. “There are safeguards in place.”

No sharpies allowed.

Jon Keegan of Beautiful Public Data highlights researchers who used lidar to estimate fire damage in Southern California.

“We said, what would be a useful product for people to have as quickly as possible, since we’re doing this a couple weeks after the end of the fires? And we thought trying to get as high of a resolution and as kind of as differencing as possible would be a good idea,” said Brigham. Her team cleaned and reformatted the older, lower-resolution data and then subtracted the newer data. The resulting visualizations reveal the scale of devastation in ways satellite imagery can’t match. Red shows lost elevation (like when a building burns), and blue shows a gain (such as tree growth or new construction).

For NYT’s the Upshot, Ethan Singer found the birth of pickleball courts in aerial photographs.

By analyzing nearly 100,000 aerial photographs, we were able to identify more than 26,000 outdoor pickleball courts made in the last seven years — a majority of them at the expense of once-exclusive tennis spaces and created since the onset of the pandemic in 2020. In total, we found more than 8,000 tennis courts that had been transformed for pickleball.

Singer used computer vision to get precise coordinates of each court. Then he compared that data against old photographs to find tennis courts taken over by pickleball.

The sliding effect for before and after photographs works well here, given the contrast between a lone tennis court and a tennis court with four pickleball boundaries drawn on top.

This week is about helping people see data for what it is and avoiding poor choices.

NYPD arrested the wrong man, because facial recognition marked a match. Maria Cramer and Kashmir Hill report for the New York Times:

Like Mr. Williams, the culprit was Black, had a thick beard and mustache, and wore his hair in braids. Physically, the two men had little else in common. Mr. Williams was not only taller, he also weighed 230 pounds. The victim said the delivery man appeared to weigh about 160 pounds. But Mr. Williams still spent more than two days in jail in April.

“In the blink of an eye, your whole life could change,” Mr. Williams said.

It’s clear that facial recognition can be useful for finding people, but without considering outside information, officers use the tool wrong. If they cannot use the tool correctly, then they should not use the tool.

The New York Times estimated political bias in Grok’s models. They entered questions from an ideology survey and evaluated the chatbot’s answers over time.

By July 11, xAI’s updates had pushed its chatbot’s answers to the right for more than half the questions, particularly those about the government or the economy, the tests showed. Its answers to about a third of the questions — most of them about social issues like abortion and discrimination — had moved to the left, exposing the potential limits Mr. Musk faces in altering Grok’s behavior. Mr. Musk and his supporters have expressed frustration that Grok is too “woke,” something the billionaire said in a July post that he is “working on fixing.”

Musk continues to make “fixes” that align with his opinions. Not ideal.

A Tesla Model S, while on “Autopilot”, crashed into a parked truck, killing one and injuring another. Tesla claimed in a lawsuit that the data about the crash could not be found. So lawyers for the plaintiffs tried a different route. For the Washington Post, Trisha Thadani and Faiz Siddiqui report:

That’s when they turned to hacker greentheonly, who had a robust social media following for his work recovering data from damaged Teslas and posting his findings on X.

[…]

Inside a Starbucks near the Miami airport, the plaintiffs’ attorneys watched as greentheonly fired up his ThinkPad computer and plugged in a flash drive containing a forensic copy of the Autopilot unit’s contents. Within minutes, he found key data that was marked for deletion — along with confirmation that Tesla had received the collision snapshot within moments of the crash — proving the critical information should have actually been accessible all along.

Even if the data were corrupted or lost initially, which it seems like it wasn’t, Tesla should know their systems well enough to access the data in different ways. One would hope at least, for a company pushing for ubiquitous self-driving cars. Either that or Tesla should hire greentheonly to fix all their systems.

Pew Research asked U.S. adults if certain behaviors in public, such as cursing or smoking, were acceptable. The above are the results for four age groups.

For every behavior, the percentage of people who said it was rarely or never acceptable increased with age. Television and movies (and my own experiences) would tell you that sounds about right, but for some reason the clear trend surprised me. A quiz with the behaviors lets you get in on the action to see how crotchety you are.

At least we all mostly agree that taking a photo without permission is not acceptable. Now about all that public surveillance.

Gordon Hart put together a fun interactive atlas of space. Click on objects, pan, and zoom. It’s not comprehensive but not bad for a side project:

This was a fun side project over Winter Break 2024 to learn orbital mechanics, browser animation, serverless deployment options, and of course facts about moons, asteroids, and comets. Building for yourself is a treat that I haven’t properly enjoyed in some time. Source code is available on GitHub at @gordonhart/atlasof.space.

TSA PreCheck allows U.S. travelers to skip the part of airport security where you take your shoes off. For NYT’s the Upshot, Ben Blatt and Christine Chung analyzed wait times at a handful of airports to see if the program really shaves off minutes. The program seems to help most of the time, at New York airports at least.

At these airports — Kennedy, LaGuardia and Newark — PreCheck saves travelers five to 10 minutes on average, according to our analysis. But this will depend on the terminal you’re flying out of and the time of day you’re departing. Sometimes you may save over 30 minutes, sometimes none at all.

At some other major airports, the average time saved appears to be lower than in New York.

A histogram shows the distribution of wait times. The orange side on the right indicates less time waiting with PreCheck than with non-PreCheck. The blue side on the left indicates the same or more.

The U.S. federal government does not release official numbers for the cuts to health agencies, so ProPublica tracked changes to federal employee directories to estimate. They estimate 20,500 workers lost since January 2025. With a set of unit charts, each square represents five employees.

For WaPo’s Department of Data, Andrew Van Dam goes looking for American and British words, finding the most statistical action in spoken words over written.

We used our new measure to focus our book-word analysis on those words that people say out loud with at least some regularity. And with every crank of the out-loud-ness dial, we watch the two dialects get less and less similar, and more and more hilarious.

We start with relatively harmless terms. Footballers and whingeing stand out on one side, and statewide and nonfat stand out on the other. But it escalates quickly. British rises from manky and dodgy to shagging to knobhead and bruv. American goes from hoagie and doggone to homegirl and loogie to — at the slangiest echelons of the language — cornhole and bruh.

In the above, more British is on the left and more American is on the right, based on the OpenSubtitles dataset from Opus.

Then there’s the swear words.

Here are tools to use, datasets to poke at, and resources to learn from.

For Wired, Lauren Goode spent a day vibe-coding at Notion:

The next assignment was as open-ended as Lucy’s was specific: to build whatever I wanted. The freedom was unnerving, a Rorschach test for vibe coders. What did I see when I looked at the blinking cursor? I decided that there should be a way for Notion users to draft an “intelligent” to-do list in one step. They would be able to flick open the app and type “to do reorder pet food” and Notion AI would know what they meant. I also wanted this feature to avoid duplicate items from other recent to-do lists.

I was crushing it. I was a responsible babysitter for code, watching it cascade in front of my eyes and then toddle its way into the world. Except, my logic was wrong. My to-do list hack was somehow allowing for endless duplicates instead of avoiding them. Who was to blame: me or the AI?

A product designer named Brian talked me through it. “Pretend you’re talking to a smart intern,” he said. Again with the interns.

Kudos for not using “magic” even once.

New to me, someone anonymously scraped and published the Spotify playlists of a handful of celebrities and politicians. The project is called the Panama Playlists.

I found the real Spotify accounts of celebrities, politicians, and journalists. Many use their real names. With a little investigating, I could say with near-certainty: yep, this is that person.

I’ve been scraping their playlists for over a year. Some individuals even have a setting enabled that displays their last played song. I scraped this continuously, so I know what songs they played, how many times, and when.

The Panama Papers revealed hidden bank accounts. This reveals hidden tastes.

Will Smith posted a video showing highlights from his tour, but parts of it look AI-generated. Signs in the crowd are illegible, faces look smudged, and fingers are maybe a little too long. Andy Baio looked into it more closely, showing why the internet thinks the crowds are fake but are probably real and it’s more likely bad AI-assisted editing.
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