Governance and Regulation of Artificial Intelligence in Developing Countries: A Case Study of Nigeria

TL;DR

This study explores Nigerian legal professionals' perceptions of AI governance, highlighting ethical risks, regulatory gaps, and the need for context-specific, inclusive legal frameworks to ensure responsible AI development in developing countries.

Contribution

It provides qualitative insights into local perceptions of AI regulation in Nigeria, emphasizing the importance of tailored governance models over foreign frameworks.

Findings

Concerns about data privacy and lack of enforceable legal frameworks.

Limited confidence in institutional capacity for AI regulation.

Support for locally adapted, inclusive governance models.

Abstract

This study examines the perception of legal professionals on the governance of AI in developing countries, using Nigeria as a case study. The study focused on ethical risks, regulatory gaps, and institutional readiness. The study adopted a qualitative case study design. Data were collected through 27 semi-structured interviews with legal practitioners in Nigeria. A focus group discussion was also held with seven additional legal practitioners across sectors such as finance, insurance, and corporate law. Thematic analysis was employed to identify key patterns in participant responses. Findings showed that there were concerns about data privacy risks and the lack of enforceable legal frameworks. Participants expressed limited confidence in institutional capacity and emphasized the need for locally adapted governance models rather than direct adoption of foreign frameworks. While some expressed optimism about AI's potential, this was conditional on the presence of strong legal oversight and public accountability. The study contributes to the growing discourse on AI governance in developing countries by focusing on the perspectives of legal professionals. It highlights the importance of regulatory approaches that are context-specific, inclusive, and capable of bridging the gap between global ethical principles and local realities. These insights offer practical guidance for policymakers, regulators, and scholars working to shape responsible AI governance in similar environments.