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"Unskilled manual laborers have felt the pressure of automation for a long time - but, increasingly, they're not alone. The last few years have been a bonanza of advances in artificial intelligence. As our software gets smarter, it can tackle harder problems, which means white-collar and pink-collar workers are at risk as well. Here are eight jobs expected to be automated (partially or entirely) in the coming decades. Call Center Employees call-center Telemarketing used to happen in a crowded call center, with a group of representatives cold-calling hundreds of prospects every day. Of those, maybe a few dozen could be persuaded to buy the product in question. Today, the idea is largely the same, but the methods are far more efficient. Many of today's telemarketers are not human. In some cases, as you've probably experienced, there's nothing but a recording on the other end of the line. It may prompt you to "press '1' for more information," but nothing you say has any impact on the call - and, usually, that's clear to you. But in other cases, you may get a sales call and have no idea that you're actually speaking to a computer. Everything you say gets an appropriate response - the voice may even laugh. How is that possible? Well, in some cases, there is a human being on the other side, and they're just pressing buttons on a keyboard to walk you through a pre-recorded but highly interactive marketing pitch. It's a more practical version of those funny soundboards that used to be all the rage for prank calls. Using soundboard-assisted calling - regardless of what it says about the state of human interaction - has the potential to make individual call center employees far more productive: in some cases, a single worker will run two or even three calls at the same time. In the not too distant future, computers will be able to man the phones by themselves. At the intersection of big data, artificial intelligence, and advanced

"The purpose of handing the economy off to the synths is so that we can do the kinds of tasks that every human would wake up in the morning eager to do. There should not be any human doing a task they find a waste of their talent. If it is a job where productivity matters, a human should not be doing it. Productivity is for robots. Humans should be doing the jobs where inefficiency reigns - art, exploration, invention, innovation, small talk, adventure, companionship. All the productive chores should be handled by the billions of AIs we make. Therefore our task right now - as humans - is to make sure that in the following decades as our biological numbers start to shrink on this planet, that we can repopulate it with a sufficient number of synthetic agents, bots, and robots with sufficient intelligence, grit, perseverance, and moral training to take over the economy in time to keep our living standards rising. We are not replacing existing humans with bots, nor are we replacing unborn humans with bots. Rather we are replacing never-to-be-born humans with bots, and the relationship that we have with those synthetic agents and ems, will be highly mutual. We build an economy around their needs, and propelled by their labor, and rewarding their work, but all of this is in service of our own definition of progress and human success."

"First of all, in the short term I agree with arguments that comparative advantage will continue to keep humans relevant and in fact increase their productivity, and may even in some ways level the playing field between humans. As long as AI is only better at 90% of a given job, the other 10% will cause humans to become highly leveraged, increasing compensation and in fact creating a bunch of new human jobs complementing and amplifying what AI is good at, such that the "10%" expands to continue to employ almost everyone. In fact, even if AI can do 100% of things better than humans, but it remains inefficient or expensive at some tasks, or if the resource inputs to humans and AI's are meaningfully different, then the logic of comparative advantage continues to apply. One area humans are likely to maintain a relative (or even absolute) advantage for a significant time is the physical world. Thus, I think that the human economy may continue to make sense even a little past the point where we reach "a country of geniuses in a datacenter"."

"That's why the best systems may come from a combination of AI and human work; we can play to the machine's strengths, Ilievski says. But when we want to compare AI and the human mind, it's important to remember "there is no conclusive research providing evidence that humans and machines approach puzzles in a similar vein", he says. In other words, understanding AI may not give us any direct insight into the mind, or vice versa."

"To start we need a new human right to "cognitive liberty", which would come with an update to other existing human rights to privacy, freedom of thought and self-determination. All told it would protect our freedom of thought and rumination, mental privacy, and self-determination over our brains and mental experiences. It would change the default rules so we have rights around the commodification of our brain data. "

"The specific engineering of ChatGPT has made it quite compelling. But ultimately (at least until it can use outside tools) ChatGPT is "merely" pulling out some "coherent thread of text" from the "statistics of conventional wisdom" that it's accumulated. But it's amazing how human-like the results are. And as I've discussed, this suggests something that's at least scientifically very important: that human language (and the patterns of thinking behind it) are somehow simpler and more "law like" in their structure than we thought. ChatGPT has implicitly discovered it. But we can potentially explicitly expose it, with semantic grammar, computational language, etc."

""As the deceptive capabilities of AI systems become more advanced, the dangers they pose to society will become increasingly serious," said Dr Peter Park, an AI existential safety researcher at MIT and author of the research. Park was prompted to investigate after Meta, which owns Facebook, developed a program called Cicero that performed in the top 10% of human players at the world conquest strategy game Diplomacy. Meta stated that Cicero had been trained to be "largely honest and helpful" and to "never intentionally backstab" its human allies."

"Microsoft researchers said VALL-E 2 was capable of generating "accurate, natural speech in the exact voice of the original speaker, comparable to human performance," in a paper that appeared June 17 on the pre-print server arXiv. In other words, the new AI voice generator is convincing enough to be mistaken for a real person - at least, according to its creators."

"Recent experiments suggest AI peer reviews tend to be surprisingly good, with 82.4% of scientists finding AI peer reviews more useful than at least some of the human reviews they received from on a paper, and other work suggests AI is reasonably good at spotting errors, though not as good as humans, yet. Regardless of how good AI gets, the scientific publishing system was not made to support AI writers writing to AI reviews for AI opinions for papers later summarized by AI. The system is going to break."

"That comment sparked interest and outrage, raising concerns that the kind of AI-generated "slop" that's prominent on Facebook would soon come straight from Meta and disrupt the core utility of social media - fostering human-to-human connection. As users began to sniff out some of Meta's AI accounts this week, the backlash grew, in part because of the way the AI accounts disingenuously described themselves as actual people with racial and sexual identities."

"Uber knows when your phone battery is running low because its app collects that information in order to switch into power-saving mode. But Chen swears Uber would never use that knowledge to gouge you out of more money. "We absolutely don't use that to kind of like push you a higher surge price, but it's an interesting kind of psychological fact of human behavior," Chen said. Uber's surge pricing uses a proprietary algorithm that accounts for how many users are hailing rides in an area at a given time. Customers are apparently less willing to believe that when the multiplier is a round number like 2.0 or 3.0, which seems more like it could have been arbitrarily made up by a human."

"Generally, it questions the advance of computing in the absence of a deeper knowledge of how the human brain perceives the world to be computed. We want computers to have perception, yet we know little about the workings of our own human perception."

"The findings from those examples were striking: overall, those who trusted the accuracy of the AI tools found themselves thinking less critically, while those who trusted the tech less used more critical thought when going back over AI outputs. "The data shows a shift in cognitive effort as knowledge workers increasingly move from task execution to oversight when using GenAI," the researchers wrote. "Surprisingly, while AI can improve efficiency, it may also reduce critical engagement, particularly in routine or lower-stakes tasks in which users simply rely on AI, raising concerns about long-term reliance and diminished independent problem-solving." This isn't enormously surprising. Something we've observed in many domains, from self-driving vehicles to scrutinizing news articles produced by AI, is that humans quickly go on autopilot when they're supposed to be overseeing an automated system, often allowing mistakes to slip past."

"Rather than being "taught" medical knowledge, the AI was asked to learn using unsupervised deep neural networks, known as autoencoders, without being given any medical knowledge. The researchers developed a method for translating the features found by the AI-only numbers initially-into high-resolution images that can be understood by humans."

"And he emphatically doesn't see the process of building an AI image as dehumanised, or even one in which the human is sidelined. "I don't see it as a threat to creativity. For me, it really is setting me free. All the boundaries I had in the past - material boundaries, budgets - no longer matter. And for the first time in history, the older generation has an advantage, because AI is a knowledge accelerator. Two thirds of the prompts are only good if you have knowledge and skills, when you know how photography works, when you know art history. This is something that a 20-year-old can't do.""

""An emotionally intelligent human does not usually claim they can accurately put a label on everything everyone says and tell you this person is currently feeling 80% angry, 18% fearful, and 2% sad," says Edward B Kang, an assistant professor at New York University writing about the intersection of AI and sound. "In fact, that sounds to me like the opposite of what an emotionally intelligent person would say." Adding to this is the notorious problem of AI bias. "Your algorithms are only as good as the training material," Barrett says. "And if your training material is biased in some way, then you are enshrining that bias in code.""

"Cancer diagnosis and management depend upon the extraction of complex information from microscopy images by pathologists, which requires time-consuming expert interpretation prone to human bias. Supervised deep learning approaches have proven powerful, but are inherently limited by the cost and quality of annotations used for training. Therefore, we present Histomorphological Phenotype Learning, a self-supervised methodology requiring no labels and operating via the automatic discovery of discriminatory features in image tiles. Tiles are grouped into morphologically similar clusters which constitute an atlas of histomorphological phenotypes (HP-Atlas), revealing trajectories from benign to malignant tissue via inflammatory and reactive phenotypes. These clusters have distinct features which can be identified using orthogonal methods, linking histologic, molecular and clinical phenotypes. Applied to lung cancer, we show that they align closely with patient survival, with histopathologically recognised tumor types and growth patterns, and with transcriptomic measures of immunophenotype. These properties are maintained in a multi-cancer study."

"As smart as they are, doctors can't compete with the volume of knowledge that a robot can retain. In an effort to join the best of both worlds - human experience with robotic data - a number of companies are developing telemedicine robots that not only allow doctors to reach out to patients miles or continents away, but can offer immediate information and advice that draws from volumes of medical research and case studies. In January the FDA approved the telepresence platform RP-Vita, developed by iRobot and InTouch Health. Now seven hospitals across North America have enlisted the services of RP-Vita, bringing us one step closer to robotics-augmented healthcare."

"The really significant thing about AlphaGo is that it (and its creators) cannot explain its moves. And yet it plays a very difficult game expertly. So it's displaying a capability eerily similar to what we call intuition - "knowledge obtained without conscious reasoning". Up to now, we have regarded that as an exclusively human prerogative. It's what Newton was on about when he wrote "Hypotheses non fingo" in the second edition of his Principia: "I don't make hypotheses," he's saying, "I just know.""

"The piece is meant to be a commentary on the collection and use of private data by tech companies, as Posters explained. "The fact that citizens' data - including intimate knowledge on political leanings, sexuality, psychological traits and personality - are made available to the highest bidder shows that the digital influence industry and its associated architectures pose a risk not only to individual human rights but to our democracies at large.""