The need for Legal and Ethical Frameworks for Artificial Intelligence in Artificial Reproduction Technology Practices in Africa: The Role of the African Union
1Michael Olugbenga Adeleke, 2Nike Oguntokun and 3Iyanuoluwa Racheal Ibironke
1School of Law, Kampala International University, Western Campus,
2College of Law, McPherson University, Km 75. Lagos-Ibadan Expressway, Seriki Sotayo, Ogun State, Nigeria.
3Legal scholar and researcher, Faculty of Law, Obafemi Awolowo University, Ile-Ife, Osun State, Nigeria.
INTRODUCTION
The term Artificial intelligence (AI) was coined by Standford Professor John McCarthy at the Dartmouth conference in 1956. It refers to systems that display intelligent behaviour by analysing their environment and taking action – with some degree of autonomy – to achieve specific goals.[1] According to the Organisation for Economic Co-operation and Development, AI is a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments.[2] From these definitions, it can be construed that AI systems are designed to operate with varying levels of autonomy and it leverages computers and machines to simulate and mimic human intelligence. AI is typically implemented as a system comprised of both software and hardware.[3] AI utilizes computational power, deep learning algorithms, and graphics processing units (GPU) produced by Nvidia’ to process vast datasets and derive insights to emulate cognitive functions such as tackling language understanding, learning, logical reasoning, problem-solving, and/or decision-making[4]. Deep learning refers to a class of algorithms which are based on artificial neural networks optimized to work with unstructured data such as images, voice, videos and text.[5] While GPU is an electronic circuit which manipulates and modifies the memory for better image output.[6] Deep learning involves huge amounts of matrix multiplications and other operations which can be massively parallelized and thus done on GPUs.[7] AI uses such algorithms to learn how to complete tasks through many rounds of trial and error.[8]
AI portfolio also involves Natural Language Processing (NLP), Robotics, Machine Learning, and Cognitive Computing.[9] Machine Learning (ML) is a particularly successful AI application.[10] It identifies patterns between variables in a large dataset. Most ML approaches can be classified as supervised, unsupervised or reinforcement learning.[11] Supervised ML uses labelled training data to develop models in which target results (such as a diagnosis) are known. In contrast, unsupervised ML recognizes patterns or aggregations that occur within data without requiring labelled data.[12] Reinforcement ML uses a system with reward and punishment methods to form a solution strategy to solve some problems.[13]
Presently, the adoption and use of AI is rapidly increasing. AI is becoming more widely adopted and integrated into many aspects of daily life, including commerce, health, education, communication, and public service, holding significant impact in almost all areas where human intelligence is involved.[14] AI can be used by businesses and institutions to optimize operations, promote innovations, and empower and supplement staff.[15] For instance, AI models can run in cars to avoid accidents,[16] in smartphones to perform various tasks,[17] in banks to manage investments and loans,[18] and in law enforcement to help officials recover evidence and make law enforcement easier. In the same vein, AI is used in hospitals to aid doctors. AI can effectively analyze and provide valuable insights
CITE AS: Michael Olugbenga Adeleke, Nike Oguntokun and Iyanuoluwa Racheal Ibironke (2025). The need for Legal and Ethical Frameworks for Artificial Intelligence in Artificial Reproduction Technology Practices in Africa: The Role of the African Union. NEWPORT INTERNATIONAL JOURNAL OF LAW, COMMUNICATION AND LANGUAGES, 5(2):1-11. https://doi.org/10.59298/NIJLCL/2025/5.2.11100