South Africa’s pursuit of sustainable development is reflected in a vast network of policies and legislation. Numerous government departments, agencies, and stakeholders contribute to this agenda, resulting in a multitude of policies addressing the environmental, social, and economic dimensions of sustainable development.

The sheer volume of policies and legislation makes incoherence likely. The complex web of policies also makes it challenging to determine accurately potential policy synergies and conflicts. This lack of coherence and challenges with addressing incoherence impede South Africa’s ability to allocate resources efficiently and, ultimately, accelerate progress towards sustainable development.


The project usesmachine learning (ML) tools to analyse publicly available South African policies and legislation related to sustainable development. By doing so, it seeks to build on and contribute to the growing body of research on using ML for improved public policy. The project seeks to go beyond existing policy databases and traditional research methods by leveraging the capabilities of ML to identify potential synergies and conflicts. By doing so, the project aims to inform the development of a coherent and strategically aligned policy framework, paving the way for more effective and efficient pursuit of South Africa’s sustainability goals.