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"Company emails that she provided to NPR show her employer believed the tracking software would improve the team's productivity and efficiency while everyone was working from home."

"Employers argue they make considerable savings on real estate when workers shift from office to home work. However, these savings result from passing costs on to workers. Unless employees are fully compensated, this could become a variant of what urban theorist Andy Merrifield calls parasitic capitalism, whereby corporate profits increasingly rely on extracting value from the public - and now personal - realm, rather than on generating new value."

""There's sort of an emerging sense behind the scenes of executives saying, 'This is not going to be sustainable,'" said Laszlo Bock, chief executive of human-resources startup Humu and the former HR chief at Google. No CEO should be surprised that the early productivity gains companies witnessed as remote work took hold have peaked and leveled off, he adds, because workers left offices in March armed with laptops and a sense of doom."

""Often the problem is that the topic itself is unethical," said Gemma Galdon Clavell, an independent tech ethicist who has evaluated many Horizon 2020 security research projects and worked as a partner on more than a dozen. "Some topics encourage partners to develop biometric tech that can work from afar, and so consent is not possible - this is what concerns me." One project aiming to develop such technology refers to it as "unobtrusive person identification" that can be used on people as they cross borders. ¨If we're talking about developing technology that people don't know is being used," said Galdon Clavell, "how can you make that ethical?" "

"They then analysed how diverse the individuals' work was at different points in their careers. This was assessed using an artificial intelligence system that was trained, in the case of art, to "recognise" different styles by features such as the brush strokes, shapes and objects in a piece, while in the case of film, it was trained to classify a director's work based on plot and cast information. For science, the system identified different research topics based on the papers cited within a researcher's publications."

"Remote surveillance software like Sneek, also known as "tattleware" or "bossware", represented something of a niche market pre-Covid. But that all changed in March 2020, as employers scrambled to pull together work-from-home policies out of thin air. In April last year, Google queries for "remote monitoring" were up 212% year-on-year; by April this year, they'd continued to surge by another 243%."

"Alex Naka, a data scientist at a biotech firm who signed up to test Copilot, says the program can be very helpful, and it has changed the way he works. "It lets me spend less time jumping to the browser to look up API docs or examples on Stack Overflow," he says. "It does feel a little like my work has shifted from being a generator of code to being a discriminator of it.""

"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."

"There's a similar problem in artificial intelligence: The people who develop AI are increasingly having problems explaining how it works and determining why it has the outputs it has. Deep neural networks (DNN)-made up of layers and layers of processing systems trained on human-created data to mimic the neural networks of our brains-often seem to mirror not just human intelligence but also human inexplicability."

"The post sparked a debate in the comments about the ethics of fine-tuning an AI on the work of a specific living artist, even as new fine-tuned models are posted daily. The most-upvoted comment asked, "Whether it's legal or not, how do you think this artist feels now that thousands of people can now copy her style of works almost exactly?""

"Musicians are therefore worried - about being made to perform material they otherwise wouldn't, or being usurped by a fantasy. "I can't help but think that I can be easily replaced," says Flora Rose, a singer-songwriter on TikTok. "I'm spending months crafting my debut EP, [and meanwhile] people can make tracks in one click." When it comes to the arts, AI tends to provoke horror or ridicule - as when an AI photograph won a major photography competition, or when ChatGPT declared young adult weepie The Fault in Our Stars "one of the best books of all time". In February, the lawyer behind a lawsuit on behalf of visual artists whose work was being used to generate AI art called any generative image "an infringing derivative work"."

"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."

"Some experts see platforms like Appen as a new form of data colonialism, says Saiph Savage, director of the Civic AI lab at Northeastern University. "Workers in Latin America are labeling images, and those labeled images are going to feed into AI that will be used in the Global North," she says. "While it might be creating new types of jobs, it's not completely clear how fulfilling these types of jobs are for the workers in the region." Due to the ever moving goal posts of AI, workers are in a constant race against the technology, says Schmidt. "One workforce is trained to three-dimensionally place bounding boxes around cars very precisely, and suddenly it's about figuring out if a large language model has given an appropriate answer," he says, regarding the industry's shift from self-driving cars to chatbots. Thus, niche labeling skills have a "very short half-life." "From the clients' perspective, the invisibility of the workers in microtasking is not a bug but a feature," says Schmidt. Economically, because the tasks are so small, it's more feasible to deal with contractors as a crowd instead of individuals. This creates an industry of irregular labor with no face-to-face resolution for disputes if, say, a client deems their answers inaccurate or wages are withheld. The workers WIRED spoke to say it's not low fees but the way platforms pay them that's the key issue. "I don't like the uncertainty of not knowing when an assignment will come out, as it forces us to be near the computer all day long," says Fuentes, who would like to see additional compensation for time spent waiting in front of her screen. Mutmain, 18, from Pakistan, who asked not to use his surname, echoes this. He says he joined Appen at 15, using a family member's ID, and works from 8 am to 6 pm, and another shift from 2 am to 6 am. "I need to stick to these platforms at all times, so that I don't lose work," he says, but he struggles to earn more than $50

"What's fascinating about all this is how much of it comes down, not to finance or technology, but to people and what they know. In that sense the FT's deep dive into TSMC's travails reminded me of a striking piece of research conducted decades ago by the philosopher of science Harry Collins when he was a PhD student. Collins was interested in how knowledge gets transferred and intrigued by a particular piece of technology, the TEA laser. This was a device that was comprehensively documented in the physics literature but which research laboratories were unable to replicate. What Collins discovered was that "nobody could make the laser work if they hadn't spent time in a laboratory that already had a working laser. There was very good information in the journals about how to build such a laser. But anybody who tried to put one together using written articles failed. They had something that looked like a laser on their bench, but it wouldn't lase.""

"ow, legal redress is all very well, but it's usually beyond the resources of working artists. And lawsuits are almost always retrospective, after the damage has been done. It's sometimes better, as in rugby, to "get your retaliation in first". Which is why the most interesting news of the week was that a team of researchers at the University of Chicago have developed a tool to enable artists to fight back against permissionless appropriation of their work by corporations. Appropriately, it's called Nightshade and it "lets artists add invisible changes to the pixels in their art before they upload it online so that if it's scraped into an AI training set, it can cause the resulting model to break in chaotic and unpredictable ways" - dogs become cats, cars become cows, and who knows what else? (Boris Johnson becoming piglet, with added grease perhaps?) It's a new kind of magic. And the good news is that corporations might find it black. Or even deadly."

"In early December, Musk called ChatGPT "scary good" and warned, "We are not far from dangerously strong AI." But Altman has been warning the public just as much, if not more, even as he presses ahead with OpenAI's work. Last month, he worried about "how people of the future will view us" in a series of tweets. "We also need enough time for our institutions to figure out what to do," he wrote. "Regulation will be critical and will take time to figure out…having time to understand what's happening, how people want to use these tools, and how society can co-evolve is critical.""

"All of this probably means I should be worried about recent trends in artificial intelligence, which is encroaching on voice-over work in a manner similar to how it threatens the labour of visual artists and writers-both financially and ethically. The creep is only just beginning, with dubbing companies training software to replace human actors and tech companies introducing digital audiobook narration. But AI poses a threat to work opportunities across the board by giving producers the tools to recreate their favourite voices on demand, without the performer's knowledge or consent and without additional compensation. It's clear that AI will transform the arts sector, and the voice-over industry offers an early, unsettling model for what this future may look like."

"During a Q&A in September 2015, Zuckerberg mentioned that Facebook was working on a "dislike" button. "I think people have asked about the dislike button for many years," he said, adding that Facebook had been working on the feature for awhile and wanted to implement it in a way that didn't feel like you were down-voting a post. "

"Ultimately, he suggests, each user would have their own "large language model" (LLM), the underlying technology of services such as ChatGPT, which would be trained on their own speech and behaviour patterns, to let them generate extremely personalised responses to queries and requests. Such systems could be a natural progression from AI tools that already exist today. Services such as Gmail can summarise and suggest replies to emails based on previous messages, while Microsoft Teams will transcribe and summarise video conferences, automatically generating a to-do list from the contents."

"In one activity, my students drafted a paragraph in class, fed their work to ChatGPT with a revision prompt, and then compared the output with their original writing. However, these types of comparative analyses failed because most of my students were not developed enough as writers to analyze the subtleties of meaning or evaluate style. "It makes my writing look fancy," one PhD student protested when I pointed to weaknesses in AI-revised text. My students also relied heavily on AI-powered paraphrasing tools such as Quillbot. Paraphrasing well, like drafting original research, is a process of deepening understanding. Recent high-profile examples of "duplicative language" are a reminder that paraphrasing is hard work. It is not surprising, then, that many students are tempted by AI-powered paraphrasing tools. These technologies, however, often result in inconsistent writing style, do not always help students avoid plagiarism, and allow the writer to gloss over understanding. Online paraphrasing tools are useful only when students have already developed a deep knowledge of the craft of writing."