Couples find that lab-grown diamonds make it cheaper to get engaged or upgrade to a bigger ring. But there are rocky moments.
4 min
Wedding planner Sterling Boulet has some advice for brides-to-be regarding lab-grown diamonds, which cost a fraction of the natural ones.
“If you’re trying to get your man to propose, they’ll propose faster if you offer this as an option,” says Boulet, of Raleigh, N.C. Recently, she adds, a friend’s fiancé “thanked me the next three times I saw him” for telling him about the cheaper lab-made option.
Man-made diamonds are catching on, despite some lingering stigma. This year was the first time that sales of lab-made and natural mined loose diamonds, primarily used as centre stones in engagement rings, were split evenly, according to data from Tenoris, a jewellery and diamond trend-analytics company.
The rise of lab-made stones, however, is bringing up quirks alongside the perks. Now that blingier engagement rings—above two or three carats—are more affordable, more people are dealing with the peculiarities of wearing rather large rocks.
Esther Hare, a 5-foot-11-inch former triathlete, sought out a 4.5-carat lab-made oval-shaped diamond to fit her larger hands as a part of her vow renewal in Hawaii last year. It was a far cry from the half-carat ring her husband proposed with more than 25 years ago and the 1.5-carat upgrade they purchased 10 years ago. Hare, 50, who lives in San Jose, Calif., and works in high tech, chose a $40,000 lab-made diamond because “it’s nuts” to have to spend $100,000 on a natural stone. “It had to be big—that was my vision,” she says.
But the size of the ring has made it less practical at times. She doesn’t wear it for athletic training and swaps in her wedding band instead. And she is careful to leave it at home when traveling. “A lot of times I won’t take it on vacation because it’s just a monster,” she says.
The average retail price for a one-carat lab-made loose diamond decreased to $1,426 this year from $3,039 in 2020, according to the Tenoris data. Similar-sized loose natural diamonds cost $5,426 this year, compared with $4,943 in 2020.
Lab-made diamonds have essentially the same chemical makeup as natural ones, and look the same, unless viewed through sophisticated equipment that gauges the characteristics of emitted light.
At Ritani, an online jewellery retailer, lab-made diamond sales make up about 70% of the diamonds sold, up from roughly 30% two years ago, says Juliet Gomes, head of customer service at the company, based in White Plains, N.Y.
Ritani sometimes records videos of the lab-diamonds pinging when exposed to a “diamond tester,” a tool that judges authenticity, to show customers that the man-made rocks behave the same as natural ones. “We definitely have some deep conversations with them,” Gomes says.
Not all gem dealers are rolling with these stones.
Philadelphia jeweller Steven Singer only stocks the natural stuff in his store and is planning a February campaign to give about 1,000 one-carat lab-made diamonds away free to prove they are “worthless.” Anyone can sign up online and get one in the mail; even shipping is free. “I’m not selling Frankensteins that were built in a lab,” Singer says.
Some brides are turned off by the larger bling now allowed by the lower prices.When her now-husband proposed with a two-carat lab-grown engagement ring, Tiffany Buchert, 40, was excited about the prospect of marriage—but not about the size of the diamond, which she says struck her as “costume jewellery-ish.”
“I said yes in the moment, of course, I didn’t want it to be weird,” says the physician assistant from West Chester, Pa.
But within weeks, she says, she fessed up, telling her fiancé: “I think I hate this ring.”
The couple returned it and then bought a one-carat natural diamond for more than double the price.
When Boulet, the wedding planner in Raleigh, got engaged herself, she was over the moon when her fiancé proposed with a 2.3 carat lab-made diamond ring. “It’s very shiny, we were almost worried it was too shiny and was going to look fake,” she says.
It doesn’t, which presents another issue—looking like someone who really shelled out for jewellery. Boulet will occasionally volunteer that her diamond ring came from a lab.
“I don’t want people to think I’m putting on airs, or trying to be flashier than I am,” she says.
For Daniel Teoh, a 36-year-old software engineer outside of Detroit, buying a cheaper lab-made diamond for his fiancée meant extra room in his $30,000 ring budget.
Instead of a bigger ring, he got her something they could both enjoy. During a walk while on an annual ski trip to South Lake Tahoe, Calif., Teoh popped the question and handed his now-wife a handmade wooden box that included a 2.5-carat lab-made diamond ring—and a car key.
She put on the ring, celebrated with both of their sisters and a friend, who was the unofficial photographer of the happy event, and then they drove back to the house. There, she saw a 1965 Mustang GT coupe in Wimbledon white with red stripes and a bow on top.
Looking back, Teoh says, it was still the diamond that made the big first impression.
“It wasn’t until like 15 minutes later she was like ‘so, what’s with this key?’” he adds.
Copyright 2020, Dow Jones & Company, Inc. All Rights Reserved Worldwide. LEARN MORE
The Australian leather house has opened an immersive four-day pop-up in Manhattan, unveiling its Bloom Collection and redefining what a product launch can look like.
Following the successful launch of its Palais Collection, MAISON de SABRÉ has unveiled a new modular handbag system offering more than 720 styling combinations.
AI doesn’t rebel—people design, deploy and profit from it. The real danger lies in allowing tech companies to escape accountability while shaping regulations that protect their dominance.
4 min
A wave of corporate warnings and technical disclosures has flooded the media, with headlines worrying over “swarms” of rogue artificial-intelligence agents launching “unprecedented” cyberattacks, outsmarting their makers, and inching toward a terrifying autonomy. The most revealing part of this narrative isn’t what the software did. It’s who is telling the story—and why. When corporate leaders publicly insist that the systems they financed, engineered and deployed are suddenly beyond their power to contain, skepticism isn’t only healthy; it is essential.
For years, Silicon Valley has drawn scrutiny from civil society and global regulators over tangible harms such as youth mental health deterioration and systematic privacy violations. Today, industry figures seem to be trying to change that public image. Loudly blowing the whistle on their own systems—just as two of the leading companies were preparing for massive initial public offerings—lets AI executives position themselves as a new generation of leaders who have come to terms with their societal responsibilities. They seem to want us to believe that they no longer want to “move fast and break things” but will instead stand as vigilant guardians between humanity and a technological apocalypse.
There is one glaring problem: Software doesn’t rebel. A mathematical model possesses neither intent, malice nor the will to defy its creators, let alone extinguish our species. AI is a human artifact, engineered for profit.
When an agentic model in an evaluation sandbox connects to an unauthorized server or executes an exploit, it hasn’t staged a coup. It has tried to meet the human-defined objectives set out before it through a path its designers failed to constrain. It’s the digital equivalent of the King Midas myth, in which the king’s ill-defined wish turns even his food and drink into gold.
That powerful experimental models were able to discover novel vulnerabilities and breach external systems isn’t a sign of a dangerous superintelligence but of human error or negligence. There is no sentient actor lurking in the weights to be reasoned with, feared or pacified. There are only human software engineers, product managers and corporate boards deciding which guardrails are worth the latency cost and which permissions can be skipped in the race to market.
Policymakers and voters need to resist AI exceptionalism. In any other discipline—from civil engineering to pharmaceuticals—courts and regulators treat a system failure as evidence of bad product design and inadequate safety testing. If an aircraft crashes, we focus on finding the engineering defect, correcting it, and enforcing established liability standards for the damage created.
By leaning on an anthropomorphic narrative, Silicon Valley attempts to repackage its specific human choices that led to experimental, powerful models behaving unexpectedly during tests as an existential peril. Elevating the issue to a cosmic scale leaves the public paralyzed and takes ordinary product accountability off the table.
In the cutthroat race for venture capital and market dominance, building guardrails slows down deployment. Grandstanding about uncontrollable power costs nothing and generates billions of dollars in free publicity, justifying stock prices, all while cultivating an aura of technological capability not only to build the frontier but also ultimately to rein it in.
Governments need to recognize regulatory capture when it stares them in the face. Tech leaders’ strategy looks transparent: Alarm Washington and Brussels into creating a regime in which only trillion-dollar incumbents with fully staffed compliance and safety departments can legally operate. By sitting at the policymakers’ tables before anyone else, these companies can help draft rules digging an impassable moat protecting them from open-source developers and upstart competitors, domestic or international. The real danger is in further concentrating the tech industry into the hands of only a few companies with deep pockets.
Beijing and Washington have brushed off those tech leaders’ calls, albeit for very different reasons. Chinese state media dismissed them as part of the “Cold War playbook” and intended to preserve U.S. dominance. Xi Jinping argued for exactly the opposite at the Brics Summit on Sept. 12, calling on Brics countries to “strengthen cooperation in the field of AI, encourage open source, openness, collaboration and sharing, and break new grounds and scale new heights.” President Trump, steeped in a doctrine of unfettered capitalism and technological supremacy, called fears that AI could destroy humanity a “hoax.” Vice President JD Vance warned that AI companies “begging the government to regulate them” looked like a “Trojan Horse.”
Striving to pursue its “European way” on AI and assert regulatory leadership, Europe, by contrast, welcomed the call. European Union President Ursula von der Leyen made this clear at the State of the EU speech last Wednesday and announced that the EU will invite “the main frontier labs for a discussion on how we can support ongoing industry efforts to pace the frontier.”
Europe has been here before. In an effort to lead global regulation and react to fears borne from ChatGPT, Europe rushed its landmark AI Act into law in 2024. Already the world’s most restrictive rulebook, the framework quickly proved too broad and complex to enforce. Stalled by implementation delays and concerns about European competitiveness, the EU postponed the law’s full rollout, leaving regulations uncertain.
AI should be regulated—risks exist and should be taken seriously. But governments need to act based on available evidence and verified facts, not corporate PR panic, the views of industry insiders, or the desire for quick political wins. The greatest danger facing society isn’t that software will awaken and overthrow its human masters. It is that we will allow the creators of the software to abdicate human responsibility for the systems they choose to build and help them pull up the ladder to market access behind them.
