This essay is part of the series: AI F4: Facts, Fiction, Fears and Fantasies.
International and national development organisations have highlighted Artificial Intelligence’s (AI) potential for providing a skills and innovation boost in emerging economies. The United Nations (UN) recently launched its AI Advisory Body, similarly, the United Kingdom (UK) government announced its AI for development policy to focus on helping developing countries build AI skills and boost innovation. Conversely, academia has highlighted Western countries’ grip on Global South data as “Data colonialism”. Regardless of where you stand on AI being a fantasy or fear in emerging economies, the current discourse ignores emerging economies’ agency in determining the use of AI for guiding their own development.
(1) A homegrown AI ecosystem in emerging economies
The World Economic Forum highlights that emerging economies are more optimistic about AI than developed economies. There are four distinct economic aspects where AI has had success in emerging economies, especially in, creating startup hubs, upskilling, and ease of installation.
First, startup hubs in emerging economies have brought about the rise of a national AI ecosystem. The Harvard Business Review includes emerging economies in its top 50 AI hubs. Of the 50, one might be surprised to find Kuala Lumpur ranked higher than both Johannesburg and Istanbul. Additionally, it is interesting to see locations like São Paulo in the mix. Admittedly, both cities are much lower on the list with Kuala Lumpur ranked at 38 and São Paulo at 43.
Even though it is significant to see emerging economies make the list, it must be noted that their success stories have not been seen in international media and many opt to discuss AI’s progression in more established tech centres like Bengaluru, Beijing, or San Francisco.
The OECD.AI Observatory highlights that Nigeria has seen its greatest AI skill force growth to date, with its labour force jumping from 1.2 to2.2 percent of citizens working with AI.
Second, education in emerging economies has also driven their AI bloom. In fact, the World Economic Forum notes that emerging economies' populations are more familiar, if not more advanced, in their understanding of AI application than citizens of developed peers. For instance, Brazil coming out of the COVID-19 pandemic was able to hire three times as many more AI workers from its talent pipeline than in 2017. Additionally, the OECD.AI Observatory highlights that Nigeria has seen its greatest AI skill force growth to date, with its labour force jumping from 1.2 to2.2 percent of citizens working with AI.
Third, digitalisation in emerging economies is a significant factor enabling AI growth. Unlike infrastructure-intensive general purpose technologies (GPT), such as broadband, AI is software based. This is significant for emerging economies as it provides a means to leapfrog without significant hardware investment. In particular, Bloomberg notes the Philippines as a primary contender for rapid AI integration.
Fourth, in quite a few cases, emerging economies’ governments have taken a proactive approach to regulating industries around AI, even more so than developed countries without a responsible AI act like the UK. For instance, Malaysia is set to release its code of ethics and governance in 2024, and it has been following its National Artificial Intelligence Roadmap since 2021.
Together these four peaks in emerging economies’ AI trajectory—a strong startup ecosystem, skills, growth potential, and governance—highlight its homegrown economic potential. However, developing countries' ability to use AI for non-economic development need to be analysed.
(2) How are emerging economies using AI to promote non-economic development
Three non-economic areas where AI in emerging economies has made an impact include job transformation, health, and sustainability.
A core success story has been Ghana which has fully incorporated AI-driven telemedicine into its national medical infrastructure after a successful pilot during the COVID-19 pandemic.
First, with respect to job transformation, the OECD.AI Observatory highlights that reorganisation is more likely than displacement, with positive effects including improved workplace safety. Additionally, AI promotes job transformation in emerging economies through job matching, or streamlining, the hiring process to better match workers with new types of jobs.
Second, with consideration to health, the World Bank notes that AI has helped ease diagnosis difficulties in emerging economies’ remote communities. A core success story has been Ghana which has fully incorporated AI-driven telemedicine into its national medical infrastructure after a successful pilot during the COVID-19 pandemic.
Third, with regard to sustainability efforts, the KTH Royal Institute of Technology notes that AI algorithms have already supported emerging economies by automatically detecting potential oil spills. Moreover, a recent World Bank blog highlights the ability to combine AI with 3D printing to build more affordable and environmental housing.
Development organisations should confront this fear of AI underdevelopment in the Global South and forge closer partnerships with each country's AI governing body.
Concluding remarks
The hype on AI’s success in tech-developed countries like the United States (US), China, and India has influenced the discourse around their development organisations guiding AI’s rollout in emerging economies. This discourse should be taken with a grain of salt given the optimism for self-administered AI in emerging markets for both economic and non-economic forms of growth
Accordingly, development organisations should confront this fear of AI underdevelopment in the Global South and forge closer partnerships with each country's AI governing body. Such collaboration can result in cross-knowledge diffusion on AI’s use cases for promoting economic and non-economic development while carving out a greater role for emerging economies.
Alex Brunner is an Mphil candidate at the University of Oxford.
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