DiPLab’s Antonio Casilli was interviewed by journalist Massimo Cerofolini in the show EtaBeta on Radio1 Rai, italian national radio brodcast. Here’s the complete interview. Their conversation revolves around two recent stories, that reveal deeper truths about today’s tech and political landscapes. First, Builder.ai—a company claiming full automation in app development—was exposed as relying on hundreds of human developers in India. It’s another example of tech companies disguising cheap labor as artificial intelligence, a pattern long studied by researchers at DiPLab. Second, how Elon Musk and Donald Trump’s breakup isn’t just a personal feud. It reflects a deeper conflict between two forms of right-wing capitalism: Trump’s old-school, protectionist, real estate-driven model vs. Musk’s futuristic, tech-centered, data-fueled empire. According to Casilli, both are authoritarian and exploitative, but they represent competing visions of power and profit.

DiPLab’s Antonio Casilli was interviewed by Martijn Arets in the WageIndicator Foundation Gig Work Podcast about his latest book Waiting for Robots. The Hired Hands of Automation (University of Chicago Press, 2025). THE MYTH OF AUTOMATION: HOW AI IS AND WILL REMAIN DEPENDENT ON CHEAP HUMAN LABOUR -------------------------------------------------------------------------------- Artificial intelligence (AI) is and will remain dependent on human labour. The people who do the work behind AI systems are often invisible. This carries risks of poor working conditions, low wages and inadequate protection for workers. How does this situation arise, and how can we ensure that the many invisible data workers also benefit from technological developments? For the WageIndicator Foundation’s Gig Work Podcast, I spoke with Professor Antonio Casilli (Institut Polytechnique de Paris), author of the book Waiting for Robots, the Hired Hands of Automation. Listen to this podcast episode on Spotify SCOOBY-DOO IN THE WORLD OF PLATFORM WORK ‘Me and my team are like Scooby-Doo: we travel all over the world investigating mysteries,’ says Casilli. ‘We conduct empirical research into artificial intelligence and how it is produced. Our focus is not on the new possibilities of AI, but on the development process: who is working behind the scenes to make AI possible? His research team is called Diplab, which stands for Digital Platform Labor. They have developed a very broad view of automation. THE MYTH OF AUTOMATION The dream of automating work is not new: Thomas Mortimer, among others, wrote in 1801 about a machine that would be capable of making human labour ‘almost completely superfluous’. ‘Technologists and economists have been looking for ways to make labour more efficient for centuries,’ says Casilli. ‘The industrial revolution saw the emergence of the first machines, such as the steam engine and the Spinning Jenny. Every innovation came with great promises. They would save us many hours of work. But nothing could be further from the truth.’ Many predictions about automation were overstated. Studies between 2013 and 2024 claimed that robots would replace 46-47% of all jobs. Casilli: ‘Organisations such as the OECD and ILO have shown that this is not true. Even with additional crises such as climate change, geopolitical tensions and a pandemic, global unemployment has not risen. In fact, in 2025, people will be working more than ever.’ The problem lies in the methodology used by these researchers, explains the professor. ‘They take a profession and break it down into tasks. If they expect AI to replace 60% of the tasks, they conclude that the job will disappear. But that’s not how it works in practice. Often, employees simply get new tasks.’ INFLUENCE OF PLATFORMISATION According to Casilli, the biggest change in recent years is not automation, but platformisation. Companies such as Uber, Amazon and Meta use huge amounts of data to connect supply and demand and organise work. They also use all this data to train AI systems. For example, they build software such as ChatGPT (the P stands for ‘Pretrained’) and the technology behind self-driving cars. ‘What is often forgotten or ignored is how many people are involved in this,‘ says the researcher. “The promise of AI is that systems can take over human cognitive tasks. But in reality, many so-called ”automatic’ processes depend on human labour. The people who do this work are often invisible and poorly paid.’ This is not a recent phenomenon: Google, for example, has had its own platform, Raterhub, since 2007, where data workers verify search results and thus improve the search engine’s algorithms. Amazon Mechanical Turk, the platform used by Amazon and also available to external customers, makes a clear reference to the myth surrounding AI and its dependence on human labour. The Mechanical Turk after which the platform is named is the ‘chess robot’ invented in 1770, which travelled the world for 84 years as an example of automation. Later, it turned out that there was a person (often described as disabled or underage, in any case not a chess master) inside the machine and there was little automation involved. Automation does not lead to less work, but to different, degraded form of work. ‘Big tech companies prefer not to talk about that. It undermines the narrative that AI is truly intelligent. In reality, people are working more than ever, but sometimes under worse conditions than before.’ WHO ARE THESE DATA WORKERS? Data workers collect, organise and improve data. Without them, AI would not work. Take image recognition, for example: AI learns what a cat is by analysing millions of images of cats. ‘People have to label those images first. It seems like simple work, but it’s a skill in itself. Yet these data workers often receive remuneration that is not commensurate with their efforts,’ says Casilli. ‘In countries such as Kenya, the monthly wage for these data workers is around $400. That’s not enough to make ends meet.’ Casilli emphasises that this is not a temporary phase. ‘Data work will remain necessary as long as we continue to develop AI,’ he says. ‘We have to constantly train the systems, adapt them to new customer requirements and check them for errors. World Bank or Oxford estimates point towards a ballpark figure of 150 million such workers worldwide, and that number is only growing. That’s another reason why it’s important to take a critical look at their working conditions.’ YOU ARE A DATA WORKER TOO In his book Waiting for Robots, Antonio Casilli mentions a group of digital workers who are often overlooked: social network labourers. This basically includes everyone with a smartphone. Through our daily online activities, we train the AI of large tech companies. We teach AI what a traffic light is by filling in ReCaptchas. When we like social media posts, we teach systems which images are attractive. So we provide value to AI systems, but we are usually not paid for it. We are both users and producers of data. This raises an interesting question: is this work or not? Casilli sees that this form of labour reinforces existing power structures and unequal labour relations. He and his team have been working with both policymakers and unions to bring this to light. ‘Tech engineers at companies like Google earn high salaries, while data workers in India, Venezuela and Madagascar are underpaid. This follows colonial patterns. India carries out data work for English-speaking countries, while French companies outsource work to French-speaking countries in Africa.’ WHAT CAN WE DO? What can we do about this? He describes this in the last chapter of his book ‘What is to be done?’, a tongue-in-cheek quote from Vladimir Lenin. According to Casilli, a systemic approach is needed to improve the conditions of all data workers worldwide. ‘A solution for a specific group will not work in the end. We need to look for a universal strategy.’ He distinguishes between three types of solutions: regulation, collective platform initiatives, and a global redistribution system: 1. Regulation: Spain, for example, has introduced the Riders’ Law and the European Union is working on guidelines for platform workers. “These are steps in the right direction, but this type of regulation needs to be applied more broadly. After all, tech companies operate globally.” 2. Platform cooperatives: Workers can set up their own platforms in which they have a say in wages and working conditions. ‘This is already happening on a small scale, but deserves more attention.’ 3. Redistribution: Large tech companies can be taxed and the proceeds used for a universal basic income for data workers. Importantly, Casilli states that this UBI is neither connected to a “robot tax” (as he doesn’t see robots replacing workers) nor it is intended to replace welfare assistance (as it should be paid regardless of other social benefits). ‘This will ensure greater fairness.’ By combining these three strategies, the professor hopes that we can create a fairer and more sustainable system. ‘Tech companies must take responsibility for all their workers, including the invisible ones who manufacture their data,’ says Casilli. ‘I am concerned about this situation: wages are far below the minimum and even basic health and safety rules are not always observed.’ Casilli believes that organisations such as the WageIndicator Foundation and the Fairwork project are making an important contribution. ‘These organisations set standards for fair wages and working conditions, and these are desperately needed.’ ENFORCEMENT, COLLECTIVE ACTION, AND USER RESPONSIBILITY After several interviews on this topic, I personally believe that, besides the solutions that Casilli provides, it is also important to enforce existing regulations. In countries where there are many underpaid data workers, there is a lack of supervision. This is partly due to strong lobbying by tech companies. That is why it is so important for workers to take collective action, for example via trade unions. These are underrepresented, although a number of interesting grassroots initiatives have emerged. I also believe that (large) users of AI solutions must take responsibility. There are many discussions about responsible AI use. But I can no longer take a discussion about responsible AI seriously if it does not take into account the hidden workers. WHY THIS IS IMPORTANT Casilli and his team are uncovering an important mystery: AI is not a magical ‘black box’. In reality, millions of people work behind the scenes on these so-called ‘intelligent systems’. AI is presented as completely autonomous, and the extensive manual labour involved is often forgotten or ignored. This has serious consequences for the working conditions of these data workers. If we really want to use AI responsibly, we must also consider the people behind the technology. I try to raise awareness of this issue and highlight it wherever possible. That is why I spoke earlier with Claartje ter Hoeven about Ghostwork: the invisible world of work behind AI. I will soon be speaking to the Data Labeler Association in Kenya to gain more insight into the conditions and problems faced by workers in Kenya. After all, we can only really get started with responsible AI if we understand how AI is created. Want to know more? Listen to the full podcast with Antonio Casilli

On May 1st, 2025—Labor Day—France24 hosted a timely televised debate on the fears and opportunities that artificial intelligence presents for workers. Among the guests was Paola Tubaro, co-founder of DiPLab and a researcher at CNRS, who offered a sharp perspective on the discussion. The conversation revolved around a deep contradiction. On one hand, a widespread fear that AI will replace human labor, destabilize job markets, and deepen inequality. Certain jobs—especially those involving routine or precarious tasks—seem to be far more vulnerable than others. On the other hand, AI is also seen as a potential opportunity: the beginning of a “new industrial revolution”, capable of transforming how we work, influencing education, creating new room for social dialogue between employers, governments, and workers. Click here for video Yet Dr. Tubaro urged viewers to go further than surface-level concerns, by shifting the focus toward a more often overlooked question: how AI is produced, and by whom. Behind every “intelligent” machine lies a hidden human infrastructure—thousands of workers labeling data, training algorithms, and moderating online content. These workers, often located in the Global South, remain largely invisible, underpaid, and unprotected. For Tubaro, these workers are among those most overlooked in the AI-driven economy, often bearing the hidden costs of innovation. > “The struggles and union efforts of data workers in the Global South are > especially powerful because they’re not just fighting for better > conditions—they’re putting forward a vision of what AI should be, and what > kind of future it could help us build.” (Paola Tubaro, France24, 1 mai 2025) However, their story does not end there. These same workers are now at the forefront of organizing and resistance, pushing back against the terms of their exploitation and offering alternative visions of an AI-driven world. They are contributing a powerful voice to the global conversation about technology and fairness.

DiPLab’s Thomas Le Bonniec was interviewed by Radio Blackout, an autonomous Italian radio station based in Turin. He discussed the working conditions of AI trainers and the results of the DeepSeek policy memo published by DiPLab. The memo can be downloaded here: THE-HUMAN-COST-OF-DEEPSEEK

Antonio Casilli, professor of Sociology at the Polytechnic Institute of Paris and co-director of the DiPLab research group, recently featured on Italy’s national radio program Eta Beta, hosted by Massimo Cerofolini on Rai Radio1, to discuss the dark side of artificial intelligence. In the interview, Casilli shed light on the invisible workforce behind AI’s apparent automation—millions of precarious, underpaid workers across Africa, Asia, and South America who perform the “dirty work” powering AI systems. For mere pennies per hour, these digital laborers filter disturbing content including graphic violence and sexual abuse, annotate images and videos, correct algorithm errors, train self-driving cars, and even produce commissioned social media engagement. The DiPLab director, author of the award-winning book Waiting for Robots. The Hired Hands of Automation, also highlighted how everyday users unknowingly contribute free labor to improve AI models like American-made ChatGPT or Chinese-developed DeepSeek, further entrenching this exploitative system.

MIT Technology Review has highlighted Antonio Casilli’s Waiting for Robots: The Hired Hands of Automation as one of the essential reads examining our complex relationship with AI and automation technologies. In his review, contributor Bryan Gardiner praises the award-winning book published by University of Chicago Press, placing it among the most insightful works that explore humanity’s nuanced and often tense interactions with robotics and artificial intelligence systems. Casilli, a co-founder of the interdisciplinary group DiPLab, offers a compelling examination of automation’s hidden human workforce—revealing how many supposedly AI-powered systems actually rely on armies of invisible laborers performing digital piecework around the globe. The book’s inclusion in this roundup signals growing mainstream recognition of critical perspectives that look beyond the technological hype to examine the real social and economic impacts of our increasingly automated world. > “Forget about losing jobs to automation. Remarkably, the reality is that > humans steal the jobs of robots.” > The Voder may have been one of the first crude attempts at speech synthesis, > but the disconnect between the way it worked (with a lot of human training and > labor) and the way the public and press perceived it (as a more or less > autonomous machine with its own voice) foreshadowed a problem we still face > today. In Waiting for Robots: The Hired Hands of Automation, Antonio A. > Casilli argues that despite claims to the contrary, human input remains a > crucial component of all modern automation and artificial-intelligence tools, > regardless of their sophistication. The difference is that instead of this > role being obvious—as was the case with the Voderettes—it’s now hidden, and > usually on purpose. Waiting for Robots: The Hired Hands of Automation Antonio A. Casilli > Casilli is a sociology professor at the Polytechnic Institute of Paris who > studies the unseen and unacknowledged “digital labor” that undergirds many of > today’s social media platforms, microtask sites, and on-demand services. > Rather than viewing automation and AI as destroyers of human jobs, he makes a > convincing case that they merely result in the further atomization of work, > fracturing it into smaller, more meaningless, more demeaning tasks for many of > us. “Forget about losing jobs to automation,” he writes. “Remarkably, the > reality is that humans steal the jobs of robots.” > Whether it’s Amazon’s Mechanical Turk, a service for recruiting hundreds of > thousands of micro-taskers to perform video-filtering and image-tagging tasks > that machines can’t do, or the perpetual human “supervision” and > “reinforcement” required for automated learning and AI training, Casilli gives > readers plenty of examples of how human labor (much of it coming from Asian, > Latin American, and African countries) props up—or, in some cases, pretends to > actually be—intelligent systems and products. > > Ultimately, Casilli is less concerned that robots will replace white-collar > workers, and more worried that thousands of lower-paid or unpaid digital > workers will. As he points out, we are already unwittingly being recruited by > companies to collectively perform millions of hours of free work every year. > Take the aforementioned captchas: Google, which owns and deploys one of the > most popular versions of the service (ReCAPTCHA and No CAPTCHA), has been > using this digital labor for more than a decade. The results help detect house > numbers to improve Google Street View, digitize texts for Google Books, and > train its computer vision algorithms to detect locations and reconstruct > scenes, enhancing Google Images and improving the performance of Waymo’s > self-driving cars. “The irony here is that a service that is supposed to > distinguish humans from robots is actually making humans work to produce more > robots,” Casilli writes. > > While all the hype and hyperbole surrounding today’s AI tools can feel > unprecedented, Casilli reminds readers that such rhetoric isn’t really new at > all. Robots, automation, and various intelligent systems have been just on the > verge of taking over all aspects of our work lives and cultural output for > decades now. In the end, artificial intelligence is a technological process > that isn’t actually artificial, he says. Peer behind the curtains of smooth > and seamless efficiency, and it’s humans all the way down.

Sociologist Antonio Casilli joins Monday Buzz’s host Brian Standing on WORT 89.9 Community Radio, Madison, WI for an interview about his book Waiting for Robots. The Hired Hands of Automation. > A recent financial advice column on MSN from The Motley Fool, included the > following breathless assessment of the future of artificial intelligence: > “With AI, software and systems are being empowered to reason, act and evolve, > all without the need for human intervention.”  A CNN report from 2024 claimed > that “AI is Replacing Human Tasks Faster Than You Think.”  Ever since the era > of John Henry and the steam driver, industrialists have crowed about machines > replacing human labor, opening up a future of leisure and prosperity.  But > workers feel more exploited than ever.  Why does that day seem always to be > some time in the future?  Just how autonomous are artificial intelligences any > way?  These questions are the focus of the book “Waiting for Robots” by > Antonio Casilli, now out in English translation from the University of Chicago > Press.