Generally, in conversations on cutting-edge technology, the focus tends to be on financially lucrative opportunities for entrepreneurs, the wider private sector and countries’ economies. However, these very technologies can be crucial in addressing a broad range of social ills and challenges. In this article, we make a case for harnessing AI for the societal good of developing countries.
The narrative surrounding Artificial Intelligence (AI) often centres on its transformative power for economic growth. We hear of its potential to revolutionise industries, enhance productivity, and drive innovation across sectors such as agriculture, manufacturing, and finance. Although this focus is understandable, particularly in the context of developing countries striving for economic advancement, it risks overshadowing an equally crucial and perhaps more profound potential: AI’s ability to address pressing societal challenges and foster inclusive development.
The plight of pensioners versus countries’ economic growth
The impetus for this article was the chasm that exists based on two recently published articles that effectively highlighted the different worlds that need to coexist in Caribbean society. First, there was a recent Letter to the Editor in the Jamaica Observer in which the writer lamented “…the very archaic system of tracking the legitimacy of pensioners to continue receiving pensions”. Every quarter, pensioners in Jamaica are required to confirm they are still alive by submitting a Life Certificate that must be verified by a Justice of the Peace or other suitable officer. However, as tends to be the norm worldwide, the elderly live very modestly and, in some instances, live below the poverty line. They might also live in remote areas, not have ready access to transportation, or be physically challenged. Hence, the cost and quarterly effort to submit the Life Certificate, for which processing may eventually be delayed, can result in undue hardship for pensioners who are relying on those funds to survive. The writer was thus advocating for urgent attention to be given to this issue and made some recommendations.
In a different vein, the Cayman Compass reported that based on a report published by PwC, assertions were being made that, “Artificial intelligence could revolutionise the economies of Cayman and those across the Caribbean…” Noting the Cayman Islands’ focus on financial services, the report was stated to highlight AI and emerging technologies’ potential to revolutionise that sector, particularly in risk assessment, portfolio management, and compliance.
AI to tackle societal challenges
Developing nations grapple with a unique set of complex social issues, ranging from inadequate healthcare and limited access to quality education to environmental degradation and inefficient governance. These challenges often disproportionately affect vulnerable populations and hinder overall societal progress. AI, with its capacity for data analysis, pattern recognition, and automation, offers a powerful toolkit to tackle these issues head-on.
The potential is vast and compelling. AI can analyse complex datasets related to poverty, inequality, and food insecurity to identify underlying causes and inform targeted interventions. It can also personalise educational content to cater to individual learning needs, bridging gaps in access and quality. Further, AI-powered early warning systems can help communities prepare for climate-related shocks, minimising their impact on livelihoods and infrastructure.
Additionally, as was discussed in our article, Leapfrogging with less: Why Small Language Models could be a game-changer for developing countries, developing countries and regions can build their own small language AI models to address their unique challenges and ecosystems and to do so more economically than can currently be done with Large Language Models (LLM). Small Language Models cost a fraction of that for an LLM and are not as resource-intensive, and so are considered a viable and attractive option for developing countries to create “local solutions that have an impact”.
Harnessing AI’s potential for the social transformation
Having said this, the development and deployment of AI solutions focused on societal challenges in developing countries face significant hurdles, particularly in securing the necessary support and investment. The allure of immediate economic returns and creating the next ‘tech unicorn’ often overshadows the longer-term, yet equally vital, benefits of addressing social issues. Furthermore, social development projects may not always present clear-cut financial incentives, making it challenging to attract traditional funding sources.
To ensure that the transformative potential of AI benefits the whole of society, especially in developing countries, a concerted effort is required to cultivate support for socially oriented AI initiatives. Outlined below are key strategies that could be implemented.
1. Raise awareness and demonstrate impact
First, it is crucial to showcase the tangible benefits of AI in addressing social challenges through pilot projects and compelling case studies. Documenting the positive impact on people’s lives, such as improved health outcomes, enhanced educational attainment, or more efficient resource management, can build trust and garner support from policymakers, investors, and the public. For example, demonstrating how an AI-powered agricultural advisory service leads to increased yields and improved livelihoods for smallholder farmers can be a powerful advocacy tool.
2. Foster collaboration and partnerships
Addressing complex social issues requires a multistakeholder approach. Collaboration between governments, research institutions, non-governmental organisations (NGOs), social enterprises, and the private sector should be encouraged to bring together diverse expertise and resources. Public-private partnerships, with governments providing seed funding or policy support, for example, and private entities offering technological expertise, can be particularly effective and a powerful investment tool countries should have in their arsenal.
3. Develop ethical frameworks and guidelines
As AI applications become more prevalent, it is essential to establish ethical frameworks and guidelines that address issues of data privacy, bias, and accountability, especially when dealing with sensitive social data. Currently, many Caribbean countries are having discussions on this, but so far, no regional consensus has emerged. These frameworks will ensure that AI solutions are developed and deployed responsibly and do not exacerbate existing inequalities, which may be more pronounced in developing countries. Implementing the multistakeholder approach and involving local communities in the development of these frameworks is crucial to ensure they are appropriate, culturally relevant and context specific.
4. Build local capacity and expertise
Sustainable AI development requires investing in local talent and ensuring that the enabling environment supports that objective. Supporting educational programmes in AI and data science, fostering research and innovation hubs, and developing the ecosystem for local AI entrepreneurs and researchers to thrive would need to be addressed. More importantly, these elements ought to be tailored to address the specific needs and contexts of developing countries to, once again, ensure they will facilitate realisation of the desired objective and goals.
5. Explore innovative funding mechanisms
In many developing countries there can be an overwhelming focus on donor funds to implement most projects. However, that posture may result in misalignment between a country’s needs and the imperatives and lending objectives of donor agencies. Beyond traditional funding models, countries should be prepared to explore innovative financing mechanisms such as impact investing, social bonds, and philanthropic grants can provide crucial support for socially focused AI initiatives. These mechanisms prioritise social and environmental impact alongside financial returns, and could foster a greater alignment of incentives with the broader goals of inclusive development.
6. Advocate for supportive policies
Finally, governments play a critical role in creating a supportive policy environment for socially beneficial AI. They can drive prioritising AI for social good in national development strategies, providing regulatory clarity, and incentivising investment in this area through tax breaks or grants. Moreover, they can establish channels through which to foster international collaborations and knowledge sharing, which can accelerate the adoption and implementation of best practices.
Conclusion
In summary, although the economic potential of AI in developing countries is undeniable, its power to address deep-seated societal challenges offers an even more transformative opportunity. Matters related to social development and the social good have been important focus areas in regional and international forums, but the will or effort to meaningfully address goals and targets that have been established may not be as evident as would be needed to realise meaningful improvements.
Finally, it is emphasised that although much of the social development initiatives tend to be focused on improving the lot of the most vulnerable members of society, such as addressing property reduction, improved access to healthcare and education, there is also considerable scope to use AI and associated technologies to address inefficiencies and unduly bureaucratic processes. Adopting a more comprehensive and holistic posture to solve societal problems will redound to the benefit of all members, not just the most vulnerable.
Image credit Freepik
