Chapter 34: Further Reading — AI Ethics in Emerging Markets

Foundational Texts

1. Couldry, Nick, and Mejias, Ulises A. (2019). The Costs of Connection: How Data Is Colonizing Human Life and Appropriating It for Capitalism. Stanford University Press. The foundational academic text developing the "data colonialism" concept. Couldry and Mejias argue that the extraction of data from human life represents a new form of colonial appropriation, drawing explicit parallels with historical colonialism. Required reading for understanding the political economy of AI in the Global South.

2. Mohamed, Shakir, Png, Marie-Therese, and Isaac, William (2020). "Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence." Philosophy and Technology, 33, 659–684. An influential academic paper applying decolonial theory to AI, arguing that AI development reproduces colonial power dynamics and proposing a decolonial AI research agenda. By three prominent AI researchers, including Google DeepMind's Shakir Mohamed. Available freely online.

3. Birhane, Abeba (2021). "Algorithmic Injustice: A Relational Ethics Approach." Patterns, 2(2), 100205. An analysis of algorithmic injustice from an Ethiopian-born AI ethics researcher, centering African philosophical traditions in AI ethics analysis and arguing for relational rather than individualistic ethical frameworks. Represents an important alternative to Western-centric AI ethics approaches.

4. Hao, Karen, and Perrigo, Billy (2023). "OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic." TIME Magazine, January 18, 2023. The original investigative journalism that documented the Sama Group/OpenAI content moderation controversy. Essential primary source for the Case Study 1 analysis. Available at time.com.

Surveillance Export and Democratic Governance

5. Feldstein, Steven (2021). The Rise of Digital Repression: How Technology Is Reshaping Power, Politics, and Resistance. Oxford University Press. The most comprehensive academic analysis of how AI-enabled surveillance technology is reshaping political power globally, with extensive case study analysis of AI surveillance deployments in Africa, Asia, and elsewhere. Essential reading for understanding the surveillance export dynamic.

6. Carnegie Endowment for International Peace. "AI Global Surveillance Index." A regularly-updated database documenting AI surveillance technology deployments globally, by country, technology type, and supplier. Available at carnegieendowment.org. The database provides the empirical foundation for analyzing the scope and distribution of AI surveillance export.

7. Freedom House. "Freedom on the Net" Annual Reports. Annual country-by-country assessments of internet freedom, including assessments of AI-enabled surveillance and its political implications. Available at freedomhouse.org. Essential empirical resource for assessing the relationship between AI surveillance deployment and democratic governance.

8. Matsakis, Louise (2019). "How the West Got China's Social Credit System Wrong." WIRED, July 29, 2019. A nuanced corrective to simplistic Western coverage of China's social credit system, which is important context for understanding the distinction between the Chinese governance model and the technology export question. Understanding what China's domestic AI governance actually consists of is necessary for analyzing its technology export.

Development and Financial Inclusion AI

9. Mazzucato, Mariana, and Penna, Caetano (2016). "Beyond Market Failures: The Market Creating and Shaping Roles of State Investment Banks." Journal of Economic Policy Reform, 19(4), 305–326. While not specifically about AI, Mazzucato's analysis of how public investment shapes technology development trajectories provides essential context for understanding why AI development in the Global South requires different public investment frameworks than wealthy-country AI development.

10. Donovan, Kevin, and Park, Emma (2019). "Perpetual Debt in the Silicon Savanna." Boston Review, September/October 2019. A critical analysis of mobile money and fintech in East Africa, examining the debt dynamics that can emerge from financial inclusion technology and challenging the development narrative that uncritically celebrates fintech in Africa. Essential counterpoint to the leapfrogging narrative.

11. Srinivasan, Janaki (2019). "The Political Economy of Big Data in the South." Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. An analysis of how big data and AI intersect with political economy in South Asian contexts, with implications that extend to other Global South settings. Examines who benefits from data collection, who is harmed, and how power dynamics shape data use.

Language AI and Representation

12. Joshi, Pratik, et al. (2020). "The State and Fate of Linguistic Diversity and Inclusion in the NLP World." Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. A systematic analysis of the representation of world languages in NLP research, documenting the enormous skew toward a small number of high-resource languages and the structural barriers to improving underrepresented language performance. The empirical foundation for the chapter's language representation analysis.

13. Nekoto, Wilhelmina, et al. (2020). "Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages." Findings of EMNLP 2020. A paper by a large coalition of African NLP researchers, including the Masakhane founding community, documenting their participatory approach to building machine translation for African languages. Essential reading for understanding what community-driven AI research looks like in practice.

14. Bird, Steven (2020). "Decolonising Speech and Language Technology." Proceedings of COLING 2020. An analysis of colonial dynamics in speech and language technology development, arguing that the field's methods, norms, and priorities reflect colonial knowledge-production structures. Proposes alternative approaches centered on community self-determination.

AI Governance in the Global South

15. Nanjira Sambuli (2019). "Equality and the Digital Revolution." D+C Development and Cooperation. Kenyan technology policy researcher Nanjira Sambuli's analysis of digital inequality and its implications for AI, grounded in African context. Sambuli is one of the most important voices on AI governance in Africa and this piece provides accessible entry to her analysis.

16. Research ICT Africa. "A Framework for Governing Artificial Intelligence in Africa." Research ICT Africa Policy Paper, 2022. A policy analysis from the premier African internet policy research organization, proposing governance frameworks appropriate for African contexts rather than simply adapting EU or US frameworks. Available at researchictafrica.net.

17. Global Partnership on AI (GPAI). "Responsible AI in the Context of COVID-19 and Global Health." GPAI Report, 2020. One of GPAI's substantive research outputs examining AI in global health contexts, with some attention to Global South applications. Illustrates both GPAI's analytical capacity and the limitations of its Global South representation.

Labor and Supply Chain Ethics

18. Gray, Mary, and Suri, Siddharth (2019). Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass. Houghton Mifflin Harcourt. The most thorough analysis of the hidden human labor that powers AI systems, documenting the on-demand and gig economy labor structures that make AI possible. While US-centered, its analysis of how labor invisibility enables exploitation applies directly to Global South annotation work.

19. Williams, Adrienne, Miceli, Milagros, and Gebru, Timnit (2022). "The Exploited Labor Behind Artificial Intelligence." Noema Magazine, October 13, 2022. A shorter, accessible analysis of AI annotation labor exploitation by three prominent AI ethics researchers. A good entry point into the annotation labor ethics discussion that leads into more detailed academic treatments.

20. Tubaro, Paola, and Casilli, Antonio A. (2019). "Micro-work, Artificial Intelligence and the Automotive Industry." Journal of Industrial and Business Economics, 46(3), 333–345. Academic analysis of the micro-work phenomenon — the use of large numbers of low-paid human workers to perform small, discrete tasks that collectively enable AI systems — with implications for understanding the political economy of AI annotation labor globally.