One Man’s Quest to Reunite With His First Love: A 1971 VW Bug

Locals in Pawleys Island have a special affection for classic vehicles. The coastal South Carolina town is home to many nostalgic retirees, and on weekends its streets see plenty of restored ‘60s-era muscle cars.

Of all the classics motoring past Parlor Doughnuts on Ocean Highway, none has captured the community’s attention like Rudolph the Red-Nosed Volkswagen.

“Everybody in town rubber necks and waves when this Beetle drives by,” says Rev. Wil Keith, a 47-year-old priest. “It’s one of the much-adored cars in our little town right now.”

It is a 1971 red Super Beetle and its story is special.

Jeff Siegrist was a student at the University of Tennessee when he first set eyes on her at a Knoxville dealership.

Siegrist pounced, handing over his father’s old Ford Falcon and $2,278.54 for the Bug. He kicked in $67.45 for an AM radio and $5.95 for a cigarette lighter.

“So that was my car from that day forward,” says Siegrist, an executive search consultant specialising in the forest products industry.

The Beetle was a sales phenomenon and a pop-culture hit that ushered in the era of mass European auto imports. It was also a Hollywood star, thanks to Herbie from the “Love Bug” movie franchise.

Siegrist road-tripped his Beetle all over. When he met his future wife, Mary, he took her on a first date in the red Bug. When the couple had their first child, the baby boy came home in the backseat.

“It was part of the family,” says Siegrist. Mary gave the car its name, around Christmas time in 1972: Rudolph.

The couple had two more children and ultimately sold the car in 1996. “It just wasn’t practical anymore,” he says. “There were tears in my eyes.”

Up to this point, the story isn’t much different from many of the more than 21.5 million original Beetles that Volkswagen sold.

But during the pandemic, things got interesting.

“I kept thinking, ‘Boy, I wish I knew where my old Beetle was,’” says Siegrist. “I wondered whether other people loved it the way my wife and I did.”

Eventually he got serious. He dug up the car’s original bill of sale, which had a vehicle identification number. He had sold the car to someone in Georgia, a quarter century earlier.

So he called the Georgia department of motor vehicles. Turns out the car was still registered and on the road. But that’s all the office would say.

Siegrist got an attorney involved. Two weeks later, the lawyer called with a name and a phone number for a woman he believed to be the current owner. So Siegrist called.

“I was shocked,” says Tracy Swift, who teaches dental hygiene at Albany State University in Georgia. “He started the conversation with, ‘You’re going to find this phone call very weird.’” Swift thought she had a stalker, and recalls Siegrist saying, “I’m not crazy, I promise. Just let me tell you my story.”

Swift did drive a 1971 Beetle. She checked the VIN number and it was a match.

Siegrist traveled to Georgia, met Swift at her office, and drove the car in the parking lot. “I didn’t want to sell the car,” she says, “but because of his story, I felt like it needed to go back to its owner. It was the sweetest story.”

They agreed on a price (he says “many times over the original cost”) and the car showed up on a truck in Siegrist’s driveway days later. It was just before Christmas in 2022.

The first thing Siegrist and his wife did was drive around the block, with tears in their eyes. “Rudolph is back!” his wife yelled as they drove.

Siegrist went digging in a bucket full of coins and junk for a key chain. At the bottom, he found Rudolph’s original key. He didn’t remember saving it.

The Beetle needed restoration. So Siegrist asked advice from someone he trusted. Enter Keith, the rector at Siegrist’s church.

“When you’re at church,” Keith says, “and the service is over and everyone is filing out, that’s when folks share, often, important information about their lives.”

Keith, it turns out, had grown up the son of a car restorer and worked on cars himself in his garage. He was not a professional. He worried if he would have enough time. But a parishioner needed help. How could he say no?

It took about a year. “Aside from the paint and some engine work,” Keith says, “I ended up doing more than I was expecting, with no complaints whatsoever. In some ways, it was like I gained a parishioner. Only it was a car.”

In 2024, Siegrist began driving Rudolph around Pawleys Island. “Rarely can I go anywhere where somebody doesn’t stop me,” he says.

“Because probably 50% of the people of my generation have owned a Beetle or have had an adventure in a Beetle. People want to know the car’s story. So I tell it.”

As for Keith, he says, “It’s a point of pride that I had a hand in it.” Like most classic car stories, this one continues.

“As soon as Jeff stops finding little things for me to fix, then the story will be over,” he says. “But he keeps finding things for me to do! Which I don’t mind one bit.”

There is ample and alarming evidence that artificial intelligence can help humans do bad things, such as committing cyberattacks, building weapons and even killing themselves or others. The Hugging Face hacking episode—and a growing list of others by poorly constrained swarms of agents—indicate just how powerful and potentially dangerous AI has quickly become.

Yet many inside the U.S. AI industry insist far worse is coming, on account of the imminent arrival of AI with superhuman and self-improving abilities.

Plenty of experts, including many who study AI harms for a living, are skeptical. The so-called doomers’ assertion that AI might decide to wipe out all of humanity—or even “just” topple human civilization—is contingent on it achieving a pace of development not yet seen.

And if the assumptions behind this global-doomsday scenario are wrong, it could lead us to curb or regulate AI in ways that don’t address its real harms.

At the center of this debate is the claim that current AI systems might take over the job of training their next versions, a process called “recursive self-improvement.” Think of it like evolution on steroids—billions of years happening at light speed within vast AI supercomputers. Anthropic Chief Executive Dario Amodei recently proposed a global agreement to slow down the pace of releasing new AI models, with the goal of delaying the arrival of recursive self-improvement.

“I don’t think we’re anywhere near ‘artificial general intelligence,’” says Melanie Mitchell, a professor at the nonprofit research group Santa Fe Institute who studies AI. She said AI is making impressive strides but thinks claims by engineers that they’ve achieved recursive self-improvement don’t stand up to scrutiny.

She is hardly alone. A recent paper by two dozen academics at Princeton, Stanford and other institutions found that even the most cutting-edge AIs are incapable of doing the original research required to advance the AI frontier.

Two of the authors involved in that paper also threw cold water on the idea that the Hugging Face swarm hack by OpenAI agents occurred because of a breakthrough in intelligence. The attack succeeded primarily because of a lack of basic technical guardrails, not an unmanageable explosion in AI capability, they wrote.

Yann LeCun, former chief AI scientist at Meta, posted that this analysis was “a welcome dose of sanity in an otherwise insane debate.”

OpenAI and Anthropic didn’t respond to several requests for comment.

The people who disagree with the doomers still consider AI to be dangerous, and point out that such systems don’t have to be particularly capable to be powerful. Some argue that AI should undergo regular evaluation by outsiders and that the companies that make it should be held responsible when their systems do harm. AI should also be treated the same as airplanes and elevators, and should be designed to do the least harm possible, they say.

“If you believe that technology is powerful enough to create novel, dangerous viruses, or to essentially take over the whole planet for some reason, then it must also be strong enough to create cures for cancer, to cure aging, to fix socio-economic or political problems,” says Christopher Canal, CEO of EquiStamp, a company that helps companies and governments evaluate AIs.

AI has shown an ability to rapidly advance because it is matching the abilities of humans who are constantly feeding it their knowledge. Sometimes it can recombine that knowledge and exceed what people have been capable of, through a kind of post-training known as reinforcement learning, as we’ve seen in mathematics.

Today’s LLMs are “models of knowledge” rather than actually intelligent, wrote Yi Ma, professor of AI at Hong Kong University.

Researchers at universities and commercial AI research labs in China wrote in a recent paper that autonomous, self-improving AI is likely to be a long way off, due to the sheer number of breakthroughs required. They also argue that humans will probably remain in the loop, supervising that process—and gating how fast it can occur.

Vals AI, a company that evaluates today’s AI models, maintains an RSI Index that benchmarks whether models can “do the research that builds the next model.” So far, no publicly released model is even close.

Yet Rayan Krishnan, CEO of Vals AI, says his team projects models will exceed humans’ ability to improve the next generation of AIs by August 2027, or sooner, and at that point could start building their successors all on their own.

“Once we get to recursive self-improvement, the fear is that all bets are off,” he says. “You could end up with a ‘fast takeoff’ situation, where the models quickly acquire skills and eclipse humans across every possible domain.”

In a reply to the resignation tweet heard round the world from Jacob Coxon, another Anthropic engineer declared his belief that those odds were at least 10% over the next decade. Many others in the industry chimed in to say they thought the percentage was even higher.

Some who argue the end is nigh say they calculate their personal p(doom) based on a chain of conditional probabilities—a bit like the Drake equation for calculating the likelihood of intelligent alien life. Since all those probabilities are based on speculation, estimates range from 0% to nearly 100%. Many land around 10%.

“The weird thing is that if you go back and look at the predictions on this over the last 10 years or more, it’s always been 10%—it’s just a nice round number,” says Mitchell. “I think it’s all vibes, and there’s no actual evidence or calculation.”

One argument against worrying about superintelligent AI is that the world is full of unlikely humanity-ending disasters, and trying to avert them all can make it impossible to prioritize, says Canal.

This has led AI experts and the policymakers who listen to them to propose remedies that don’t get at its real and present dangers.

AI companies’ proposals to “pace the frontier” aren’t addressing the problem in the right way, argues Stuart Russell, a computer-science professor at the University of California, Berkeley, and the president of the International Association for Safe and Ethical Artificial Intelligence.

“It’s like saying we’re driving toward the cliff at 60 miles per hour and we’re going to drive toward it at 40 miles per hour instead, and everything will be OK,” he says.

Russell and his peers have proposed that AI companies should have to meet the same standards that govern other areas of everyday life, from air travel and buildings to food and drugs. They highlight the “behavioral red lines” AI should not be allowed to cross. Breaking into other computer systems, stealing information or advising terrorists on how to build biological weapons are all illegal for a human to do, and should be illegal for companies’ AIs as well, he argues.

The challenge for AI companies in such a proposal, he adds, is that it would be a de facto ban on today’s advanced AI systems, since the companies behind them don’t know how to make them respect such boundaries all of the time.

Others have proposed something like the Food and Drug Administration, but for AI, but setting up a new agency has so far been a nonstarter in Congress. And some prominent voices in tech have said such a structure would give up America’s AI edge to China.

Given the bipartisan groundswell of support for curbing AI companies and their creations, however, that may soon change.

“The tech industry has had this mantra for decades that regulation is bad,” says Russell. “They don’t accept the liability for any harm, and they hide behind free speech. That, I think, has to change.”

One Man’s Quest to Reunite With His First Love: A 1971 VW Bug

Jeff Siegrist couldn’t take his mind off the car he sold in 1996. So he set out to track it down.

Could fears of an AI apocalypse be distracting us from the dangers already here? Experts debate whether regulation should focus on speculative existential threats or present-day harms, including cyberattacks, weapons and unsafe autonomous agents. Read more via the link in bio.