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"In the short term, generative AI will replace a lot of people because productivity increases while demand stays the same due to inertia. In the long term, the creation of new jobs compensates for the loss of old ones, resulting in a net positive outcome for humans who leave behind jobs no one wants to do. The most important aspect of any technological revolution is the transition from before to after. Timing and location matters: older people have a harder time reinventing themselves into a new trade or craft. Poor people and poor countries have less margin to react to a wave of unemployment. Digital automation is quicker and more aggressive than physical automation because it bypasses logistical constraints-while ChatGPT can be infinitely cloned, a metallic robot cannot. Writing and painting won't die because people care about the human factor first and foremost; there are already a lot of books we can't possibly read in one lifetime so we select them as a function of who's the author. Even if you hate OpenAI and ChatGPT for being responsible for the lack of job postings, I recommend you ally with them for now; learn to use ChatGPT before it's too late to keep your options open. Companies are choosing to reduce costs over increasing output because the sectors where generative AI is useful can't artificially increase demand in parallel to productivity. (Who needs more online content?) Our generation is reasonably angry at generative AI and will bravely fight it. Still, our offspring-and theirs-will be grateful for a transformed world whose painful transformation they didn't have to endure. Certifiable human-made creative output will reduce its quantity but multiply its value in the next years because demand specific for it will grow; automation can mimic 99% of what we do but never reaches 100%. The maxim "AI won't take your job, a person using AI will; yes, you using AI will replace yourself not using it" applies more in the long term than the

"Do the potential paying customers for these large models add up to enough money to keep the servers on? That's the 13 trillion dollar question, and the answer is the difference between WorldCom and Enron, or dotcoms and cryptocurrency. Though I don't have a certain answer to this question, I am skeptical. AI decision support is potentially valuable to practitioners. Accountants might value an AI tool's ability to draft a tax return. Radiologists might value the AI's guess about whether an X-ray suggests a cancerous mass. But with AIs' tendency to "hallucinate" and confabulate, there's an increasing recognition that these AI judgments require a "human in the loop" to carefully review their judgments. In other words, an AI-supported radiologist should spend exactly the same amount of time considering your X-ray, and then see if the AI agrees with their judgment, and, if not, they should take a closer look. AI should make radiology more expensive, in order to make it more accurate. But that's not the AI business model. AI pitchmen are explicit on this score: The purpose of AI, the source of its value, is its capacity to increase productivity, which is to say, it should allow workers to do more, which will allow their bosses to fire some of them, or get each one to do more work in the same time, or both. The entire investor case for AI is "companies will buy our products so they can do more with less." It's not "business custom­ers will buy our products so their products will cost more to make, but will be of higher quality.""

"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

"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."

"A promotional poster for the second season of Loki on Disney Plus has sparked controversy amongst professional designers following claims that it was at least partially created using generative AI. Illustrator Katria Raden flagged the image on X (formerly Twitter) last week, claiming that the image of the spiraling clock in the background "is giving all the AI telltale signs, like things randomly turning into meaningless squiggles" - a reference to the artifacts sometimes left behind by AI-image generators. The creative community is concerned that AI image generators are being trained on their work without consent and could be used to replace human artists. Disney previously received backlash regarding its use of generative AI in another Marvel series, Secret Invasion, despite the studio insisting that using AI tools didn't reduce roles for real designers on the project."

"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"."

"Now, as more people use AI to produce and publish content, an obvious question arises: What happens as AI-generated content proliferates around the internet, and AI models begin to train on it, instead of on primarily human-generated content? A group of researchers from the UK and Canada have looked into this very problem and recently published a paper on their work in the open access journal arXiv. What they found is worrisome for current generative AI technology and its future: "We find that use of model-generated content in training causes irreversible defects in the resulting models.""

The British-Canadian computer scientist often touted as a "godfather" of artificial intelligence has shortened the odds of AI wiping out humanity over the next three decades, warning the pace of change in the technology is "much faster" than expected. Prof Geoffrey Hinton, who this year was awarded the Nobel prize in physics for his work in AI, said there was a "10% to 20%" chance that AI would lead to human extinction within the next three decades. Previously Hinton had said there was a 10% chance of the technology triggering a catastrophic outcome for humanity.

"Needless to say, AI-generated accidents and AI-generated artworks are viewed differently under the law. As far as art goes, be it a video, an image, a script, a song, or any medium that the AI can work with, the (US) law is pretty straightforward - According to copyright law, only humans can be granted copyrights. If it's created by AI, nobody can claim ownership of it or copyright it."

GREAT ARTICLE ON AI "There is some debate about how soon AI will reach human-level general intelligence-the median year on a survey of hundreds of scientists about when they believed we'd be more likely than not to have reached AGI was 204012-that's only 25 years from now, which doesn't sound that huge until you consider that many of the thinkers in this field think it's likely that the progression from AGI to ASI happens very quickly. Like-this could happen: It takes decades for the first AI system to reach low-level general intelligence, but it finally happens. A computer is able understand the world around it as well as a human four-year-old. Suddenly, within an hour of hitting that milestone, the system pumps out the grand theory of physics that unifies general relativity and quantum mechanics, something no human has been able to definitively do. 90 minutes after that, the AI has become an ASI, 170,000 times more intelligent than a human."

"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."

"With the release of artificial intelligence (AI) video generation products like Sora and Luma, we're on the verge of a flood of AI-generated video content, and policymakers, public figures and software engineers are already warning about a deluge of deepfakes. Now it seems that AI itself might be our best defense against AI fakery after an algorithm has identified telltale markers of AI videos with over 98% accuracy."

"The new AI Index report notes that in 2023, AI still struggled with complex cognitive tasks like advanced math problem-solving and visual commonsense reasoning. However, 'struggled' here might be misleading; it certainly doesn't mean AI did badly. Performance on MATH, a dataset of 12,500 challenging competition-level math problems, improved dramatically in the two years since its introduction. In 2021, AI systems could solve only 6.9% of problems. By contrast, in 2023, a GPT-4-based model solved 84.3%. The human baseline is 90%. "

"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."

"Open AI researchers said that while it was "impossible to reliably detect all AI-written text", good classifiers could pick up signs that text was written by AI. The tool could be useful in cases where AI was used for "academic dishonesty" and when AI chatbots were positioned as humans, they said."

"Researchers involved in a recent study trained an artificial intelligence (AI) model to diagnose type 2 diabetes in patients after six to 10 seconds of listening to their voice. Canadian medical researchers trained the machine-learning AI to recognise 14 vocal differences in the voice of someone with type 2 diabetes compared to someone without diabetes. The auditory features that the AI focussed on included slight changes in pitch and intensity, which human ears cannot distinguish. This was then paired with basic health data gathered by the researchers, such as age, sex, height and weight. Researchers believe that the AI model will drastically lower the cost for people with diabetes to be diagnosed."

"One of the key features introduced is a "Correction" capability in Azure AI Content Safety. This tool aims to address the problem of AI hallucinations - instances where AI models generate false or misleading information. "When we detect there's a mismatch between the grounding context and the response… we give that information back to the AI system," Bird explained. "With that additional information, it's usually able to do better the second try.""

"The model is AI-generated, a digital rendering of a human being that will start appearing on Levi's e-commerce website later this year. The brand teamed with LaLaLand.ai, a digital studio that makes customized AI models for companies like Calvin Klein and Tommy Hilfiger, to dream up this avatar. Amy Gershkoff Bolles, Levi's global head of digital and emerging technology strategy, announced the model's debut at a Business of Fashion event in March. AI models will not completely replace the humans, she said, but will serve as a "supplement" intended to aid in the brand's representation of various sizes, skin tones and ages."

"He's right to be annoyed - these tracks are a violation of an artist's creativity and personhood - and the fakes are noticeably more sophisticated than those from a few years ago, when Jay-Z was made to rap Shakespeare (this is the kind of humour beloved of AI dorks). The tech will continue to improve to the point where the differences become indistinguishable. Perhaps lazy artists will soon use AI to generate their latest album, not so much phoning it in as texting it. AI composes its music by regurgitating things it's been trained to listen to in vast song databases, and that's not so different than the way human-composed pop music is recombined from prior influences. Producers, engineers, lyricists and all the other people who work behind a star could be usurped or at least have their value driven down by cheap AI tools."

"Seeing an opportunity, Franklin decided to take advantage. On 9 July, the company said that it would begin to support digital employees as part of its platform and treat them like any other employee. "Today Lattice is making AI history," Franklin pronounced. "We will be the first to give digital workers official employee records in Lattice. Digital workers will be securely onboarded, trained and assigned goals, performance metrics, appropriate systems access and even a manager. Just as any person would be." The pushback was swift - and, in many cases, brutal, particularly on LinkedIn, which is generally not known for its savage engagement like X (formerly known as Twitter). "This strategy and messaging misses the mark in a big way, and I say that as someone building an AI company," said Sawyer Middeleer, an executive at a firm that uses AI to help with sales research, on LinkedIn. "Treating AI agents as employees disrespects the humanity of your real employees. Worse, it implies that you view humans simply as 'resources' to be optimized and measured against machines. It's the exact opposite of a work environment designed to elevate the people who contribute to it.""