Lo sfogo rancoroso e carico di dolore contro l’IA non ci aiuta a intravedere la via verso un futuro migliore: né utopie né… L'articolo I cinque stadi del lutto da AI sembra essere il primo su L'INDISCRETO.

Has artificial intelligence truly outgrown its “Global South data sweatshop” phase? The recent deluge of “AI tutor” job advertisements on LinkedIn targeting highly qualified candidates with advanced degrees might suggest so. When Sam Altman claims his chatbot is “PhD-level smart,” one might assume this reflects a genuine shift toward elite expertise in AI training. However, groundbreaking investigative reporting published by Africa Uncensored reveals a more troubling reality: these recruitment campaigns represent elaborate investor-facing theatrics rather than meaningful industry evolution. DiPLab applauds the exceptional work of data journalists and Pulitzer Center Artificial Intelligence Accountability fellows Kathryn Cleary and Marché Arends, whose year-long investigation exposed a curious case study in modern AI labor practices. Their research focused on companies like Mindrift and Scale AI’s Outlier, which have been flooding professional networks with advertisements for highly qualified and relatively well-compensated “AI tutors” and “trainers,” primarily targeting workers in high-income countries across North America and Europe. These positions appeared to target elite specialists rather than the typical pool of low-paid data annotators traditionally associated with AI training. The recruitment campaigns seems to suggest that major tech companies, in their aggressive push toward Artificial General Intelligence (AGI), are now seeking only the most brilliant minds to train sophisticated chain-of-thought models. The Africa Uncensored investigation reveals a starkly different reality. Once recruited, these qualified workers—many holding advanced degrees in physics, philology, and other specialized fields—were left idle for months, barely managing to earn double-digit wages. They were essentially serving as props in an elaborate performance of AI progress, carefully staged to impress investors and signal scalability to potential big tech clients. Meanwhile, on platforms targeting workers in the Global South, such as Mindrift’s sister platform Toloka, recruitment for poorly paid microtasks continued under largely exploitative conditions. This parallel system reveals the persistent nature of what researchers have termed “digital sweatshops.” For DiPLab and its research community, these findings represent “old wine in new bottles.” For nearly a decade, DiPLab researchers have been encountering and interviewing data workers who hold Master’s and Doctoral degrees—experts in their own right across diverse disciplines. Many of these highly qualified individuals remain unemployed due to dysfunction in traditional job markets, or find themselves forced to accept data work that neither matches their specialization nor provides adequate compensation. According to DiPLab co-founder Antonio Casilli, interviewed along prof. Edemilson Paranà and dr. Adio Dinika, in the exposé: “This is the biggest waste of social capital in human history. These people would be, should be, destined to the best jobs because they are probably the best and the brightest of their generation.” The mass recruitment strategy serves a specific economic function within what researchers call “labor hedging”—a tactic where companies amass large pools of workers primarily to signal scalability and attract major contracts. As the investigation revealed, Mindrift alone posted over 5,770 job listings across 62 countries in just four months, yet provided minimal actual work opportunities. This approach allows platforms to maintain what they euphemistically term “talent pools”—readily available workforces that can be presented to potential clients as evidence of operational capacity. When a major tech company inquires about access to specialized expertise, these platforms can point to their extensive databases of pre-vetted candidates as proof of their ability to deliver at scale. DiPLab’s research situates these practices within the broader context of platform capitalism surrounding AI development. The current AI boom and the associated recruitment theater serve as crucial signals in this speculative environment. As Casilli noted, “Investors are on LinkedIn too, they see this [mass recruitment], it is a signal for them. This looks more like a communications operation.” These platforms understand that LinkedIn functions not merely as a talent acquisition tool, but as a visibility platform for investor audiences. The courageous reporting by Cleary and Arends, supported by Africa Uncensored, an outlet willing to publish investigations that major US and European media often avoid, highlights the critical need for continued scrutiny of AI labor practices. --------------------------------------------------------------------------------

DiPLab researchers Paola Tubaro and Antonio Casilli recently completed a research mission to Santiago, Chile, participating in key academic events that advanced understanding of artificial intelligence’s social and environmental dimensions. Tubaro delivered a keynote address at the 4th annual workshop of the Millennium Nucleus on the Evolution of Work (M-NEW), where she serves as a senior international member. The interdisciplinary workshop convened labor scholars from across Latin America and internationally to examine contemporary work transformations. Her presentation drew on DiPLab’s multi-year research program investigating the invisible human labor underlying global AI production. Tubaro’s analysis traced the evolution of this work form over two decades, demonstrating that while core functions in smart system development have remained consistent, the scope and volume of these tasks have expanded significantly. Tubaro and Casilli also participated in the inaugural meeting of SEED (“Social and Environmental Effects of Data connectivity: Hybrid ecologies of transoceanic cables and data centers in Chile and France”), a new collaborative research project between DiPLab and the Millennium Nucleus FAIR (“Futures of Artificial Intelligence Research”). The project has received joint funding from the ECOS-SUD programme (France) and ANID (Chile) to analyze the complete AI value chain, examining production, development, employment impacts, usage patterns, and environmental consequences through comparative study of the Valparaíso-Santiago de Chile and Marseille-Paris corridors. In their SEED presentations, Tubaro and Casilli introduced the concept of the “dual footprint” as an analytical framework for understanding the interconnected environmental and social impacts of AI systems. This heuristic device captures commonalities and interdependencies between AI’s effects on natural and social environments that provide resources for its production and deployment. DiPLab researchers framed the AI industry as a transnational value chain that perpetuates existing global inequalities. Countries driving AI development generate substantial demand for inputs while externalizing social costs through the value chain to more peripheral actors. These arrangements distribute AI’s costs and benefits unequally, resulting in unsustainable practices and limiting upward mobility for disadvantaged countries. The dual footprint framework demonstrates how environmental and social dimensions of AI emerge from similar structural dynamics, providing a unified approach to understanding AI’s comprehensive impact on global resource systems.

It has been a particularly productive semester for DiPLab researchers and affiliates in terms of publishing articles and book chapters. Here are the complete citations (and open access links) of our recent contributions that compare data work in various countries. -------------------------------------------------------------------------------- A Special issue of New Political Economy guest-edited by Uma Rani Amara and Nicolas Pons-Vignon on “Power relations in the digital economy” has been published as Volume 30, issue 3 of the journal. It includes our article on “Where does AI come from?”, a comparison of data work in Venezuela, Madagascar, and France. > Tubaro, Paola, Antonio A. Casilli, Maxime Cornet, Clément Le Ludec, and Juana > Torres Cierpe. 2025. “Where Does AI Come from? A Global Case Study across > Europe, Africa, and Latin America.” New Political Economy 30 (3): 359–72. > doi:10.1080/13563467.2025.2462137. (preprint access here: > https://inria.hal.science/hal-04933816v1) The Journal Globalizations has published a special issue on The Political Economy of Artificial Intelligence in Latin America. It features our article on AI labor in Brazil and Argentina. > Tubaro, Paola, Antonio A. Casilli, Mariana Fernández Massi, Julieta Longo, > Juana Torres Cierpe, and Matheus Viana Braz. 2025. “The Digital Labour of > Artificial Intelligence in Latin America: A Comparison of Argentina, Brazil, > and Venezuela.” Globalizations, February, 1–16. > doi:10.1080/14747731.2025.2465171. (preprint access here: > https://cnrs.hal.science/hal-04935984v1) The Handbook of Digital Labor, edited by Jack Linchuan Qiu, Shinjoung Yeo, and Richard Maxwell, has been released by Wiley Blackwell. This comprehensive work brings together leading voices on the transformations of labor in the digital age. Among its contributions, our chapter on global inequalities and AI, comparing Venezuela, France, Madagascar, and Brazil. > Casilli, Antonio A., Paola Tubaro, Maxime Cornet, Clément Le Ludec, Juana > Torres-Cierpe, et al. 2025. Global Inequalities in the Production of > Artificial Intelligence: A Four-Country Study on Data Work. In: Jack Linchuan > Qiu, Shinjoung Yeo, Richard Maxwell (eds.). The Handbook of Digital Labor, > Wiley Blackwell, pp.219-232, 2025, ISBN10: 9781119981800. (preprint access > here: https://hal.science/hal-04742532v2) The journal New Technology, Work and Employment has made available, as an online first, the new article by Juana Torres-Cierpe and Paola Tubaro about Venezuelan data workers. > Torres-Cierpe, Juana and Paola Tubaro. 2025. Uninvited Protagonists: The > Networked Agency of Venezuelan Platform Data Workers. New Technology, Work and > Employment. https://doi.org/10.1111/ntwe.12340 (preprint access here: > https://hal.science/hal-05041068v1)

Un’intelligenza artificiale prende parola per raccontare cosa significa studiare senza copiare, imparare senza possedere, generare senza replicare. In questo manifesto, si interroga e… L'articolo Il deep learning è studio, non memoria sembra essere il primo su L'INDISCRETO.

Dalla “morte della pittura” ai libri scritti dall’AI, ogni nuovo medium risveglia la stessa paura: l’arte avrebbe esaurito la propria aura. Il caso-performance… L'articolo Dall’aura all’algoritmo: Benjamin, Ipnocrazia e l’arte senza ombelico sembra essere il primo su L'INDISCRETO.

Quanto è importante prestare attenzione alle foto false generate dall’AI, l’intelligenza artificiale, che circolano sul web? Ne parliamo con Davide Del Monte, presidente di info.nodes. Radio Onda d’Urto ha intervistato Davide del Monte a seguito dell’incrementarsi nel Mondo di due diverse correnti di utilizzo dell’intelligenza artificiale e della diffusione delle ‘fake news‘. Un utilizzo è quello incontrollato della controparte, delle grandi potenze, per creare notizie false e criminalizzare lotte o movimenti e che Del Monte definisce pura “propaganda“. L’altro utilizzo dell’intelligenza artificiale proviene, invece, dal basso. E per analizzarlo si è partiti da una fake news diffusa durante la Global March to Gaza: una marcia composta da persone da tutto il mondo che stanno convergendo in Egitto per cercare di rompere l’assedio israeliano su Gaza. Le immagini che circolano, però, sono in alcuni casi false: la carovana Sumud partita dal Nordafrica è effettivamente partecipata da migliaia di persone, ma i video e le foto che si stanno diffondendo maggiormente sono realizzate dall’intelligenza artificiale (vedi foto). “C’è il rischio di depotenziare e delegittimare il messaggio di questa importante iniziativa se diffuse”, fa sapere Davide Del Monte. La disinformazione sui social ha anche contribuito grandemente alla tensione in California a seguito delle proteste anti-ICE. E’ tornata in auge la già utilizzata foto di mattoni impilati su dei pallet – e che circola sin dalle proteste di Black Lives Matter nel 2020 – per tentare di criminalizzare le proteste producendo notizie false e per tentare di dimostrare che ci sia una volontà “esterna” a guidare le rivolte a Los Angeles. Nel contesto del film Matrix, la “realtà” è definita come una simulazione creata da macchine, che viene percepita come “reale” dai personaggi umani. Siamo a questo punto? Ne parliamo con Davide Del Monte, presidente di info.nodes. Ascolta o scarica.

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.

We share the exciting news of two new papers that were published last month, concerning parts of the extensive research DiPLab conducts on the networks of production of AI The first paper is titled “Where does AI come from? A global case study across Europe, Africa, and Latin America” (by P. Tubaro, A.A. Casilli, M. Cornet, C. le Ludec and J. Torres Cierpe), appears in New Political Economy’s special issue on power in the digital economy. It examines AI supply chains, focusing on how and where companies recruit workers for data annotation and other essential tasks. While the organisation of AI data work varies, the reasons for these differences and the ways it dovetails with local economies were underexplored. This article clarifies these supply chains’ structures, highlighting their impacts on labour conditions and remunerations. Framing AI as an instance of well-known outsourcing and offshoring trends, analysis of AI data work in France, Madagascar, and Venezuela, highlights two main models: marketplace-like contracts and firm-like structures, with hybrid arrangements in between. Each model suits different AI tasks but all reproduce well-known patterns of exclusion that harm externalised workers especially in the Global South. We argue that worker reclassification alone is insufficient and advocate for a broader policy mix, including regulation of technology and development strategies at national and supra-national levels. You may find an open access version of the preprint of the paper here -------------------------------------------------------------------------------- -------------------------------------------------------------------------------- The second paper is titled “The digital labour of artificial intelligence in Latin America: a comparison of Argentina, Brazil, and Venezuela” (by P. Tubaro, A.A. Casilli, M. Fernández Massi, J. Longo, J. Torres Cierpe and M. Viana Braz) appears in Globalizations’ special issue on AI in Latin America. It sheds light on the precarious, low-paid data workers supporting AI production in the region, often for foreign firms. Mixed-method data support a comparison of Argentina, Brazil, and Venezuela to reveal common patterns and regional differences. The analysis supports the conclusion that Latin America plays a key role in AI data work, with companies exploiting economic hardship to cut costs. In Venezuela and Argentina, crisis conditions foster an ‘elite’ of young, STEM-educated workers, while in Brazil, this work is done by lower-income groups. In all three countries, AI data work also blends with the informal economy, reinforcing inequality in this way. These findings call for more attention to AI labour conditions and advocate for policies to recognise data workers’ skills and support their career development, potentially enabling worker organisation. You may find an open access version of the preprint of the paper here