Figure 10: Promotion and Compliance Strategies for AI Ethical Policy in Africa.
Monitoring: • Good monitoring and best practices should be put in place. • Monitor the use of Al policies from time to time.
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Education and Awareness: • Create awareness and education campaigns about Al and its ethics. • Talk about the bennefits of Al and how it cann increase productivity.
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Penalties: • Enforce penalties for non-compliance.
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Incentives for complicance: • Provide incentives to promote compliance.
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Collaboration: • Policymalers should engage the stakehodlers when developing the Al policies from the inception to implemenation stage.
4.2 Discussion Artificial Intelligence is the foundation of digital transformation and business innovation of Africa, hence, leading the new stage of advancing industries and technologies and making decisions that can affect the future in Africa (Stern et al. 2023). With the wide use and application of AI in everything, from automated predictive models in agriculture and financial sectors to diagnostic systems in the healthcare domain, concerns have emerged on the liability and responsibility in the use and application of AI. Liability is the obligation of an individual to compensate the injured party for the damage suffered. “African legal systems, like other international legal systems, do not provide a clear answer to this question (Jaldi 2023). AI is an immaterial entity with no legal personality or assets, so it cannot be held responsible for its actions. As a result, and because artificial intelligence is immaterial (software), but embedded in machines (hardware), it is difficult
to extract its specific behavior beyond the action it co-commands with man. However, its growing autonomy (co-learning) will make it increasingly independent of human action”. Hence, there is a need for a policy for AI which guides effective protection to potential victims. Whereas, Responsible AI principles must ensure that transparency, fairness, and accountability are guaranteed in the underlying principles of adoption, development, implementation and use with a high human-centred consideration. The study findings indicate that some of the data-driven decision-making solutions are susceptible to inaccuracies, discriminatory outcomes, embedded and exacerbated bias, and even unintended consequences due to various limitations that occur through the process. Nevertheless, there is a scarcity of pertinent policies that prioritise AI development and its application in Africa while addressing potential social repercussions.
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Ethical Horizons - Mapping AI Policy in Africa May, 2024
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