Hernando Murcia was the kind of pilot who flew routes others wouldn’t dare. He worked for Avianline Charters, one of the air taxi companies that shuttle people across Colombia’s Amazon region, an expanse of rainforest roughly the size of California. The forest is dark, dense and often treacherous. There are no roads, much less commercial airports, and the meandering rivers teem with predators, including piranhas and anacondas. Violent rebel groups and drug smugglers hide out in the region.
On 1 May 2023, Murcia agreed to pilot a flight from the southern Amazon town of Araracuara to San José del Guaviare, a population centre connected to Colombia’s road network. He was supposed to be carrying representatives of Yauto, a company brokering carbon credits between Indigenous populations and multinational firms, but sometime before takeoff, members of the Colombian military stationed in Araracuara approached Murcia. They told him that there was a change of plans: he needed to evacuate an Indigenous family.
As the family hurried to the rear of the plane, a blue and white Cessna, a local Indigenous leader named Hermán Mendoza clambered up front next to Murcia; he said that he was there to ensure the other passengers arrived at their destination safely. Murcia added everyone’s names to the flight manifest, radioed the information with the plane’s registration number, HK2803, to Colombian air traffic control, then took off.
About 30 minutes into the flight, as the Cessna approached the Colombian department of Caquetá, one of the densest, wettest, most remote corners of the Amazon, its engine failed. Over his radio, Murcia sent a mayday alert. To land, Murcia needed an opening in the landscape below him, but these are exceedingly rare in the Amazon. Air traffic control asked him to confirm his location.
“One hundred and three miles outside San José,” Murcia responded. “I am going to hit water.”
These were the last words air traffic control heard from Murcia. Moments later, radar recorded the Cessna taking a sharp right turn. Then, about 7.50am, it disappeared.
Word of the Cessna’s disappearance spread quickly. By 8.15am, authorities had picked up a distress signal from the plane’s emergency locator transmitter, a device triggered by impact from a crash. The Cessna appeared to be somewhere in an area of about 4 sq km, near a small community called Cachiporro along the Apaporis River.
When a plane crashes in Colombia, the responsibility for finding it normally lies with the Civil Aviation Authority, which will arrange for the military and the air force to dispatch recovery teams. But the vast wilderness and unique dangers of the Amazon meant that it was initially deemed too risky to send anyone on foot. Only the air force was deployed, and it sent surveillance planes over the jungle near Cachiporro, hoping to spot the wreckage or possibly survivors.
Meanwhile, Freddy Ladino, the founder of Avianline Charters, sent up several of his other planes to look for HK2803. But neither Avianline nor the air force saw any sign of the crash: no debris, no smoke, no conspicuous swath cut through the rainforest’s canopy.
Read the rest of this article at: The Guardian
Alan Turing was far from the first to imagine human-like machines. According to legend, 3,500 years ago, Dædalus constructed humanoid statues that were so lifelike that they moved and spoke by themselves.2 Nearly every culture has its own stories of human-like machines, from Yanshi’s leather man described in the ancient Chinese Liezi text to the bronze Talus of the Argonautica and the towering clay Mokkerkalfe of Norse mythology. The word robot first appeared in Karel Čapek’s influential play Rossum’s Universal Robots and derives from the Czech word robota, meaning servitude or work. In fact, in the first drafts of his play, Čapek named them labori until his brother Josef suggested substituting the word robot.3
Of course, it is one thing to tell tales about humanoid machines. It is something else to create robots that do real work. For all our ancestors’ inspiring stories, we are the first generation to build and deploy real robots in large numbers.4 Dozens of companies are working on robots as human-like, if not more so, as those described in the ancient texts. One might say that technology has advanced sufficiently to become indistinguishable from mythology.5
The breakthroughs in robotics depend not merely on more dexterous mechanical hands and legs, and more perceptive synthetic eyes and ears, but also on increasingly human-like artificial intelligence. Powerful AI systems are crossing key thresholds: matching humans in a growing number of fundamental tasks such as image recognition and speech recognition, with applications from autonomous vehicles and medical diagnosis to inventory management and product recommendations.6 AI is appearing in more and more products and processes.7
These breakthroughs are both fascinating and exhilarating. They also have profound economic implications. Just as earlier general-purpose technologies like the steam engine and electricity catalyzed a restructuring of the economy, our own economy is increasingly transformed by AI. A good case can be made that AI is the most general of all general-purpose technologies: after all, if we can solve the puzzle of intelligence, it would help solve many of the other problems in the world. And we are making remarkable progress. In the coming decade, machine intelligence will become increasingly powerful and pervasive. We can expect record wealth creation as a result.
Replicating human capabilities is valuable not only because of its practical potential for reducing the need for human labor, but also because it can help us build more robust and flexible forms of intelligence. Whereas domain-specific technologies can often make rapid progress on narrow tasks, they founder when unexpected problems or unusual circumstances arise. That is where human-like intelligence excels. In addition, HLAI could help us understand more about ourselves. We appreciate and comprehend the human mind better when we work to create an artificial one.
Let’s look more closely at how HLAI could lead to a realignment of economic and political power.
The distributive effects of AI depend on whether it is primarily used to augment human labor or automate and replace it. When AI augments human capabilities, enabling people to do things they never could before, then humans and machines are complements. Complementarity implies that people remain indispensable for value creation and retain bargaining power in labor markets and in political decision-making. In contrast, when AI replicates and automates existing human capabilities, machines become better substitutes for human labor and workers lose economic and political bargaining power. Entrepreneurs and executives who have access to machines with capabilities that replicate those of human for a given task can and often will replace humans in those tasks.
Read the rest of this article at: Stanford Digital Economy Lab
If Ralph Waldo Emerson was right that ‘language is fossil poetry’, then metaphors undoubtedly represent a significant portion of these linguistic remnants. A particularly well-preserved linguistic fossil example is found in the satirical TV show Veep: after successfully giving an interview designed to divert the public’s attention from an embarrassing diplomatic crisis, the US vice-president – portrayed by the outstanding Julia Louis-Dreyfus – comments to her staff: ‘I spewed out so much bullshit, I’m gonna need a mint.’
When used properly, metaphors enhance speech. But correctly dosing the metaphorical spice in the dish of language is no easy task. They ‘must not be far-fetched, or they will be difficult to grasp, nor obvious, or they will have no effect’, as Aristotle already noted nearly 2,500 years ago. For this reason, artists – those skilled enhancers of experience – are generally thought to be the expert users of metaphors, poets and writers in particular.
Unfortunately, it is likely this association with the arts that has given metaphors a second-class reputation among many thinkers. Philosophers, for example, have historically considered it an improper use of language. A version of this thought still holds significant clout in many scientific circles: if what we care about is the precise content of a sentence (as we often do in science) then metaphors are only a distraction. Analogously, if what we care about is determining how nutritious a meal is, its presentation on the plate should make no difference to this judgment – it might even bias us.
Read the rest of this article at: Aeon
In his studio on the east coast of Vancouver Island, the master clockmaker Phil Abernethy is crafting a timepiece that will be calibrated in a manner that no horologist has ever attempted. It won’t show the minutes and hours of an ordinary human day. Instead, his clock will display time as experienced by some of the oldest trees on the planet.
Using techniques he’s honed over a lifetime, Abernethy will machine the gears by hand in traditional materials such as steel and brass. But the pendulum will respond to the forest: When trees grow quickly, the hours will advance more rapidly; more lethargic growth will result in a slower tempo. Over centuries, the long-term fate of the canopy will be registered on a calendar that may deviate from the Gregorian date by decades or more.
Abernethy has been commissioned to fabricate the arboreal clock by the Nevada Museum of Art. Standing 12 feet tall, the clock will be the first physical manifestation of an environmental timekeeping project I have been developing over the past decade. Some of the clocks in the project respond to rivers; Abernethy’s enlists a stand of bristlecone pine trees in Nevada’s Great Basin as living timekeepers.
Fluctuations in the bristlecones’ growth rate, affected by environmental conditions ranging from local rainfall to planetary climate change, will be measured by analyzing the thickness of tree rings in microcores retrieved from the mountain each year. These data will be used to determine the center of gravity for the pendulum, which will swing slower or faster depending on the tree ring thickness. Though the clock face will display time in the usual way, it won’t serve as a mechanism for human planning — a technology to impose order on the environment for our convenience — but rather to pace our lives to match the lived reality of other organisms.
Read the rest of this article at: Noema
Free food, nap rooms, wellness walks, unlimited vacation days: such are the workaday perks of a job in tech. These perks, along with the six- and sometimes seven-figure salaries that accompany them, are, we’ve long been told, well-deserved. Not only are tech workers portrayed as feverishly hardworking, they are the epitome of innovation and productivity.
However, it’s become apparent that they aren’t as productive as we’ve been told to think. Ex-Meta employee Madelyn Machado recently posted a TikTok video claiming that she was getting paid $190,000 a year to do nothing. Another Meta employee, also on TikTok, posted that “Meta was hiring people so that other companies couldn’t have us, and then they were just kind of like hoarding us like Pokémon cards.” Over at Google, a company known to have pioneered the modern tech workplace, one designer complained of spending 40 percent of their time on “the inefficien[cy] overhead of simply working at Google.” Some report spending all day on tasks as simple as changing the color of a website button. Working the bare minimum while waiting for stock to vest is so common that Googlers call it “resting and vesting.”
In an anonymous online poll on how many “focused hours of work” software engineers put in each day, 71 percent of the over four thousand respondents claimed to work six hours a day or less, while 12 percent said they did between one and two hours a day. During the acute phase of the Covid-19 pandemic, it became common for tech workers to capitalize on all this free time by juggling multiple full-time remote jobs. According to the Wall Street Journal, many workers who balance two jobs do not even hit a regular forty-hour workload for both jobs combined. One software engineer reported logging between three and ten hours of actual work per week when working one job, with the rest of his time spent on pointless meetings and pretending to be busy. My own experience supports this trend: toward the end of my five-year tenure as a software engineer for Microsoft, I was working fewer than three hours a day. And of what little code I produced for them, none of it made any real impact on Microsoft’s bottom line—or the world at large.
For much of this century, optimism that technology would make the world a better place fueled the perception that Silicon Valley was the moral alternative to an extractive Wall Street—that it was possible to make money, not at the expense of society but in service of it. In other words, many who joined the industry did so precisely because they thought that their work would be useful. Yet what we’re now seeing is a lot of bullshit. If capitalism is supposed to be efficient and, guided by the invisible hand of the market, eliminate inefficiencies, how is it that the tech industry, the purported cradle of innovation, has become a redoubt of waste and unproductivity?
Read the rest of this article at: The Baffler