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

• URL: http://arxiv.org/abs/2604.06018v2
• Date: Wed, 08 Apr 2026 11:59:02 GMT
• Title: Governance and Regulation of Artificial Intelligence in Developing Countries: A Case Study of Nigeria
• Abstract summary: This study examines the perception of legal professionals on the governance of AI in developing countries, using Nigeria as a case study.<n>Data were collected through 27 semi-structured interviews with legal practitioners in Nigeria.<n>Findings showed that there were concerns about data privacy risks and the lack of enforceable legal frameworks.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

Related papers

• Security, privacy, and agentic AI in a regulatory view: From definitions and distinctions to provisions and reflections [53.468443050795344]
  The rapid proliferation of artificial intelligence (AI) technologies has led to a dynamic regulatory landscape.<n>As AI paradigms shift towards greater autonomy, specifically in the form of agentic AI, it becomes increasingly challenging to articulate regulatory stipulations.<n>This paper reviews the evolving European Union (EU) AI regulatory provisions via analyzing 24 relevant documents published between 2024 and 2025.
  arXiv  Detail & Related papers  (2026-03-19T13:50:52Z)
• Mirror: A Multi-Agent System for AI-Assisted Ethics Review [104.3684024153469]
  Mirror is an agentic framework for AI-assisted ethical review.<n>It integrates ethical reasoning, structured rule interpretation, and multi-agent deliberation within a unified architecture.
  arXiv  Detail & Related papers  (2026-02-09T03:38:55Z)
• Algorithmic Criminal Liability in Greenwashing: Comparing India, United States, and European Union [0.0]
  This study conducts a comparative legal analysis of criminal liability for AI-mediated greenwashing across India, the US, and the EU.<n>Existing statutes exhibit anthropocentric biases by predicating liability on demonstrable human intent, rendering them ill-equipped to address algorithmic deception.
  arXiv  Detail & Related papers  (2025-12-14T20:49:41Z)
• Argumentation-Based Explainability for Legal AI: Comparative and Regulatory Perspectives [0.9668407688201359]
  Artificial Intelligence (AI) systems are increasingly deployed in legal contexts.<n>The so-called black box problem'' undermines legitimacy of automated decision-making.<n>XAI has proposed a variety of methods to enhance transparency.
  arXiv  Detail & Related papers  (2025-10-13T07:19:15Z)
• Trustworthiness of Legal Considerations for the Use of LLMs in Education [0.0]
  This paper offers a comparative analysis of AI-related regulatory and ethical frameworks across key global regions.<n>It maps how core trustworthiness principles, such as transparency, fairness, accountability, data privacy, and human oversight are embedded in regional legislation and AI governance structures.<n>The paper contributes practical guidance for building legally sound, ethically grounded, and culturally sensitive AI systems in education.
  arXiv  Detail & Related papers  (2025-08-05T07:44:33Z)
• The Role of Legal Frameworks in Shaping Ethical Artificial Intelligence Use in Corporate Governance [0.0]
  This article examines the evolving role of legal frameworks in shaping ethical artificial intelligence (AI) use in corporate governance.<n>It explores key legal and regulatory approaches aimed at promoting transparency, accountability, and fairness in corporate AI applications.
  arXiv  Detail & Related papers  (2025-03-17T14:21:58Z)
• Ethical Implications of AI in Data Collection: Balancing Innovation with Privacy [0.0]
  This article examines the ethical and legal implications of artificial intelligence (AI) driven data collection, focusing on developments from 2023 to 2024.<n>It compares regulatory approaches in the European Union, the United States, and China, highlighting the challenges in creating a globally harmonized framework for AI governance.<n>The article emphasizes the need for adaptive governance and international cooperation to address the global nature of AI development.
  arXiv  Detail & Related papers  (2025-03-17T14:15:59Z)
• Media and responsible AI governance: a game-theoretic and LLM analysis [61.132523071109354]
  This paper investigates the interplay between AI developers, regulators, users, and the media in fostering trustworthy AI systems.<n>Using evolutionary game theory and large language models (LLMs), we model the strategic interactions among these actors under different regulatory regimes.
  arXiv  Detail & Related papers  (2025-03-12T21:39:38Z)
• The Fundamental Rights Impact Assessment (FRIA) in the AI Act: Roots, legal obligations and key elements for a model template [55.2480439325792]
  Article aims to fill existing gaps in the theoretical and methodological elaboration of the Fundamental Rights Impact Assessment (FRIA)<n>This article outlines the main building blocks of a model template for the FRIA.<n>It can serve as a blueprint for other national and international regulatory initiatives to ensure that AI is fully consistent with human rights.
  arXiv  Detail & Related papers  (2024-11-07T11:55:55Z)
• Towards Responsible AI in Banking: Addressing Bias for Fair Decision-Making [69.44075077934914]
  "Responsible AI" emphasizes the critical nature of addressing biases within the development of a corporate culture. This thesis is structured around three fundamental pillars: understanding bias, mitigating bias, and accounting for bias. In line with open-source principles, we have released Bias On Demand and FairView as accessible Python packages.
  arXiv  Detail & Related papers  (2024-01-13T14:07:09Z)
• Regulation and NLP (RegNLP): Taming Large Language Models [51.41095330188972]
  We argue how NLP research can benefit from proximity to regulatory studies and adjacent fields. We advocate for the development of a new multidisciplinary research space on regulation and NLP.
  arXiv  Detail & Related papers  (2023-10-09T09:22:40Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.