AI for sustainable development | United Nations Development Programme

Authors:
Keyzom Ngodup Massively, Head of Digital Programming, UNDP Chief Digital Office
Calum Handvoort, Strategic Digital Programs Manager, UNDP Chief Digital Office
Alena Klatte, Data Collaboration Project Manager, UNDP Digital Office Chief
Maria Giulia Vitagliano, Digital expert, UNDP for the Italian Presidency of the G7
Alex Hradecky, Artificial Intelligence (AI) Policy Analyst, UNDP Chief Digital Office
Oluwatoyin-Samuel Bamidele, Digital Innovation Officer, UNDP Nigeria
Willem Tsuma, Chief Innovation Officer, UNDP Nigeria
Seth Akumani, Head of Exploration, UNDP Ghana
Ngasuma Kanyeka, Communications Specialist, UNDP Chief Digital Office

Globally, tackling the digital divide is a key development priority. About 2.6 billion people – a third of the population – remain offline. Women use mobile internet 19% less often than men. Digital government services still primarily benefit young, urban, digitally savvy men with higher incomes. This exclusion trend has far-reaching economic and social consequences, with 32 lower-income countries alone losing approximately $1 trillion in tax revenues, productivity and other benefits due to the digital gender divide. As some of these digital gaps close, a new inequality emerges; Computing power, for artificial intelligence and the ability of emerging countries to leverage technological developments as a key accelerator for achieving their sustainable development goals. Computing power is quickly becoming the new and next facet of the digital divide.

1. A new era of opportunity – and inequality

Compute describes the computing power and technology available to train and refine artificial intelligence models and processes. Shifts in the way AI models are evolving, particularly advances in research and development around hardware use and significant investments in custom hardware and technology, have potentially transformed the AI landscape. The “modern era” of how AI systems are trained represents the potential differences between higher and lower income countries.

In a pivotal year of the Global Digital Compact, an initiative to ensure digital technologies work for the benefit of all, UNDP is working to bridge the local and the global – driving action and meaningful change in financing , data, talent, regulations – and computing power. Recent discussions across Africa have highlighted that current AI capabilities require collective action, despite varying development statuses between countries. Collective action is a fundamental driver of the UNDP-G7 industry partnership to explore the development of the AI Hub for Sustainable Development, with a particular focus on Africa.

This direction is shaped by the important recognition that the digital divide between computers and AI is both a new and important inequality, but also based on and catalyzed by existing, deeper and widespread differences. Already digitally constrained, ecosystems in the Global South do not yet have the capacity and resources to research and develop at the pace and concentration that richer countries can. The existing barriers faced by women and girls in such countries pursuing STEM careers lead to a lack of available AI and digital talent. Challenges in financing data collection, curation and management are preventing public and private sector innovators from exploring the power and potential of AI to address local challenges and priorities.

2. Closing the gap

Recent discussions on the African continent have highlighted three key priorities around computing, data and talent.

About democratizing computers

Computing resources around the world are unevenly distributed and not accessible to everyone. Less than 20% of developing countries have modern data infrastructure, such as co-located data centers and direct access to cloud computing. Undertaking large-scale inferences on large-scale models requires robust computing power that is expensive. This limits the local market’s ability to build artificial intelligence that supports policymaking, data-driven decisions and business opportunities. Computing power is a major challenge for students working on AI projects; some need to leave their laptops on for several hours or days to process AI models. There are more and more initiatives to address computing power for local contexts. An example is People + AI a collective of researchers, companies, startups and non-profits to solve ecosystem-level challenges in India. People + AI through the Open Cloud Compute initiative, recently succeeded in increasing access to cost-effective and resilient cloud computing through a digital public infrastructure approach to open computing infrastructure networks.

About data and data models

The critical lack of data sets that reflect the needs and capacities of global majority countries is a significant barrier to digital development. While some data for AI models is available through open data repositories, high-quality, locally relevant datasets in developing countries are often limited and expensive to collect. Researchers need funding to implement new and low-cost methods of collecting, managing, analyzing, and using data relevant to unique local contexts. Private sector companies are creating open and publicly available data sets to drive research and innovation in Africa. A good example is Mozilla Common Voice and Fair forward, open source collectives that amplify natural language processing in the African context.

About human ability and talent

There is a continued need to support the development of science, technology and innovation pathways, deepen research and development culture and improve translational and commercialization skills. Initiatives such as Data science Africa are shaping AI research communities in Africa. GIZ (Gesellschaft für Internationale Zusammenarbeit) is working with the Responsible AI Lab of the Kwame Nkrumah University of Science and Technology (KNOUST) to develop graduate courses in AI for students in Ghana. KNUST has trained more than 200 people in advanced machine learning techniques and data science applications to strengthen the capacity to create AI-related solutions suitable for the African context.

3. A new development approach is needed

To address the challenges of democratizing computing, strengthening data infrastructure, and fostering sustainable talent pipelines, a new multi-stakeholder partnership is essential. The AI Hub for Sustainable Development, championed by the Italian Presidency of the G7 together with UNDP, aims to create a multi-stakeholder initiative to orchestrate collective actions to strengthen local AI ecosystems in developing countries, with a focus on the African continent.

To do this, the Italian Presidency, together with its knowledge partner, UNDP, proposes that the Hub operate as an AI “ecosystem partnerships and exchange space”, to solve the challenges at the ecosystem level. Failure to address these challenges would slow the pace of innovation, lead to waste and inefficiency, and lead to unequal and unfair access to AI. This requires collaboration with private, public and non-profit stakeholders to innovate and demonstrate catalytic and scalable actions on three ecosystem-level challenges:

Infrastructure challenges: Data gaps – unequal distribution or access in AI models, likely to create data gaps with language; high computing costs slow innovation without innovative or new strategies to reduce ecosystem-level computing costs and increase access.
Talent challenges: Talent in research, exploration of AI use cases that do not extend beyond a few donor-funded initiatives.
Policy challenges: Unclear robust and innovative AI policies that do not lead to growth of local ecosystems and leave gaps in digital safeguards for people.

As the Italian-led G7 and UNDP collaborate with global, regional and local industry partners to design the AI Hub for Sustainable Development, it is imperative to build alliances with stakeholders in the country who are deeply immersed in exploring AI -possibilities. Co-design efforts should focus on orchestrating global action on behalf of local AI ecosystems. In the meantime, stakeholders across Africa must continue to meet and take action to lead, learn, invest and collaborate to unleash the potential of AI for Africa’s development.

Contributors to the discussion during roundtables in Ghana and Nigeria

Ghana AI Roundtable: (Patricia Poku (Data Protection Commissioner), Kofi Dadzie (Tony Blair Institute), Nii Longdon, Gifty Buah (University of Ghana) Elikplim Sabblah (GIZ), Daniella Darlington (Copianto AI), Blaise Bayuo (ACET), Alhassan Baba Muniru, Daniel Otto, (GFA Consulting) Worlali Senyo, Jeffrey Amasa, (Farmerline) George Arthur-Sarpong (Viamo), Joseph Berkoh (AU Development Agency – NEPAD)

Italy G7: Eva Spina (G7 President and Head of Department at MIMIT) Vincenzo Del Monaco (G7 Co-President and Minister Plenipotentiary), Valeria Vinci (HoU at MIMIT), Eleonora Iannuzzi (HoU at MIMIT)

Nigeria AI4D: Ada Irkefe, Ayomido Owoyemi, Nonye Ujam (Microsoft), Ojoma Ochai, Olayinka David-West, Sanusi Ismaila, Surryyah Ahmad, Toyosi Arkele-Ongunsiji, Victor Famubode, Dr. Ifeoma Nwafor, Nasir Yamama.

UNDP: Keyzom Ngodup Massally, Calum Handforth, Alena Klatte, Giulia Vitagliano, Alex Hradecky, Oluwatoyin-Samuel Bamidele, Seth Akumani, William Tsuma and Ngasuma Kanyeka