The U.S. Bureau of Labor Statistics published cost estimates for April 2026. If you’ve bought anything over the past month, you’ve likely noticed a rise. For the Washington Post, Rachel Lerman and Federica Cocco charted the rising cost of groceries this year, before and after the war with Iran.

Prices were already going up because of tariffs (remember those?), but the war is pushing costs up harder. Soon, we will pay for goods with cherry tomatoes.

The percentage of U.S. men in the workforce has been declining for decades, with a sharper shift the past few years. For the Washington Post, Lauren Kaori Gurley and Federica Cocco report.

“It’s not all retirement and education. … There are guys just dropping off the planet. They’re not looking after their kids. They’re not in school. They’re not in the labor force,” said Betsey Stevenson, a professor of economics at the University of Michigan. “Across the board when we look at men, we see challenges that they face that leave too many men disconnected.”

Since 2006, the percentage is down six percentage points, which is maybe a bit less than you would think after looking at the line chart above. The reasons of course are multifaceted, but if I were to guess, I’d say more women in workforce has and will continue to change dynamics at work and at home.

Raymond Zhong and Harry Stevens, for the New York Times, go with a sketch aesthetic to describe the effects of El Niño. Some areas are wetter and others are drier. Although it’s still difficult to forecast the full range geographically and the magnitude of the effects. Because wind.

For the New York Times, Agnes Chang and Pablo Robles illustrate the journey from the Strait of Hormuz to the gas tank. The oil starts in a tanker, waiting to move through the strait, and the journey begins as you scroll. There are transfers, checkpoints, and changes in transportation.

I like the transfers where there’s a stop and you get taken through the various steps. Even if the strait opened right now, it would still take a month for travel, processing, and more travel.

For Bloomberg, Tanaz Meghjani, Dhruv Mehrotra, and Surya Mattu report sharing of private data.

TikTok’s filtering on the Washington exchange relied on preset keyword lists to identify sensitive categories prohibited under their policies — including race, religion, sexual orientation, political affiliation, union membership and criminal record. The filter hides terms such as “Asian,” “Black,” “Muslim” and “Jewish,” plus US political references like “Democrat,” “Republican,” “MAGA” and “Antifa.” Any terms missing from the preset list were not filtered.

“It’s a flawed and brittle process for filtering unwanted information,” said Zach Edwards, an independent cybersecurity expert who has spent years auditing advertising technology developed by US tech giants.

It seems like the sharing is unintentional yet careless, which is par for the course these days. The honor system might not be enough to keep this internet thing usable long-term.

This week is about constraints.

For the Public Domain Review, Hunter Dukes and Adam Green visit Antoni Jażwiński’s Polish System, which charts space and time in a grid layout.

The Polish System — which almost anticipates Piet Mondrian’s abstract checkerboards and the wider modernist fascination with grid figures — coupled chronology to the map-making traditions of geography. In Jażwiński’s original chart, each main 10×10 box is a century and the rows separate decades. Within a century box, each individual square is a year, each color a nation (with shading for different monarchs or governments), and symbols can stand for marriages, wars, treaties, and other types of events. Should one become proficient with this system, they can peer down on the history of the world, summarized on a surface not much larger than a chessboard.

Not quite a calendar. Not quite a unit chart.

Beef prices keep going up a noticeable amount in grocery stores. For Bloomberg, Ilena Peng, Denise Lu, and Stephanie Davidson charted how increasing costs in the supply chain feed into the dollar amount that we see at the end.

To demonstrate with relatable units, they follow the timeline of a single calf as it moves from ranch, to stocker, feedyard, meatpacker, grocer, and consumer. Illustrations provide a visual anchor through the process.

Chicken overtook beef in 2004. It doesn’t seem like that’s going to let up any time soon.

John Nelson and Peter Atwood review maps that appeared in movies, such as Indiana Jones, Harry Potter, and Goonies. They discuss implementation, practical aspects, and accuracy. It’s about as nerdy as you imagine it to be.

Researchers analyzed newly published websites from 2022 through mid-2025 to estimate what percentage used generated text and how this might affect future information online.

The proliferation of AI-generated and AI-assisted text on the internet is feared to contribute to a degradation in semantic and stylistic diversity, factual accuracy, and other negative developments. We find that by mid-2025, roughly 35% of newly published websites were classified as AI-generated or AI-assisted, up from zero before ChatGPT’s launch in late 2022. We also find evidence suggesting that increases in AI-generated text on the internet bring about a decrease in semantic diversity and an increase in positive sentiment. We do not, however, find statistically significant evidence supporting the hypothesis that an increased rate of AI-generated text on the internet decreases factual accuracy or stylistic diversity. Notably, our findings diverge from public perception of AI’s impact on the internet.

So it has grown to about a third of new sites that use AI-generated or AI-assisted text. That seems like a lot?

I’m more surprised that there didn’t appear to be a significant change in fake information or a convergence in style.

My theory is that most people putting up these generated sites are either experimenting or trying to make a quick buck. Either way, they just take whatever information is given to them via a probabilisitic model and forget about it. They don’t care what the words say or how it is said, just as long as it fills space. So the output defaults to mostly correct statements.

It seems every day the chances that AI transforms work trends towards certain. The less certain part is the how. Some jobs could go away but new ones might appear. Employment needs could rise, even for jobs with high AI exposure. For Financial Times, John Burn-Murdoch looks at jobs over the past few decades to see how new technologies changed work in unexpected ways.

The cost of an electrical vehicle used to increase quickly as you shopped for more range, but EVs that go farther have been getting less expensive in recent years. For NYT’s the Upshot, Francesca Paris shows the current trends.

I like the side-by-side trend line comparison between the steeper slow for 2016 to 2019 models versus the 2024 to 2026 models. The shift is clear and obvious.

Once the trend line flattens and Toyota makes a fully electric Corolla, I’m in.

Every month I collect tools, datasets, and resources to help you make more useful data things. Here is what happened in April.

Hank Green dissects a video that argues against climate change. The video in question cherrypicks, makes up data, and lies about many things, all wrapped up with a calm narrator to make it seem reasonable. Green less calmly explains the manipulation.

It’s always a good time to strengthen your defenses against dishonest charts.

Apparently, the words we use and how we structure our sentences in writing is nearly as unique as our fingerprints. Kelsey Piper has been using this to benchmark new LLMs by entering text and asking who wrote it. Anthropic’s Opus 4.7 model was the first to return all the correct answers.

For WaPo opinion, Megan McArdle tested the search with her own unpublished text.

Would Claude do better or worse with something more modern? I fed Claude a different opening chapter from an unpublished science fiction novel I started right before the pandemic — I contain multitudes — and this time Claude needed only 1,132 words. The eulogy I gave for my mother, lightly edited to remove some too-specific biographical details, was even faster: Depending on the passage, Claude was able to peg me as the author in as few as 124 words.

I’m too scared to try this on myself, but I’ll assume it works. Lucky for me, I’ve always written and made things with the assumption that my mother would see it.

However, if you publish words or share thoughts on social media, I hope you don’t value online anonymity too much.

For Rest of World, Rina Chandran reports on the big difference in excitement:

As AI adoption increases globally, anxiety about AI is rising — but so is optimism about its benefits, according to a recent study from Stanford University’s Human-Centered Artificial Intelligence center. Not in the U.S. To the prompt, “products and services using AI make me excited,” only 38% of respondents in the U.S. said yes, in comparison to 84% in China. Southeast Asians are among the most optimistic about AI, with 80% of Indonesians, 77% of Malaysians, and 79% of Thais agreeing.

The difference in sentiment appears to be related to each country’s trust in government regulation. From the Stanford study, here are the percentages for those who said they trust their government:

Singapore is over 80 percent trusting. Meanwhile, the United States is the lowest at 31 percent.

This isn’t all that surprising, but I wonder why there is such a big difference. Is there an overall distrust in government and AI companies in the United States? With the largest companies in the United States, do we get a closer look and therefore more skepticism?

For NYT Opinion, Paul Ford on the challenges for AI companies to build ethical systems:

All the while, money keeps gushing in. You start out transparent, sharing your journey, but then before an initial public offering of shares, you must honor the S.E.C.-mandated quiet period and restrict promotional communications. After that, the transparency never quite returns. The market demands a rising stock price. Your company still makes a lot of software, but a huge amount of time goes to tax strategy and compliance.

At that scale, people start to blur together, and human users can become aggregate pools of statistics and growth vectors that go up and down — a mulch into which you plant your products.

Cue the Harvey Dent scene about living long enough to become the villain.

The Economist shows probabilities that a person votes for each party, given a set of demographics.

But the electorate is not monolithic. The Economist has built a statistical model of it based on a survey of voting intentions by More In Common, a pollster. Our model estimates the probability that any individual will vote for one of Britain’s main political parties based on the eight characteristics that most influence voters’ choices: sex, age, ethnicity, region, education, employment status, type of housing and whether it is in a rural or urban area. In different combinations these characteristics yield 275,000 different voter profiles. Each week we get new polling data and update our calculations.

Select the demographics, such as sex, age, race, and education, and see how each factor swings the probability for each party. The overall prediction shows at the bottom.

The 2008 decision tree by Cox comes to mind.

The Kyoto Aquarium in Kyoto and the Sumida Aquarium in Tokyo each have detailed relationship diagrams for their penguins. The above is for Kyoto.

The networks are framed as reality shows with weddings, divorce, and cheating, along with likes and dislikes of each penguin. Watch out for the penguin named Pon:

Kuruma and Tako live next door to each other, and Pon has been visiting each of them in turn for snuggle sessions. Both boys are obsessed with Pon, but it seems neither of them can fully satisfy her. What’s the fate of this neighborhood love triangle!?

Oh my.

I don’t know why these exist, but it’s nice that they do. The aquariums have updated the networks each year since 2024.

[Thanks, Charlotte]