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"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.""

"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 president of Baidu, Ya-Qin Zhang, said in a statement: "As AI technology keeps advancing and the application of AI expands, we recognise the importance of joining the global discussion around the future of AI. Ensuring AI's safety, fairness and transparency should not be an afterthought but rather highly considered at the onset of every project or system we build.""

""We are seeing deep fakes being used all the time, and the technology is going to allow still images, but ultimately also video images, to be synthesised [more easily] by bad actors," he says. DALL-E has content policy rules in place that prohibit bullying, harassment, the creation of sexual or political content, or creating images of people without their consent. And while Open AI has limited the number of people who can sign up to DALL-E, its lower-grade replica, DALL-E mini, is open access, meaning people can produce anything they want."

"Further, human intelligence is the lever that we have used for millennia to create the world we live in today: science, technology, math, physics, chemistry, medicine, energy, construction, transportation, communication, art, music, culture, philosophy, ethics, morality. Without the application of intelligence on all these domains, we would all still be living in mud huts, scratching out a meager existence of subsistence farming. Instead we have used our intelligence to raise our standard of living on the order of 10,000X over the last 4,000 years. What AI offers us is the opportunity to profoundly augment human intelligence to make all of these outcomes of intelligence - and many others, from the creation of new medicines to ways to solve climate change to technologies to reach the stars - much, much better from here."

"Despite Neville describing his use of AI technology as a "modern storytelling technique", critics voiced concerns on social media over the unannounced use of a "deepfake" voice to say sentences that Bourdain never spoke. Among those upset with the use of AI was Bourdain's ex-wife Ottavia Bourdain. She disputed Neville's claims that he had received her blessing to use the artificial technology, tweeting: "I certainly was NOT the one who said Tony would have been cool with that.""

" A new AI pair programmer that helps you write better code. It helps you quickly discover alternative ways to solve problems, write tests, and explore new APIs without having to tediously tailor a search for answers on the internet. As you type, it adapts to the way you write code - to help you complete your work faster. In other words, Copilot will sit on your computer and do a chunk of your coding work for you. There's a long-running joke in the coding community that a substantial portion of the actual work of programming is searching online for people who've solved the same problems as you, and copying their code into your program. Well, now there's an AI that will do that part for you."

"The reason to look at humans is because there are certain things that humans do much better than deep-learning systems. That doesn't mean humans will ultimately be the right model. We want systems that have some properties of computers and some properties that have been borrowed from people. We don't want our AI systems to have bad memory just because people do. But since people are the only model of a system that can develop a deep understanding of something-literally the only model we've got-we need to take that model seriously."

"One great way to tell the difference is to ask AI recruiting companies what they use artificial intelligence, machine learning and/or deep learning for. Hopefully the hiring firm can what it's using the new technology for and not just that it is. If not it's time to dig a bit deeper."

"Beginning in 2017, I did a project with artist Trevor Paglen to look at how people were being labelled. We found horrifying classificatory terms that were misogynist, racist, ableist, and judgmental in the extreme. Pictures of people were being matched to words like kleptomaniac, alcoholic, bad person, closet queen, call girl, slut, drug addict and far more I cannot say here. ImageNet has now removed many of the obviously problematic people categories - certainly an improvement - however, the problem persists because these training sets still circulate on torrent sites [where files are shared between peers]."

"In this future, teachers assisted in marking and lesson planning by LLMs would be left with more much-needed time to focus on other elements of their work. However, in a bid to cut costs, the "teaching" of lessons could also be delegated to machines, robbing teachers and students of human interaction. "Of course, that will be for the less well-off students," Luckin says. "The more well-off students will still have lots of lovely one-to-one human interactions, alongside some very smartly integrated AI." Luckin instead advocates a future in which technology eases teachers' workloads but does not disrupt their pastoral care - or disproportionately affect students in poorer areas. "That human interaction is something to be cherished, not thrown out," she says."

"As such, there are certainly some sinister ways technology like this could be used-and the faces don't need to be attractive, they just need to look real. Any circumstances where it would be useful to have fake people-like profile photos for dummy social media accounts used to manipulate online discourse-are a ready target for technological treachery."

"That is why we must demand transparency here, especially in the case of technology that uses human-like interfaces such as language. For any automated system, we need to know what it was trained to do, what training data was used, who chose that data and for what purpose. In the words of AI researchers Timnit Gebru and Margaret Mitchell, mimicking human behaviour is a "bright line" - a clear boundary not to be crossed - in computer software development. We treat interactions with things we perceive as human or human-like differently. With systems such as LaMDA we see their potential perils and the urgent need to design systems in ways that don't abuse our empathy or trust."

"The intriguing echo of Eliza in thinking about ChatGPT is that people regard it as magical even though they know how it works - as a "stochastic parrot" (in the words of Timnit Gebru, a well-known researcher) or as a machine for "hi-tech plagiarism" (Noam Chomsky). But actually we do not know the half of it yet - not the CO2 emissions incurred in training its underlying language model or the carbon footprint of all those delighted interactions people are having with it. Or, pace Chomsky, that the technology only exists because of its unauthorised appropriation of the creative work of millions of people that just happened to be lying around on the web? What's the business model behind these tools? And so on. Answer: we don't know."

"On inbuilt bias in algorithms, Sharkey said: "There are so many biases happening now, from job interviews to welfare to determining who should get bail and who should go to jail. It is quite clear that we really have to stop using decision algorithms, and I am someone who has always been very light on regulation and always believed that it stifles innovation."

"In October 2016, algorithms reacted to negative news headlines about Brexit negotiations by sending the pound down 6% against the dollar in under two minutes, before recovering almost immediately. Knowing which particular headline, or which particular algorithm, caused the crash is next to impossible. When one haywire algorithm started placing and cancelling orders that ate up 4% of all traffic in US stocks in October 2012, one commentator was moved to comment wryly that "the motive of the algorithm is still unclear"."

"His team trained a machine learning algorithm to spot words and phrases associated with bullying on social media site AskFM, which allows users to ask and answer questions. It managed to detect and block almost two-thirds of insults within almost 114,000 posts in English and was more accurate than a simple keyword search. Still, it did struggle with sarcastic remarks."

"Robots, artificial intelligence and smart speakers will ease the burden on doctors and give them more time with patients, according to an NHS report on the pending technological "revolution" in healthcare. Developments in the ability to sequence individuals' genomes - the entirety of their genetic data - will also spur on advances, according to the review published on Monday."

"With 850 million children worldwide shut out of schools, tech evangelists claim now is the time for AI education. But as the technology's power grows, so too do the dangers that come with it"

"Robots have been slow to appear because each one requires a rare confluence of market, task, technology, and innovation. (And luck. I only described some of the things that nearly killed Roomba.) But as technology advances and costs decline, the toolbox for robot designers constantly expands. Thus, more types of robots will cross the threshold of economic viability. Still, we can expect one constant. Each new, successful robot will represent a minimum-the simplest, lowest-cost solution to a problem people want solved. The growing set of tools that let us attack ever more interesting problems make this an exciting time to practice robotics."