Evaluating the Sufficiency of the data protection act 2023 in the age of Artificial Intelligence (AI): A comparative case study of Nigeria and the USA

Lionel Ebenibo 1, Joy Onma Enyejo 2, *, George Addo 3 and Toyosi Motilola Olola 4

1 Faculty of Law, University of Texas at Austin, Austin, Texas.
2 Department of Business Administration, Nasarawa State University, Keffi Nasarawa State.
3 Principal and Managing Attorney, Affum Addo & Associates, Washington DC, USA.
4 Department of Communications, University of North Dakota, Grand Forks, USA.
 
Review
International Journal of Scholarly Research and Reviews, 2024, 05(01), 088–107.
Article DOI: 10.56781/ijsrr.2024.5.1.0044
Publication history: 
Received on 12 August 2024; revised on 20 September 2024; accepted on 23 September 2024
 
Abstract: 
The rapid expansion of artificial intelligence (AI) has become a pivotal force in shaping modern society, drawing comparisons to the tech boom of the late 1990s and early 2000s. With AI applications ranging from military and defence systems to corporate tools and household devices, its transformative potential is undeniable. This paper examines the development and regulation of AI on a global scale, focusing on the legislative frameworks in Nigeria and the USA. Specifically, it evaluates the sufficiency of Nigeria's Data Protection Act 2023 in addressing the unique challenges posed by AI. By comparing Nigeria’s approach with that of the USA, the paper highlights key regulatory gaps, the distinction between AI and robotics, and the importance of establishing a legal personality for AI systems. The comparative analysis offers insights into how both countries are preparing for the future of AI, emphasizing the need for early legal intervention to ensure safe and ethical AI integration. Recommendations are provided for policymakers to strengthen regulatory mechanisms in both nations, ensuring they are equipped to handle the rapid evolution of AI technology.
 
Keywords: 
Artificial Intelligence (AI) Regulation; Data Protection Act 2023; Algorithmic Bias; Ethical AI Development; Transparency in AI; AI Governance Frameworks
 
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