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The backroads of AI: the uneven geographies of artificial intelligence and development

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posted on 2025-05-09, 00:46 authored by Duncan McDuie-RaDuncan McDuie-Ra, Kalervo Gulson
Artificial intelligence is being reconfigured as a set of technologies that can address poverty with precision. The impacts of AI will both exacerbate and ameliorate the conditions of uneven development. Recent debates focus on the disruptive effects of AI, particularly to replication of development trajectories that have had success in reducing poverty. In this paper we further these debates by analysing the backroads of AI. The backroads serve as a metaphor for understanding the ways AI will travel from the sites of incubation to the frontlines of uneven development. We explore dialogues between AI and development in two arenas: the World Bank's Development Impact Evaluation initiative (DIME) and the Government of India's national AI strategy, #AIforAll. We argue that both these arenas serve as hubs from which AI will travel out along the backroads to remote, poor, and fragmented polities. While the World Bank utilises AI as technology to empower experts and mobilise a techno-political authority, what we refer to as precision AI, India seeks to function as a second-tier AI hub, making AI cheaper and more accessible domestically and for other developing countries, what we refer to as populist AI. We conclude by discussing the interrelations of precision and populist AI along the backroads, and the potential of backroads research for mapping AI, uneven geographies of development and technology and the impacts of AI's disruptions at different scales.

History

Journal title

Area

Volume

52

Issue

3

Pagination

626-633

Publisher

Wiley-Blackwell

Language

  • en, English

College/Research Centre

Faculty of Education and Arts

School

School of Humanities and Social Science

Rights statement

McDuie-Ra, Duncan; Gulson, Kalervo. “The backroads of AI: the uneven geographies of artificial intelligence and development”. Area Vol. 52, Issue 3, p. 626-633 (2020), which has been published in final form at http://dx.doi.org/10.1111/area.12602. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.