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- Convenors:
-
Praveen Priyadarshi
(Indraprastha Institute of Information Technology, Delhi (IIITD))
Manohar Kumar (Indraprastha Institute of Information Technology)
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- Format:
- Paper panel
- Stream:
- Digital futures: AI, data & platform governance
- Location:
- L1.17
- Sessions:
- Friday 10 July, -
Time zone: Europe/Dublin
Short Abstract
The panel interrogates key considerations shaping AI regulations in the countries of the global south. Framing AI regulations, without an epistemic reimagination of technology and its relationship with development, raises questions about their normative and developmental effectiveness.
Description
The panel will focus on two broad approaches: ethical determinism and tech-solutionalism. Ethical determinism is the idea that AI governance is derived from ethical guidelines, while tech solutionism assumes technology to have solutions to all socio-economic and cultural challenges. The tech-solutionist approach, at least in part, is rooted in the colonial and post colonial legacies, especially the impact of these legacies on the imagination of technology as a force of socio-economic transformation. But framing AI regulations uncritically underplays an entire gamut of social, political, and cultural factors that shape the interplay between technology and governance. It also side-steps the unequal conditions in the production and deployment of AI technology and the unequal voice and power relations in shaping guidelines. The panel will interrogate the different imaginations and conceptions that go into framing AI governance guidelines in terms of the burdens and costs they potentially impose on the global south. To examine such epistemic contestations, the panel invites both theoretical works looking at developments and regulations in AI, as well as empirical works looking at the specific AI regulations. It will further ask what alternative imaginations, social and political processes, and values can shape it for a just, equitable and sustainable future. Papers interested in exploring the different meanings of technology and structures in which these meanings are constituted and contested are also welcome. Finally the panel invites papers that make a critical foray into the various actors, institutions, and networks that should play a critical role in shaping regulations.
Accepted papers
Session 1 Friday 10 July, 2026, -Paper short abstract
This paper studies AI and Sustainability-related policies to examine the socio-ecological implications of AI infrastructures in India and Mexico. It includes interviews with AI policy stakeholders in India and Mexico to understand their perspectives, rationalities and justifications in the process.
Paper long abstract
Growing concerns surround the increasing energy demands and environmental impacts of resource extraction for AI chips, running of AI data centres, and the training of models (Crawford, 2021; Hodgkingson et al., 2024; Lehuedé, 2025). Scholars have brought focus to difficulties with calculating the environmental costs of AI technologies and greenwashing, and there have been efforts to increase awareness about these impacts (Hao, 2024 and 2025; Heikkilä, 2022). Current scholarship at the intersections of AI, sustainability and policy studies has tended to focus on leveraging AI for achieving sustainability goals (Nishant et al., 2020). However, little is known about the experiences and policies that shape the lives of those most affected by new data infrastructures. This is critical because Global South countries bear a larger share of the brunt of the environmental costs associated with data centre and ICT infrastructure development, while reaping fewer benefits from digitisation (UNCTAD, 2024).
Our paper draws on an ongoing research project that examines the socio-ecological implications of AI infrastructure development in India and Mexico, with a focus on AI policies and lived experiences of communities. In this presentation, we specifically focus on AI and Sustainability-related policies, including international, Indian and Mexican policy documents related to AI technologies, as well as adjacent and associated policies (e.g. land acquisition, water resourcing, environmental clearances and labour laws). This is supplemented by semi-structured interviews (n=10) with AI policy stakeholders each in India and Mexico, to understand their perspectives on the sustainability implications of AI technologies and infrastructures.
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.
Paper short abstract
AI governance is often framed through ethical and techno-solutionist models presented as neutral and universal. This paper argues that such approaches reproduce epistemic injustice and digital colonialism, and advances epistemic sovereignty as a decolonial alternative.
Paper long abstract
Artificial Intelligence (AI) governance is dominated by regulatory frameworks that foreground ethical principles. While these approaches are presented as neutral and progressive, this paper argues that they reproduce deep epistemic and structural inequalities when transposed uncritically into Global South contexts. Anchored in ethical determinism and technological solutionism, prevailing AI governance regimes tend to obscure the historical and cultural conditions that shape the production of AI. This paper contends that such approaches perpetuate epistemic injustice and entrench forms of digital colonialism. Wherein Global South societies become sites of data extraction and experimentation while they remain marginal to decision-making and lack equal control over technological design and governance. The asymmetrical distribution of regulatory costs and benefits raises critical questions about whose interests AI governance ultimately serves and whether existing frameworks meaningfully address issues of economic dependency and infrastructural inequality. Against this background, the paper advances the concept of epistemic sovereignty as a normative and political horizon for decolonising AI governance in the Global South. This paper further examines how AI governance is shaped by transnational technology corporations, international standards bodies, and Global North research institutions, while the Global South states, communities, and knowledge producers are marginalised. This mirrors colonial extractive relations where value is generated from Global South resources without meaningful participation or benefit-sharing. In doing so, the paper exposes how tech-solutionist approaches to AI governance obscure power asymmetries and legitimise dependency under the guise of innovation and development.
Paper short abstract
This paper examines AI-driven revenue mobilisation in Kenya, through the integration of telco data with tax systems. It critiques tech-solutionist AI governance under Kenya’s Data Protection Act and AI Strategy, arguing that procedural compliance obscures political, and distributive challenges.
Paper long abstract
This paper critically examines tech-solutionism in AI governance through the empirical case of AI-driven revenue mobilisation in Kenya. Recently, the Kenyan government decided to integrate telecommunications and mobile money transactions data with Kenya Revenue Authority (KRA) systems as a strategy to enhance tax compliance, widen the tax base, and curb revenue leakages (Republic of Kenya, 2023). These initiatives are framed as neutral, efficiency-enhancing technological fixes to structural revenue challenges.
Considering Kenya’s Data Protection Act (2019) and the National Artificial Intelligence Strategy 2025–2030, the paper argues that such solutionist framings obscure the socio-political and distributive dimensions of taxation. While the Data Protection Act provides safeguards against solely automated decision-making and mandates data protection impact assessments (Republic of Kenya, 2019), in practice these mechanisms are operationalised as procedural compliance tools within revenue analytics systems. Application of predictive models trained on integrated data runs the danger of disproportionately targeting informal sector and intensifying surveillance without addressing underlying causes of informality.
The National AI Strategy positions AI on public sector efficiency and economic growth (Government of Kenya, 2024), reinforces a developmental narrative in which technological deployment precedes institutional readiness, and democratic oversight. This dynamic is conceptualised as epistemic displacement, whereby locally grounded understandings of informality, state–citizen trust, and fiscal justice are abandoned in favour of emerging technologies.
By foregrounding revenue mobilisation as a critical site of AI governance, the paper challenges ethical determinism and argues for a context-sensitive approach that treats AI governance as a political and distributive process rather than purely technical.
Paper short abstract
This analysis of AI co-authorship across 185 countries (2015–2024) reveals expanding geographic participation but persistent hierarchy. New centres emerge yet concentrate activity within subregions, suggesting that expanded collaboration does not automatically strengthen research capability.
Paper long abstract
The spread of artificial intelligence has intensified concern over unequal access to digital infrastructure, compute and skills. Less attention has been paid to the international relationships through which countries acquire the capacity to produce and evaluate AI knowledge. This article examines international AI co-authorship between 2015 and 2024 across five research fields, 185 countries and 19 subregions. Using a leading-partner network, it investigates whether expanding participation has redistributed research activity and strengthened countries’ capacity to sustain collaboration through several consequential relationships. The global AI research system became more extensive and more polycentric. India rose sharply in global activity, Saudi Arabia entered the leading country tier, and Singapore emerged as an important gateway in South-eastern Asia. The United Arab Emirates, South Korea, Taiwan and Australia also gained prominence, especially in frontier fields. Nevertheless, activity, continuity and partner alternatives remained highly uneven. New centres widened the geography of the upper tier while frequently concentrating activity within their own subregions. The article characterises this pattern as hierarchical integration: incorporation into a common research system expands, but the institutional and relational conditions for benefiting from that incorporation remain unequal. The concept helps distinguish simple entry from the durable conversion of collaboration into technological capability. For development policy, the relevant question is therefore not only how many countries participate, but whether collaboration strengthens continuing research activity, regional and domestic institutions, consequential partner alternatives and a greater role for local actors in defining research priorities and evaluation.