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Artificial intelligence (AI) presents unprecedented opportunities for Africa, and the increasing deployment of AI and other emerging technologies in African settings – healthcare, agriculture, socio-political processes, business and education – promises to change cultural dynamics.
Despite the obvious potential benefits of AI, the deployment and implementation of AI raises fundamental questions related to human rights, equity, privacy, bias, discrimination, security, climate change, and the future of work.
This highlights the importance of responsible AI.
However, a growing body of literature on responsible AI focuses more on the northern hemisphere context, while the African context is ignored or largely forgotten.
Elaborate on the importance of responsible AI, which takes into account Africa's context, interests, values, fears, hopes and aspirations.
It reviews the current and future AI landscape and then makes recommendations on how to conduct responsible AI discussions in and Africa.
AI offers exciting possibilities for African societies, among other things, to alleviate poverty, reduce economic inequalities, and improve access to public and private services in health, transportation, and education.
Although there is still a huge gap between Africa and other developed regions of the world in terms of dataset development, AI system development and deployment capabilities, AI is gaining attention in many aspects of African life.
Arguably, since many parts of Africa have not fully benefited from the first three industrial revolutions (electricity, production mechanization and industrial automation), the key element of the fourth industrial revolution (4IR) is artificial intelligence.
Africa's socio-economic structure, which raises the question of whether Africa should focus more on AI capacity-building than on receiving transferred technology from the Global North to ensure that all segments of society can fully benefit from the Fourth Industrial Revolution.
On the other hand, AI not only creates unprecedented opportunities to make a real impact on people's lives, but also raises fundamental questions such as fairness, human rights, privacy, bias, security, and the future of work.
The meaning of artificial intelligence is often debated between different disciplines, and although the field of research on intelligent machines was founded in the 50s of the 20th century, its history is very long. However, since Turing proposed can machines think? "After this question.
As a major branch of computer science, artificial intelligence has evolved significantly, involving the design and application of machines capable of performing tasks that would normally require human intelligence.
Alan Turing's paper on computing and intelligence can be said to have laid the fundamental goal of artificial intelligence, and John McCarthy organized a conference at Dartmouth in 1956.
The term artificial intelligence was first adopted, and McCarthy and Marvin Minsky are considered two pioneers in the field, and then co-founded the Artificial Intelligence Project (now the MIT Artificial Intelligence Laboratory) in 1959.
to explore the potential of artificial intelligence. Since then, the term has been defined differently in the research and innovation ecosystem.
Defining artificial intelligence as "the science of getting machines to do things that require human intelligence to do" mirrors the earlier definition of artificial intelligence proposed by McCarthy and others.
As a question of "getting machines to behave in a way that is called intelligent," Russell and Norvig answer Turing's question in their book Artificial Intelligence: A Modern Approach, describing AI as "the study of agents that receive rules from the environment and perform actions."
They further reveal four different approaches in the history of AI, including human thinking, rational thinking, human action, and agents of rational action.
Status of AI deployment in Africa
The level of AI deployment (as defined in this chapter) in Africa continues to increase, with areas of adoption including: healthcare, education, transportation, financial services, agriculture, public services, security, enterprise management, and telecommunications.
Some of the AI systems deployed in these areas are highlighted, and it is worth noting that many of these systems were developed by local experts but are most influenced, sponsored or controlled by large northern hemisphere tech companies.
Financial Services
Financial services is another area where AI is deployed in Africa, and in Kenya, M-Shwari has developed a system that relies on AI to review online loan applications to help it consider applications from customers living far from bank branches.
Similarly, in Egypt, Cassbana relies on AI to create digital identities for underserved communities so that they can be integrated into the banking system. It also manages their financial requests and establishes a behavior-based scoring system for them.
In Nigeria, African debtor Kudi are two AI applications deployed in the financial sector.
Debtors Africa uses artificial intelligence to automatically update its independent, searchable database of recalcitrant and delinquent debtors, providing the status of debtors in real time; Kudi, on the other hand, is a chatbot that responds to financial requests and allows users to send money and pay bills.
Security services
The private and public safety sectors are also deploying AI systems, and in order to address the well-documented risks of misidentification, unfair discrimination and bias against black people when using biometric surveillance technology, the Ghanaian BACE Group of Companies has developed BACEAPI.
Black people can be accurately identified through facial recognition technology, and the company provides secure authentication as a security service for both the public and private sectors.
Similarly, in Kenya, as part of the Safe City Project, the government deployed AI-driven facial recognition technology to complement policing.
The technology was developed by Chinese tech giant Huawei, and concerns have been raised about the lack of regulation to ensure responsible use of the technology, given the well-documented legal, ethical and sociocultural issues associated with facial recognition (Feldstein).
That's because there are reports that the Ugandan government is buying similar technology from Huawei to spy on political opponents, and Tabili Analytics (deployed in Rwanda, Kenya and Uganda) is also used to provide continuous surveillance services to protect against cyber threats.
The system utilizes cloud computing, machine learning, and artificial intelligence to automatically perform manual analysis of IT system log data for network security. Global Automotive Systems also uses data and system analysis to provide safety systems for schools, colleges, and universities in Uganda.
educate
In Uganda, M-Shule developed and deployed a toolkit to help learners engage in interactive, self-paced and personalized learning via SMS, develop academic and life skills, measure progress and performance, and keep stakeholders up to date on awareness campaigns and situational response information.
It also helps to collect data and insights from stakeholders via SMS to make real-time decisions.
In Kenya, Eneza Education is providing primary and secondary school students with virtual tutorials for primary and secondary school students in all subjects that match the curriculum content, using artificial intelligence to connect qualified tutors with students in specific fields and within budget.
It also verifies the identity of the mentor, conducts background checks and evaluates the mentor's performance, and in South Africa, the Botlhale AI solution focuses on conversational AI. With a suite of natural language processing tools, the company ensures that those who speak African languages don't miss out on the benefits of technology.
Transportation & Logistics
AI is also transforming the transportation sector in some African countries, with AI applications deployed in Egypt, SWVL, and Softtech 21 countries, making a huge impact.
SWVL uses AI to coordinate private bus fleets to get commuters around the often congested public transport network, while Softech uses AI to help commuters plan trips by collecting and analyzing traffic condition data.
Softech provides AI-based digital planners and solutions for commercial fleets, providing end-to-end visibility and command and control for B2B logistics, transportation, and mobility operations.
In Kenya, Amitluk was used to create a digital marketplace for freight; Connect transporters and customers on digital platforms, while Côte d'Ivoire uses Kamtar to connect shippers and carriers.
Kobo 360 also leverages big data analytics and technology to reduce logistics friction in Nigeria, with the overall goal of ensuring the efficiency and cost reduction of the supply chain.
telecommunications
In the telecommunications sector, MTN (a mobile telecommunications operator operating in Benin, Cameroon, Ghana, Guinea-Bissau, Côte d'Ivoire, Nigeria, Rwanda, South Africa, Uganda and Zambia) has launched a chatbot that can streamline and improve the quality of the customer experience.
Similarly, Oraidou's 25 partners partnered with PI Works, an artificial intelligence company, to enhance customer experience, network coverage and connectivity in the MENA region, particularly Tunisia and Algeria.
Safaricom has also launched an AI chatbot assistant to popular messaging service WhatsApp to perform telecommunications-related tasks and answer queries about Kenya's M-PESA (mobile money service).
agriculture
AI Mozambique, tractors are helping farmers share equipment, and it is also using machine learning to predict crop yields and facilitate farmers' access to finance.
Other AI tools used in agriculture include Agrix Tech Cameroon, which helps farmers detect crop diseases and proposes sustainable and environmentally friendly solutions to small-scale farmers and PlantVillage Nuru as a tool for diagnosing crop diseases.
In Egypt, Abu Edan used deep learning neural networks and predictive analytics algorithms to predict the future performance of chickens.
Apollo Agriculture uses satellite data and machine learning to advise farmers on credit decisions and automated operations to keep costs low and processes scalable.
Similarly, aerobatics are being deployed in South Africa to help farmers/growers make informed decisions, and the app uses artificial intelligence to collect and analyze crop yield data and subsequently predict future performance.
Africa's AI scene is dotted with large tech companies from the northern hemisphere, including Google, Facebook, Alibaba Group, Amazon, Microsoft and IBM Research.
These companies bring improved capabilities and infrastructure to make data more pervasive and valuable, which AI and other emerging technologies can use to drive Africa's massive transformation and make the continent more competitive.
This will require increased sharing of data processing systems, interoperability, and significant convergence of emerging technologies.
AI offers many sectors a good opportunity to optimize solutions to African problems. The future of much of Africa's public and private sectors will be closely linked to the future of AI.
In addition to this, Africa offers opportunities for global AI design and implementation to be diverse and versatile in terms of datasets, skill sets, and people to enable responsible AI.
The massive amount of data collected from the Northern Hemisphere exacerbates the ongoing challenge of unfair bias and discrimination in AI, and the data, values and people who build and deploy AI should include representatives from African backgrounds.
The focus on diversity ensures better AI outcomes through reliable insights from sufficiently representative datasets. A recent report on AI in sub-Saharan Africa notes that such representation should not be just a ticking exercise.
And it must be seen as an ethical imperative for all stakeholders (Ndung'u and Signe) who should appreciate the intrinsic value of the different interests, expectations, and perspectives inherent in AI data.
The inclusion of new voices, perspectives and datasets provides new opportunities to design solutions for more people.
We mention and recognize the importance of embedding African value systems and principles through philosophies such as Ubuntu, Ujamma, etc. as we seek to build truly responsible AI for Africa.
It is for this reason that we mention and recognize the importance of embedding African value systems and principles through philosophies such as Ubuntu, Ujamma, etc. as we seek to build truly responsible AI for Africa.
Responsible AI in this context means thinking, predicting, designing, implementing, adopting, adapting and using AI that connects, is public, respectful and unites with different stakeholders to achieve the common good and address the challenges facing Africa, the face.
Bibliography;
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[4] Starr, BC, 2021. AI for a Better Future: An Ecosystem Perspective on the Ethics of AI and Emerging Digital Technologies.
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