A Global South Perspective on Explainable AI

In the last five years, over a dozen international institutions have emphasized the need for outputs from artificial intelligence (AI) systems to be explainable. Among the first sets of influential international guidelines that have shaped AI policies globally is the Principles on AI by the Organisation for Economic Co-operation and Development (OECD). Third in a list of five values-based principles, the OECD principle on transparency and explainability prescribes transparency and responsible disclosures around AI systems to ensure that people understand when they are engaging with them and can challenge relevant outcomes. This analysis is far broader in its conception of explainability and seeks to consider not only the system’s technical ability to be understood but the broader workings of the AI system as embedded in society and the ability of impacted actors within broader societal contexts to understand, accept, and trust the outcomes of these AI systems.

This article explores how realizing the concept of explainable AI could benefit from some subaltern propositions observed from an African context. One proposition is the incorporation of humans serving as AI explainers akin to griots or midwives, who can provide culturally contextualized and understandable explanations for this technology. Another proposition is for explainability to be modelled as a generative exercise that enables users to customize explanations to their language and receive communication in native dialects and familiar linguistic expressions. It is possible for explainability to not just benefit individual understanding but communities as a whole by recognizing human rights and related norms of privacy and collective identities.