‘Walking Europe’s Last Wilderness’ Review: A Carpathian Ramble
Rising along the line where eastern and western Europe divide, a forested mountain range is home to shepherds, villages and plenty of bears.
Rising along the line where eastern and western Europe divide, a forested mountain range is home to shepherds, villages and plenty of bears.
The Carpathian Mountains are a horseshoe-shaped range that arcs from central to southeastern Europe. From their western edge in Austria and the Czech Republic, the Carpathians rise clockwise through Slovakia and southern Poland, curve around the Hungarian plains and through western Ukraine, run south into Romania, then turn back westward and finally protrude into northern Serbia. There are wild patches in Europe’s other major ranges, but the Carpathians have forests where the Alps have ski resorts and brown bears where the Pyrenees have the microstate of Andorra. The Carpathians are the last wild place in a crowded continent.
The Carpathians, Nick Thorpe writes in “Walking Europe’s Last Wilderness,” are the “geographical center of Europe.” Their peaks and ridges form the watershed between the Baltic Sea to the north and the Black Sea to the southeast. As geography shapes history and history shapes peoples, the mountains are a political “fault line between East and West.” Once contained within the Austro-Hungarian Empire, the Carpathians now curve through six European Union states, one candidate state (Serbia) and Ukraine, whose future is uncertain.
The cover art of “Walking Europe’s Last Wilderness” evokes John Craxton’s designs for Patrick Leigh Fermor’s travelogues “A Time of Gifts” (1977) and “Between the Woods and the Water” (1986). Though Mr. Thorpe describes the enduring exoticism of hospitable huts, historical grudges, handmade goat cheese and homebrewed pálinka fruit spirits, this is not a romanticizing epic from a lost era. Mr. Thorpe is a hiker and camper, and always ready to go barefoot in the meadows, but he lives in Budapest, one of the cities of the plains that surround the Carpathians. A BBC reporter, he launched a series of episodic explorations between 2018 and 2024. He has compiled a richly textured report on an ancient terrain that is being remade into a new political and economic landscape.
The nation-states of the region were created in the 19th and early 20th centuries by “unraveling the complex web of religious, cultural and linguistic threads that characterized Europe.” The nation-builders suppressed “local dialects, vernaculars and identities” and then the Soviets suppressed the nations. The mountains still hide the remnants of the peoples who neither attained statehood nor succumbed: Liptos, Lemkos, Boykos, Hutsuls, Bukovinians, Szeklers, Ruthenians. The revival of the nation-states and their economies after the Cold War threatens to erase the last traces of local identity.
Samo Hríbik, a shepherd in Slovakia, finds his flock by starlight without the help of a dog and fashions traditional fujara flutes, whose “long, shuddering notes,” Mr. Thorpe writes, suggest “the wind buffeting a thatched roof.” In western Ukraine, the 86-year-old Vasyl Kischuk puts on his traditional white smock and brown hat and demonstrates the trembita , the traditional Hutsul wooden trumpet, and a “deep, mournful sound fills the meadow.”
As memories and traditional crafts are fading, incomers are reviving them. Mr. Thorpe meets brewers, cheesemakers, environmentalists and animal lovers mapping migration corridors for brown bears amid the refugee crisis caused by the Ukraine war. Oreste Del Sol, a Paris-born anarchist who shows Mr. Thorpe around his farm and the local slow-food cheese factory in the Ukrainian village of Nyzhnje Selyshche, tells him that being a shepherd in Ukraine is “illegal, or a-legal.” The production and sale of cheese is unregulated. The cheese, Mr. Thorpe finds, is “magnificent.”
For Slovaks, it is the mountains that matter; their national coat of arms carries three stylized ranges. Hungarians, however, speak of the “Carpathian basin” as their homeland and its ring of mountains as a lost shield against invaders. Romanians, whose country is bisected north-south by the Carpathians’ eastern flank, trace their origins to the Dacians, one of whose ancient tribes, the Carpi, gives the name of the mountains. For all their governments, forestry is big business. There are still “primeval forests” in the Carpathians, untouched by humans. There are many “old-growth” forests that were too remote or located on terrain too steep to be exploited in the past. There are also “buffer zones” such as national parks. But the forestry companies now have modern cutting technology and transport, and satellite imagery.
The bouncy IKEA Pöang chair in Mr. Thorpe’s Budapest home is made from beechwood. Romania has two-thirds of Europe’s old-growth forests and IKEA is “the largest private forest owner in Romania.” On paper, IKEA is a “champion of sustainable forestry.” Environmentalists claim, however, that some of its beechwood is “illegally logged—or, at best, over-logged.” IKEA insists it practices “responsible forest management.” Mr. Thorpe goes to a hilltop near Romania’s border with Ukraine. Google Maps shows it “thickly forested.” Mr. Thorpe finds only stumps and scattered branches.
Romsilva, the state forestry company, manages about two-thirds of Romania’s forests. It is charged with both protecting national parks and exploiting a national asset. According to the Romanian Forestry Inventory, 18 million cubic meters (about 635 million cubic feet) of timber were legally felled annually between 2014 and 2017, but “a further 18 million cubic meters were cut illegally each year.” Between 2010 and 2020, 600 members of the Forestry Guard were assaulted after intervening to stop illegal logging. Six were killed.
When Mr. Thorpe leaves the Slovakian capital of Bratislava, he notices that a “gulf of sheer incomprehension has opened up between the village and the city.” The gulf never narrows. “The mountain people, those born and bred here, don’t do much walking in the mountains,” says Sergiu Frusinoiu, a Romanian working with a mountain rescue group. Romania’s “bear problem” is worsening as humans expand into the mountainous territory of its large carnivores: bears, wolves, lynx and jackals. New roads cut across bear migration routes. New towns increase human-carnivore contact. The bears are learning to see humans as a source of food. The Romanian government will allow “the hunting of nearly 500 bears by the end of 2025.” Foreigners, Germans especially, will pay up to 20,000 euros to kill a big male. But no one can agree how many bears there are in Romania, or whether there are really “too many.”
The mayor of Băile Tușnad has educated his townspeople, spent €10,000 on bear-proof trash cans, and cut down the fruiting apple and plum trees in his town. The bears no longer come into Băile Tușnad but, he says, neither do other Romanian mayors in search of advice. Many politicians and businessmen are deep in corrupt forestry deals. The U.S. and EU’s plans for postwar Ukraine include building a “circular road through the Carpathians” to open the mountains for further development. The oligarchs will build ski resorts “where the playboys and playgirls of the new Ukraine will glide effortlessly at high speed, while their brothers, or uncles, sit bitterly at home in wheelchairs.” Old-growth forests make new money, and slow food comes second to a quick buck.
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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.
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.”