Adopting AI and managing associated risks

With the theme 'Rebuilding Trust' at the World Economic Forum, Artificial Intelligence has taken center stage as a disruptor in emerging economies. Particularly in Africa, the concerns revolve around infrastructure and policies in adopting AI and managing associated risks. CNBC Africa's Tabitha Muthoni recently spoke with Kennedy Wangari, a Data Scientist at the University of Edinburgh, to delve into how Africa and East Africa, in particular, can best adopt AI and mitigate its risks. Kennedy Wangari emphasized the positive impacts of artificial intelligence, highlighting its ability to address challenges across various sectors such as climate change, finance, education, and agriculture. However, as AI continues to evolve, it presents a new set of challenges and concerns that necessitate the development of guidelines and regulations to steer developers, users, and organizations in the right direction. Wangari acknowledged the transformative power of AI while underscoring the importance of responsible implementation through robust governance. In terms of AI adoption in East Africa, Wangari noted significant progress within the African context, despite trailing behind more developed markets like Europe. He highlighted strides in infrastructural investments, research and development, talent cultivation, and the ongoing discussions on establishing AI policies and regulations tailored to the African landscape. By leveraging these advancements, Africa aims to harness the benefits of AI-driven innovation and avoid lagging behind on the global stage. Addressing governance issues, the conversation shifted to recent legislative challenges in Kenya, specifically the Information Communication Technology (ICT) Practitioners Bill. Wangari raised concerns over the potential stifling of innovation due to excessive regulations and emphasized the need for a balanced approach to governance in the AI sector. Reflecting on the intricate dynamics of policy formulation and implementation, he stressed the importance of maturing as a nation before implementing stringent regulations to ensure a conducive environment for AI development. Furthermore, Wangari highlighted the critical role of infrastructure in AI systems, emphasizing the three essential components of computation power, access to data, and talent. He underscored the need to achieve significant milestones in these areas before rushing into policy and regulation frameworks. By focusing on foundational elements such as infrastructure development and talent enhancement, East Africa can pave the way for responsible AI adoption and risk management. The discussion also touched upon the fear of AI displacing jobs and the concept of augmented intelligence, where human beings collaborate with technology to enhance productivity. Wangari reassured that AI is meant to augment human capabilities rather than replace them entirely. He emphasized the enduring value of skills like problem-solving, critical thinking, and interpersonal communication in a technology-driven landscape. By upskilling and adapting to AI advancements, individuals can remain relevant and contribute meaningfully to the evolving job market. In conclusion, Kennedy Wangari's insights shed light on the opportunities and challenges associated with AI adoption in East Africa. By striking a balance between innovation and regulation, prioritizing infrastructure development, and fostering a culture of continuous learning and adaptation, East African nations can navigate the complexities of AI implementation and harness its transformative potential.