Given the sustainable development goals (SDGs) of African countries, the use of Artificial Intelligence (AI) cannot be overemphasized in various sectors including Finance, Healthcare, Agriculture, and Security. There exists a massive potential for increased adoption of AI in Africa to boost productivity and economic development. This is, however, limited by a variety of challenges including the lack of expertise, resources, infrastructure for data collection, and most importantly the awareness of the tremendous capabilities of AI in Africa.

The application of AI in the Finance sector has seen much growth over the years prompting significant investments in research in these areas. However, these research efforts have been dominantly led by practices in the developed world that might not fit well given the complexity of the challenges faced by African nations. The AIA initiative is backed by a group of AI researchers whose focus is to extend these AI capabilities to the Finance sector and foster collaboration in Africa.

The main theme of the 2022 workshop will focus on the opportunities and challenges of applying AI to address key developmental problems faced in Africa. A lot of research has been impeded by the lack of data which in turn has slowed down the pace of development. Of significance is the 2030 SDG initiative (which defines the metrics for development in African nations) which relies on obtaining data from developing countries in Africa.

The topics of interest for the workshop will include, but are not limited to:

• Applied AI methods for addressing social, economic, educational, and environmental challenges faced in Africa.

• AI solutions focused on the banking sector covering areas such as fair lending, fraud detection, financial inclusion, and tools to establish creditworthiness with limited data.

• Natural Language Processing (NLP) research for the African languages.

• New benchmark datasets to help researchers apply AI methods to challenging problems faced in Africa.

• AI methods to assist in poverty reduction and increasing foreign investments in Africa.

• Synthetic Data techniques for enhancing data availability

• Data extraction techniques for documents including low-resourced languages