Paola Tubaro was invited to give a talk at the ASOR Institute in Santiago in early July, and shared some results of her research in order to deepen dialogue on these important topics. She discussed how algorithmic management comes with a promise of higher productivity, but also increases surveillance in companies, while the apparent autonomy of self-employed workers on platforms—from Rappi delivery drivers to Workana designers—proves to be illusory. Her presentation, largely though not exclusively based on this open-access book chapter, analyzed the consequences of these transformations on job quality at two key stages of the AI life cycle: its production through human labor (so-called “data work”) and its deployment in workplaces across various sectors, from logistics to healthcare. Taken together, they reveal how AI accelerates preexisting trends in the global economy: the outsourcing of business functions while maintaining control over production—a phenomenon studied by D. Weil as the “fissured workplace”—and a “regime of dispersion,” first theorized by C. Datchary, in which workers manage multiple disconnected tasks. To protect job quality, she argued, corporate strategies and labor regulations must address the cognitive overload associated with fissuring, develop worker-centered organizational models, and implement safeguards for all users. The Millennium Institute for Authority and Social Regulation (ASOR), recently created in Chile, aims to conduct cutting-edge interdisciplinary research on the decline and reconfiguration of authority relationships in contemporary society and their impacts on social regulation. Authority, claim the founders of the Institute, is a pervasive social mechanism that is in place whenever there are power asymmetries. How people manage authority – in the family, school, workplace etc. – affects social cohesion and the extent to which (un)healthy relations of domination may arise. The rise of algorithmic management, especially AI-supported, is widely thought to affect labour relationships, endowing our bosses with new tools or even – as in the exemplary book by Aloisi and De Stefano) that algorithms actually are our new bosses. At the same time, the rise of platform labour – also closely linked to the AI boom – has promoted the model of independent workers who have no boss. Authority in the workplace changes gets more fragmented, disrupting traditional relational models, not only vertically (the hierarchical chain of command), but also horizontally (team composition, collegial work). What are the effects?

Edemilson Paraná invites Paola Tubaro to participate in a special issue published in the journal Globalizations that critically interrogates the convergence of environmental sustainability and digitalization. Governments and multi-lateral institutions frame the “twin transition” as a strategy to foster economic growth and durable social prosperity at the same time. However, Paraná argues in his introductory article (co-authored with Rodrigo Santaella-Gonçalves), this agenda is shaped by market logics and geopolitical competition, in ways that ultimately contradict the social and ecological goals it supposedly supports. The special issue has been designed to offer a systemic political-economy perspective on this inconsistency, grounded in critical social sciences and heterodox economics. Overall, it shows how the structural drivers of digitalisation can constrain its green potential and identifies pathways for redirecting the transition towards socially equitable and ecologically sustainable transformations. Paola Tubaro’s article within the issues aims to reconcile two separate trends in the study of the impacts of artificial intelligence (AI), one focused on the natural and the other on the social surroundings that supply resources for its production and use. She introduces the concept of the ‘dual footprint’ as a heuristic device to capture the commonalities and interdependencies between them. For that, she uses two in-depth case studies, each illustrating international flows of raw materials (nature) and of labour services (society). Case studies are a preliminary illustration of a broader idea, that will need to be developed further: that the AI industry is a value chain that spans national boundaries and perpetuates inherited global inequalities. Specifically, she uses the case of Argentina as a provider to the United States and Madagascar as a provider to France, Japan and South Korea. It appears that the countries that drive AI development (here, the United States, France, Japan and South Korea) generate a massive demand for inputs and trigger social costs that, through the value chain, largely fall on more peripheral actors (here, Argentina and Madagascar). While Argentina and Madagascar differ under many respects, in both cases initial hopes of jobs and prosperity have failed to materialise as predominant outsourcing arrangements reinforce informality and precariousness without preventing environmental damage. Put differently, the arrangements in place distribute the costs and benefits of AI unequally, resulting in unsustainable practices and preventing the upward mobility of relatively more disadvantaged countries. The concept of the dual footprint is useful because it grasps how the environmental and social dimensions of the dual footprint emanate from similar underlying socio-economic processes and geographical trajectories. To freely access the article click here

Public debate about work tends to fixate on numbers: jobs created, jobs lost, jobs threatened by automation. Job Quality in a Turbulent Era, a new volume edited by Agnieszka Piasna and Janine Leschke (Edward Elgar Publishing), asks a harder question: what is actually happening to the quality of work? The full book is available in open access via Edward Elgar Publishing. DiPLab’s Antonio A. Casilli and Paola Tubaro contribute a chapter examining how AI and platformization are “fissuring” contemporary workplaces: fragmenting tasks, eroding protections, and reshaping job quality across sectors in ways that aggregate employment statistics simply cannot capture. To cite this chapter: > Antonio A. Casilli, Paola Tubaro. 2026. What is AI Doing to Job Quality? > Platformization, Fissured Workplaces and Dispersion. Agnieszka Piasna; Janine > Leschke. Job Quality in a Turbulent Era, Edward Elgar Publishing, pp.45-60. Casilli_Tubaro_JobQuality_Chap3Download