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Women in the U.S. are waiting longer to have babies. For the first time, the average age for giving birth has risen to nearly 30, according to a new report. The data, which comes from the National Vital Statistics System, was published on Friday in the CDC’s National Center for Health Statistics report. Per the report, the average age for giving birth rose by nearly a year from 2016 to 2023. It went from 28.7 years old to 29.6. Likewise, the age for first-time mothers increased similarly over the same time period, from 26.6 to 27.5. Interestingly, teen pregnancies fell, too. In 2016, they accounted for 11.8% of all births. In 2023, they made up only 8.7%. The latest findings are in line with the fact that many people are delaying marriage until later in life. According to a 2021 Pew Research report, the average age for tying the knot has risen dramatically since the 1980s. The number of U.S. adults who were married by age 21 dropped from about 33% in 1980 to 6% in 2021. And marrying by age 25 plunged, too, from nearly 66% to 22%. However, according to the same report, people aren’t just delaying marriage until their late 20s or even 30s. About 25%a record numberwere still unmarried at 40. Of course, the fact that it’s become massively more expensive to have a family likely plays a role in women delaying having children, or not having any at all. A recent LendingTree analysis found that since 2023, the annual cost of raising a young child has jumped by nearly 36%. In 2025, the tab is around $30,000 per year. Over 18 years, raising a child costs $300,000 (though in several states, it’s even higher). However, women also are increasingly becoming financially independent, and perhaps decentering the goal of marriage and motherhood at the same time. In 2024, 20% of homebuyers were single women, while only 8% of single men bought their own homes last year. And a 2019 Morgan Stanley report projected that by 2030, 45% of women between 25 and 44 will be single and child-free. U.S. women are not the only ones delaying motherhood. According to recent government data, per The Guardian, Japanese women are doing the same. In 2024, the number of births in Japan dropped by 5.7% from the previous year, to 686,061. The number marks the lowest birth rate since the recordkeeping began in 1899. The latest data comes as the Trump administration has recently floated the idea of incentivizing childbirth by giving families a $5,000 “baby bonus” to help offset the costs. Given that the hospital bills alone for giving birth in the U.S. can average around $3,000 (for a vaginal delivery with insurance), it’s unlikely the plan will persuade too many American women to have babies before they’re financially ready and able (or even at all).
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Consumer sentiment increased in June for the first time in six months, the latest sign that Americans views of the economy have improved as inflation has stayed tame and the Trump administration has reached a truce in its trade fight with China. The preliminary reading of the University of Michigans closely watched consumer sentiment index, released Friday, jumped 16% from 52.2 to 60.5. The large increase followed steady drops that left the preliminary number last month at the second-lowest level in the nearly 75-year history of the survey. Consumer sentiment is still down 20% compared with December 2024. Consumers appear to have settled somewhat from the shock of the extremely high tariffs announced in April and the policy volatility seen in the weeks that followed, Joanne Hsu, director of the survey, said in a written statement. However, consumers still perceive wide-ranging downside risks to the economy. Americans have largely taken a darker view of the economys future after President Donald Trump unleashed a wide-ranging trade war, imposing steep tariffs on China, the European Union, and dozens of other countries. Yet in April Trump postponed a set of sweeping tariffs on about 60 nations and last month reached a temporary truce with China, after both sides had sharply ratcheted up tariffs on each other. The Conference Board’s consumer confidence index, released in late May, also increased after five straight declines that were linked to anxiety over tariffs. U.S. duties remain elevated compared with historical levels, but so far they have not worsened overall inflation. Prices rose just 2.4% in May compared with a year ago, up slightly from 2.3% in April. Still, most economists expect tariffs to hit harder in the coming months. Consumer confidence is sharply divided by political outlook, with Republicans feeling much better about the economy under Trump than Democrats. Democratic sentiment about the economy was much higher under Biden, while Republican views were low. This month, however, sentiment did improve among supporters of both parties and independents. Consumers’ inflation expectations basically a measure of how worried people are about future inflation dropped this month, which will be welcomed by the inflation-fighters at the Federal Reserve. Inflation expectations can become self-fulfilling, because if people worry price increases will get worse, they can take steps such as demanding higher pay that push prices even higher. The Fed meets next week, and is expected to keep its key short-term interest rate unchanged at about 4.3%. Christopher Rugaber, AP economics writer
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E-Commerce
As AI car crashes go, the recent publishing of a hallucinated book list in the Chicago Sun-Times quickly became a multi-vehicle pile-up. After a writer used AI to create a list of summer reads, the majority of which were made-up titles, the resulting article sailed through lax editorial review at the Sun-Times (and at least one other newspaper) and ended up being distributed to thousands of subscribers. The CEO eventually published a lengthy apology. The most obvious takeaway from the incident is that it was a badly needed wake-up call about what can happen when AI gets too embedded in our information ecosystem. But CEO Melissa Bell resisted the instinct to simply blame AI, instead putting responsibility on the humans who use it and those who are entrusted with safeguarding readers from its weaknesses. She even included herself as one of those people, explaining how she had approved the publishing of special inserts like the one the list appeared in, assuming at the time there would be adequate editorial review (there wasn’t). The company has made changes to patch this particular hole, but the affair exposes a gap in the media landscape that is poised to get worse: as the presence of AI-generated contentauthorized or notincreases in the world, the need for editorial safeguards also increases. And given the state of the media industry and its continual push to do “more with less,” it’s unlikely that human labor will scale up to meet the challenge. The conclusion: AI will need to fact-check AI. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/03\/mediacopilot-logo-ss.png","headline":"Media CoPilot","description":"Want more about how AI is changing media? Never miss an update from Pete Pachal by signing up for Media CoPilot. To learn more visit mediacopilot.substack.com","substackDomain":"https:\/\/mediacopilot.substack.com\/","colorTheme":"blue","redirectUrl":""}} Fact-checking the fact-checker I know, it sounds like a horrible idea, somewhere between letting the fox watch the henhouse or sending Imperial Stormtroopers to keep the peace on Endor. But AI fact-checking isn’t a new idea: In fact, when Google Gemini first debuted (then called Bard), it shipped with an optional fact-check step if you wanted it to double-check anything it was telling you. Eventually, this kind of step simply became integrated into how AI search engines work, broadly making their results better, though still far from perfect. Newsrooms, of course, set a higher bar, and they should. Operating a news site comes with the responsibility to ensure the stories you’re telling are true, and for most sites the shrugging disclaimer of “AI can make mistakes,” while good enough for ChatGPT, doesn’t cut it. That’s why for most, if not all, AI-generated outputs (such as ESPN’s AI-written sports recaps), humans check the work. As AI writing proliferates, though, the inevitable question is: Can AI do that job? Put aside the weirdness for a minute and see it as math, the key number being how often it gets things wrong. If an AI fact-checker can reduce the number of errors by as much if not more than a human, shouldn’t it do that job? If you’ve never used AI to fact-check something, the recently launched service isitcap.com offers a glimpse at where the technology stands. It doesnt just label claims as true or falseit evaluates the article holistically, weighing context, credibility, and bias. It even compares multiple AI search engines to cross-check itself. You can easily imagine a newsroom workflow that applies an AI fact-checker similarly, sending its analysis back to the writer, highlighting the bits that need shoring up. And if the writer happens to be a machine, revisions could be done lightning fast, and at scale. Stories could go back and forth until they reach a certain accuracy threshold, with anything that falls short held for human review. All this makes sense in theory, and it could even be applied to what news orgs are doing currently with AI summaries. Nieman Lab has an excellent write-up on how The Wall Street Journal, Yahoo News, and Bloomberg all use AI to generate bullet points or top-line takeaways for their journalism. For both Yahoo and the Journal, there’s some level of human review on the summaries (for Bloomberg, it’s unclear from the article). These organizations are already on the edge of whats acceptablebalancing speed and scale with credibility. One mistake in a summary might not seem like much, but when trust is already fraying, its enough to shake confidence in the entire approach. Human review helps ensure accuracy, of course, but also requires more human laborsomething in short supply in newsrooms that don’t have a national footprint. AI fact-checking could give smaller outlets more options with respect to public-facing AI content. Similarly, Politico’s union recently criticized the publication’s AI-written reports for subscribers based on the work of its journalists, because of occasional inaccuracies. A fact-checking layer might prevent at least some embarrassing mistakes, like attributing political stances to groups that don’t exist. The AI trust problem that wont go away Using AI to fight AI hallucination might make mathematical sense if it can prevent serious errors, but there’s another problem that stems from relying even more on machines, and it’s not just a metallic flavor of irony. The use of AI in media already has a trust problem. The Sun-Times‘ phantom book list is far from the first AI content scandal, and it certainly won’t be the last. Some publications are even adopting anti-AI policies, forbidding its use for virtually anything./p> Because of AI’s well-documented problems, public tolerance for machine error is lower than for human error. Similarly, if a self-driving car gets into an accident, the scrutiny is obviously much greater than if the car was driven by a person. You might call this the automation fallout bias, and whether you think it’s fair or not, it’s undoubtedly true. A single high-profile hallucination that slips through the cracks could derail adoption, even if it might be statistically rare. Add to that what would probably be painful compute costs for multiple layers of AI writing and fact-checking, not to mention the increased carbon footprint. All to improve AI-generated textwhich, lets be clear, is not the investigative, source-driven journalism that still requires human rigor and judgment. Yes, we’d be lightening the cognitive load for editors, but would it be worth the cost? Despite all these barriers, it seems inevitable that we will use AI to check AI outputs. All indications point to hallucinations being inherent to generative technology. In fact, newer “thinking” models appear to hallucinate even more than their less sophisticated predecessors. If done right, AI fact-checking would be more than a newsroom tool, becoming part of the infrastructure for the web. The question is whether we can build it to earn trust, not just automate it. The amount of AI content in the world can only increase, and we’re going to need systems that can scale to keep up. AI fact-checkers can be part of that solution, but only if we manageand accepttheir potential to make errors themselves. We may not yet trust AI to tell the truth, but at least it can catch itself in a lie. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/03\/mediacopilot-logo-ss.png","headline":"Media CoPilot","description":"Want more about how AI is changing media? Never miss an update from Pete Pachal by signing up for Media CoPilot. To learn more visit mediacopilot.substack.com","substackDomain":"https:\/\/mediacopilot.substack.com\/","colorTheme":"blue","redirectUrl":""}}
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