#Fauxtomation#Marketing#SelfDrivingCars#AI : "Rather than getting angry with marketers for tricking them, reporters are ventriloquized into repeating the marketing claim that these aren't lies, they're premature truths. Sure, today these are faked, but once the product is refined, the fakery will no longer be required.
This must be the kinds of Magic Underpants Gnomery the credulous press engaged in during the jetpack days: "Sure, a 21-second rocket belt is totally useless for anything except wowing county fair yokels – but once they figure out how to fit an order of magnitude more high-explosive onto that guy's back, this thing will really take off!"
The AI version of this is that if we just keep throwing orders of magnitude more training data and compute at the stochastic parrot, it will eventually come to life and become our superintelligent, omnipotent techno-genie. In other words, if we just keep breeding these horses to run faster and faster, eventually one of our prize mares will give birth to a locomotive:"
#AI#GenerativeAI#HumanInTheLoop#GhostWork#Fauxtomation: "The human in the loop isn't just being asked to spot mistakes – they're being actively deceived. The AI isn't merely wrong, it's constructing a subtle "what's wrong with this picture"-style puzzle. Not just one such puzzle, either: millions of them, at speed, which must be solved by the human in the loop, who must remain perfectly vigilant for things that are, by definition, almost totally unnoticeable.
This is a special new torment for reverse centaurs – and a significant problem for AI companies hoping to accumulate and keep enough high-value, high-stakes customers on their books to weather the coming trough of disillusionment.
This is pretty grim, but it gets grimmer. AI companies have argued that they have a third line of business, a way to make money for their customers beyond automation's gifts to their payrolls: they claim that they can perform difficult scientific tasks at superhuman speed, producing billion-dollar insights (new materials, new drugs, new proteins) at unimaginable speed.
However, these claims – credulously amplified by the non-technical press – keep on shattering when they are tested by experts who understand the esoteric domains in which AI is said to have an unbeatable advantage. For example, Google claimed that its Deepmind AI had discovered "millions of new materials," "equivalent to nearly 800 years’ worth of knowledge," constituting "an order-of-magnitude expansion in stable materials known to humanity":"
#AI#Automation#Work#GhostWork#Fauxtomation: "As anthropologist Lilly Irani observes, labor is not replaced by machines, it’s merely displaced. While stocks surge upon restructuring, few companies achieve this promise of savings and profitability, and “bullshit jobs” soar.
The story of AI distracts us from these familiar unpleasant scenes. Instead, we envision a glistening “future of work” in which we are all miraculously more efficient, our workplaces are populated with relentlessly pleasant robots, and expert automated agents fulfill our every command. Pundits talk loftily about the “ethics of AI” as if it’s a technical question of ironing out its biases or building BB-8 instead of The Terminator.
But the future of work is not a technology: it’s an arrangement. An arrangement of people, capital, and workers that moves jobs from where they are expensive and highly-paid, to where they can be cheap and menial. “AI” is a powerful decoy, lest we start thinking about where those jobs have already gone – offshore – and who moved them there in the first place. Because robots aren’t “taking our jobs” – people are.
#AI#GenerativeAI#Globalization#Fauxtomation#LowWages: "Globalization is key to maintaining the guy-in-a-robot-suit phenomenon. Globalization gives AI pitchmen access to millions of low-waged workers who can pretend to be software programs, allowing us to pretend to have transcended the capitalism's exploitation trap. This is also a very old pattern – just a couple decades after the Mechanical Turk toured Europe, Thomas Jefferson returned from the continent with the dumbwaiter. Jefferson refined and installed these marvels, announcing to his dinner guests that they allowed him to replace his "servants" (that is, his slaves). Dumbwaiters don't replace slaves, of course – they just keep them out of sight:"
#AI#Fauxtomation#Podcasts: "The estate of George Carlin has filed a federal lawsuit against the comedy podcast Dudesy for an hour-long comedy special sold as an AI-generated impression of the late comedian. But a representative for one of the podcast hosts behind the special now admits that it was actually written by a human.
In the lawsuit, filed by Carlin manager Jerold Hamza in a California district court, the Carlin estate points out that the special, "George Carlin: I'm Glad I'm Dead," (which was set to "private" on YouTube shortly after the lawsuit was filed) presents itself as being created by an AI trained on decades worth of Carlin's material. That training would, by definition, involve making "unauthorized copies" of "Carlin's original, copyrighted routines" without permission in order "to fabricate a semblance of Carlin’s voice and generate a Carlin stand-up comedy routine," according to the lawsuit.
"Defendants’ AI-generated 'George Carlin Special' is not a creative work," the lawsuit reads, in part. "It is a piece of computer-generated click-bait which detracts from the value of Carlin’s comedic works and harms his reputation. It is a casual theft of a great American artist’s work.""
#Automation#Fauxtomation#SelfDrivingCars#Driverless#GM#Cruise: "G.M. has spent an average of $588 million a quarter on Cruise over the past year, a 42 percent increase from a year ago. Each Chevrolet Bolt that Cruise operates costs $150,000 to $200,000, according to a person familiar with its operations.
Half of Cruise’s 400 cars were in San Francisco when the driverless operations were stopped. Those vehicles were supported by a vast operations staff, with 1.5 workers per vehicle. The workers intervened to assist the company’s vehicles every 2.5 to five miles, according to two people familiar with is operations. In other words, they frequently had to do something to remotely control a car after receiving a cellular signal that it was having problems.
To cover its spiraling costs, G.M. will need to inject or raise more funds for the business, said Chris McNally, a financial analyst at Evercore ISI. During a call with analysts in late October, Ms. Barra said G.M. would share its funding plans before the end of the year."
#AI#STS#Fauxtomation: "How can we examine so-called ‘artificial intelligence’ (‘AI’) without turning our backs on the STS tradition that questions both notions of artificiality and intelligence? This special issue attempts a step to the side: Instead of considering ‘AI’ as something that does or does not exist (and then taking a position on its benefits or harms), its ambition is to document, in an empirical and agnostic way, the performances that make, sometimes, ‘AI’ appear or disappear in situation. And it comes out, from this perspective, that 'AI' could be considered a vast commensuration undertaking."
#AI#Fauxtomation#GhostWork: "AI’s development so far has been based on the exploitation of workers and users around the world, performing what anthropologist Mary L. Gray and computational social scientist Siddharth Suri call ghost work. This term refers to the undervalued human labor utilized to develop and maintain the automation of websites and apps. Ghost work is characterized by on-demand, short-term projects or tasks performed globally by precarized workers through platforms like Amazon Mechanical Turk and specialized companies like Sama. These workers, usually vulnerable people from Asia, Latin America, and Africa, are paid less than $2 per hour to generate and label data that trains AI models. Moreover, users who validate algorithmic outputs or help perfect systems usually do it for free. Ghost work is often outsourced, hidden, or rendered invisible by the tech companies who request it. As Noopur Raval argues, we must ask ourselves how and for whom this work is invisible and what happens when workers are finally seen. In light of these questions, we delve into three nuanced layers of invisibility that pervade data work: the unpaid work performed by users, human workers pretending to be AI systems, and the different forms of exploitation of vulnerable communities globally. Finally, we explore potential avenues for not only rendering this labor visible but also transforming the material conditions under which it takes place."
A string of job postings from high-profile training data companies, such as Scale AI and Appen, are recruiting poets, novelists, playwrights, or writers with a PhD or master’s degree. Dozens more seek general annotators with humanities degrees, or years of work experience in literary fields. The listings aren’t limited to English: Some are looking specifically for poets and fiction writers in Hindi and Japanese, as well as writers in languages less represented on the internet.
The companies say contractors will write short stories on a given topic to feed them into AI models. They will also use these workers to provide feedback on the literary quality of their current AI-generated text.
The listings illustrate the often-obscured connection between generative AI’s impressive capabilities and the invisible annotation work that powers them."
#AI#GenerativeAI#Fauxtomation#OpenAI#LLMs#Chatbots: "The magical claim of machine learning is that if you give the computer data, the computer will work out the relations in the data all by itself. Amazing!
In practice, everything in machine learning is incredibly hand-tweaked. Before AI can find patterns in data, all that data has to be tagged, and output that might embarrass the company needs to be filtered.
Commercial AI runs on underpaid workers in English-speaking countries in Africa creating new training data and better responses to queries. It’s a painstaking and laborious process that doesn’t get talked about nearly enough.
The workers do individual disconnected actions all day, every day — so called “tasks” — working for companies like Remotasks, a subsidiary of Scale AI, and doing a huge amount of the work behind OpenAI.
AI doesn’t remove human effort. It just makes it much more alienated."
#AI#Fauxtomation#3DModelling: "An artificial intelligence company, whose founder Forbes included in a 30 Under 30 list recently, promises to use machine learning to convert clients’ 2D illustrations into 3D models. In reality the company, called Kaedim, uses human artists for “quality control.” According to two sources with knowledge of the process interviewed by 404 Media, at one point, Kaedim often used human artists to make the models. One of the sources said workers at one point produced the 3D design wholecloth themselves without the help of machine learning at all.
The news pulls back the curtain on a hyped startup and is an example of how AI companies can sometimes overstate the capabilities of their technology. Like other AI startups, Kaedim wants to use AI to do tedious labor that is currently being done by humans. In this case, 3D modeling, a time consuming job that video game companies are already outsourcing to studios in countries like China."
Ensuring that the response is well-sourced and based on evidence, however, falls to thousands of outside contractors from companies including Appen Ltd. and Accenture Plc, who can make as little as $14 an hour and labor with minimal training under frenzied deadlines, according to several contractors, who declined to be named for fear of losing their jobs.
The contractors are the invisible backend of the generative AI boom that’s hyped to change everything. Chatbots like Bard use computer intelligence to respond almost instantly to a range of queries spanning all of human knowledge and creativity. But to improve those responses so they can be reliably delivered again and again, tech companies rely on actual people who review the answers, provide feedback on mistakes and weed out any inklings of bias.
It’s an increasingly thankless job. Six current Google contract workers said that as the company entered a AI arms race with rival OpenAI over the past year, the size of their workload and complexity of their tasks increased. Without specific expertise, they were trusted to assess answers in subjects ranging from medication doses to state laws. Documents shared with Bloomberg show convoluted instructions that workers must apply to tasks with deadlines for auditing answers that can be as short as three minutes."