- Convenors:
-
Juan Grigera
(King's College London)
Ben Tippet
Send message to Convenors
- Format:
- Paper panel
- Stream:
- Digital futures: AI, data & platform governance
Short Abstract
Behind Artificial intelligence lie profound inequalities shaping a complex dynamics of extraction, dependency, and resistance. This panel explores how the governance of AI is reconfiguring state roles, labour relations, and socioecological frontiers across the Global South.
Description
Artificial intelligence is transforming development agendas, industrial policy, and global value chains. Yet beneath the rhetoric of “AI for good” lie profound inequalities in the developing world and complex dynamics of extraction, dependency, and resistance. This panel explores how the governance of AI — through regulation, innovation policy, and infrastructural expansion — is reconfiguring state roles, labour relations, and socioecological frontiers across the Global South.
We invite contributions that examine how Global South governments deal pressures for digital innovation with pressures to protect workers, data, and the environment. How do emerging AI policies in developing contexts mediate between global standards (OECD, EU, UN) and local realities? What forms of dependency and contestation arise around the construction of resource-hungry data centres, energy consumption, rare earth extraction, and the labour that sustains AI systems? How do communities, unions, and civil society actors articulate socioecological and labour rights in the face of new digital enclosures?
By tracing the material and political economies of AI — from resource extraction and data annotation to policy experimentation and regulatory innovation — this panel seeks to connect debates on digital inequality, environmental justice, and postcolonial political economy. It welcomes empirical and theoretical papers that bridge labour, ecological, and governance perspectives to rethink what “responsible” or “just” AI might mean in development contexts.
Accepted papers
Paper short abstract
This paper examines the global value chain of artificial intelligence, tracing its global production. It shows that the Global South—China excepted—contributes labour-intensive activities and primary resources, while (tenuous) value capture remains concentrated elsewhere.
Paper long abstract
This paper analyses the global value chain of artificial intelligence, focusing on the geographical distribution of activities involved in the production, deployment, and use of AI systems. It maps key stages of the AI value chain—including data extraction and labelling, computing infrastructure, model development, and deployment—and examines how value and power are allocated across regions. The analysis shows that the Global South, with the notable exception of China, contributes extensively to AI production through labour-intensive tasks and the supply of primary resources mainly minerals, and data - but also energy and water. These contributions are essential to the functioning of contemporary AI systems, yet they tend to be weakly recognised in the existing value extraction strategies.
The paper further considers the broader economic and social implications of AI. Contrary to dominant narratives of rapid technological transformation, it finds that the impacts of AI remain highly uncertain and uneven. Empirical evidence suggests that AI diffusion has so far been limited, with adoption proceeding at a relatively mild pace in both the Global North and the Global South. Rather than a generalised AI revolution, current patterns point to selective and experimental uptake, concentrated in specific sectors and firms. Taken together, the findings call for a more grounded and globally attentive understanding of AI production and its developmental consequences.
Paper short abstract
As AI systems govern welfare and policing in the Global South, legal authority shifts to offshore algorithms beyond domestic courts. This paper exposes a due-process gap in AI law and proposes a Digital License to Operate, grounding regulation in sovereign control over data and local audits.
Paper long abstract
As artificial intelligence systems increasingly administer public functions in the Global South—ranging from welfare allocation to predictive policing—core elements of legal authority are being displaced beyond national borders. This study is important because AI governance exercises coercive and distributive power traditionally associated with the state, yet remains regulated through external legal frameworks shaped in the Global North. Existing scholarship largely addresses AI ethics or technical risk management, leaving a gap in procedural and constitutional analysis: how can Global South states assert digital sovereignty when algorithmic decision-making is governed by extraterritorial AI laws, particularly those shaped by the European Union’s regulatory reach? The central research question asks how digital sovereignty can be theorised as a jurisdictional and due-process claim, rather than merely a policy aspiration.
The objective of the study is to develop a doctrinal framework enabling states to reclaim regulatory authority over offshore AI systems that produce local legal effects. Using a desktop-based comparative legal methodology, the research analyses EU AI governance instruments alongside African and Asian regulatory responses between 2018 and 2025. Preliminary findings identify a structural due-process failure within algorithmic governance, exacerbated by the uncritical transplantation of EU-style rules—the so-called “Brussels Effect.” The study proposes a Digital License to Operate doctrine grounded in the principle of Permanent Sovereignty over Natural Resources, reframing data as a collective sovereign asset. The findings suggest that mandatory local algorithmic audits can anchor jurisdiction, offering Global South regulators a practical tool to reassert power and rebalance global AI governance.
Paper short abstract
Algorithmic management is reshaping labour relations in the Global South by shifting power from workers to digital systems. This paper examines its effects on labour regulation, worker agency and job quality.
Paper long abstract
Many employers now use digital systems and artificial intelligence to manage workers. These systems assign tasks, track performance, decide pay and sometimes discipline or remove workers. They are often described as neutral or efficient. However, this paper argues that they change who has power at work and how labour is governed, especially in the Global South. The paper examines how algorithmic management affects labour regulation, worker voice, and job quality in developing economies. It shows that when management decisions are built into digital systems, workers find it harder to question decisions, organize collectively or seek protection under labour laws. This is a serious problem in countries where labour laws are already weakly enforced and where many workers are in informal or insecure jobs. The paper argues that algorithmic management now acts like a labour market institution. It shapes working conditions and power relations even though it is not clearly regulated by law. These changes have important development effects, including greater job insecurity, unequal sharing of risks and weaker labour standards.Using examples from developing countries, the paper explores why existing labour laws struggle to deal with digital control at work. It then discusses how labour institutions and regulations could be redesigned to give workers more voice and protect job quality in an uncertain digital future. The paper contributes to development debates by placing labour and worker agency at the centre of discussions about technology and development.
Keywords:Algorithmic management; Labour regulation; Worker agency; Job quality; Global South;
Paper short abstract
The objective of this paper is to describe and analyse their institutional and interdisciplinary linkages both at macro and micro levels, and map AI researchers and their influence in the dissemination of scientific information in the network including their scientific productivity and quality.
Paper long abstract
This paper examines how Artificial Intelligence (AI) research in India is socially constructed by analysing patterns of the co-authorship network among AI researchers affiliated to the first phase of “old” Indian Institutes of Technology (IITs), and how these patterns shape the politics of knowledge production in AI in the context of the Global South. The Scopus database was used to analyse the extent of interdisciplinary and inter-institutional collaboration networks in AI research and correlation is established with the history and philosophy of science in the context of India. Through Social Network Analysis (SNA), the objective of this paper is to describe and analyse their institutional and interdisciplinary linkages both at macro and micro levels, and map AI researchers and their respective influence in the dissemination of scientific information in the network including their scientific productivity and quality. The research refutes the idea that AI develops as the sole result of an internal dynamic and then, unmediated by any other influence, moulds society to fit its patterns. The findings show that AI research projects require appropriate integration of social sciences to aim at concrete deliverables by taking the questions of equity, access and inclusion into consideration.