Table 1 Risks of AI use in Africa and measures to mitigate the risks.
From: Using artificial intelligence in support of climate change adaptation Africa: potentials and risks
Risk of AI use | Description | Mitigation measures |
|---|---|---|
Data privacy and security | Concerns over unauthorised data use and breaches. | Implement strong data protection laws and regulations; promote data literacy. |
Bias and discrimination | AI systems may perpetuate existing biases, leading to unfair outcomes. | Ensure diverse datasets; conduct regular audits and impact assessments to identify and mitigate biases |
Lack of infrastructure | Insufficient digital infrastructure can hinder AI deployment. | Invest in digital and telecommunications infrastructure; encourage public-private partnerships. |
Job displacement | Automation may lead to job losses in certain sectors. | Promote reskilling and upskilling programmes; invest in education to prepare the workforce for AI-related jobs. |
Regulatory challenges | A lack of clear regulations can lead to the misuse of AI technologies. | Develop comprehensive AI policies and frameworks that promote innovation while ensuring accountability |
Limited access to technology | Disparities in technology access can create inequities. | Increase access to technology through government programmes and public-private collaborations; invest in affordable internet initiatives. |
Ethical concerns | Concerns about the ethical use of AI, including surveillance and autonomy. | Establish ethical guidelines for AI development and use; engage stakeholders in discussions about ethical practices. |
Dependency on outsiders | Over-reliance on foreign technologies may hinder local innovation. | Encourage local AI development by supporting startups and research initiatives; foster knowledge transfer. |
Knowledge and skills gap | Limited expertise in AI technologies and implementation. | Expand education and training programmes in AI and data science; promote collaboration with academic institutions. |
