The rapid growth of AI is swiftly changing the world of work and business. Embedded in this growth is its potential to create new opportunities for gender equality. However, if not properly engaged or utilized, AI also has the capacity to reinforce gender bias, stereotypes, and discrimination. AI is gaining a lot of attention through advancements in machine learning and the increasing use of algorithms for pattern recognition. It is used across various fields and sectors to shape our economic, political, cultural, and social interactions; used in areas such as approval of bank loans, job recruitment, medical diagnostics, etc.

World leaders and governments are showing their commitment to the growth of AI by investing heavily in it. The US government’s federal spending on AI rose to almost $1billion in 2020 - which is about a 50% increase from its spendings in 2018 and the Canadian government also invested about $125million in its AI strategy in 2017. The private sector on the other hand has a leading position in investment in AI. Global total AI investment by the private sector was over $50billion in 2021 with Nvidia Corp and Alphabet Inc (Google) in the forefront, owning a large portion of about 50% of the total investment. However, with the issues of accountability and privacy violation prevalent in the present digital platform operation, leaving the powerful tool of AI unchecked can foster some of social issues in the digital space including gender discrimination. Therefore, in order to truly advance gender equality and women’s empowerment, gender considerations and issues alongside regulatory policies need to be mainstreamed in AI.

Gender Bias and AI

The gender bias found in AI takes up two forms. Bias in terms of the exclusion of women from the AI sector and Bias found in the building of algorithms. Gender equality in the workplace has been a critical issue for decades. About 80% of the male gender make up the workforce of the AI industry with only about 18% female machine learning researchers. It should be of great concern that women make up only a small percentage of the technological workforce; an industry that is seen as a force for societal transformation.

The first steps in building algorithms are the selections of training datasets. AI-generated patterns, predictions and recommended actions are reflections of the accuracy, universality and reliability of the data sets used, as well as the inherent assumptions and biases of the developers of the algorithms employed. Although one can say that AI is as good as the people behind it, it is important to note that one of the potentials of AI lies in its capacity to generate new solutions within the limits of inputs received. This is a fundamental aspect that needs to be kept in mind while training and implementing AI solutions for better gender equality.  Preventing gender biases in software applications, therefore, calls for better corporate governance that includes diversity in hiring and retention practices and enabling a work culture where gender equality principles are explicit and prioritise accountability.

Diverse teams made up of both men and women are not just better at recognizing skewed data, but they're also more likely to spot issues that could have or result in negative societal outcomes. Thus, emphasising the need for higher participation of women and gender experts in the process of principle formulations at the foundation level, and an improvement in the representation of women in technical roles and in the boardrooms of tech companies. Talent acquisition, as well as women empowerment, will therefore be critical in bridging the gender gap in AI and helping women gain their ground in the industry.

The way forward in bridging the gap

Considering the two forms of gender bias mentioned above, the following are highlights of key issues and proposed recommendations that need to be addressed in order to bridge the gender gap in the AI industry.

• In the building of algorithms, an inclusive unbiased dataset needs be used as AI learn from historical patterns by predicting the future based on the past. Therefore, using historical records to train AI without being cautious about these biases is like repeating history, but this time with a more powerful tool.
• Women need to be given opportunities to play an active role in shaping the next generation of technologies, so diversity is considered, and stereotypes are not reproduced.
• Capacity building and empowerment of women through education at the grass-root level to help them break into the AI sector. Creating awareness of the AI industry for girls in schools to spark their interest and also providing support for women making career change to easily transition into the sector.
• Creation of a robust and gender-inclusive AI guidelines, principles, and codes of ethics within the technology industry to help regulate activities in the sector.

Africa enters 2022 with a long and urgent to-do list. In this blog, Adedeji Adeniran joins other experts to outline key political, economic, security and health issues the continent must contend with as it maps its COVID-19 recovery and post-pandemic reality.

TRADE

Africa remains underrepresented in global trade, accounting for 2.19% of global exports and 2.85% of global imports in 2020. The African Continental Free Trade Area (AfCFTA) can reverse this trend if it is effectively implemented. Launched in January 2021, the agreement is a crucial step towards boosting regional trade and economic development, but full trading activity is yet to commence due to ongoing negotiations on various protocols.

Concluding negotiations on the agreement on rules of origin (the “legal provisions used to determine the nationality of a product in the context of international trade”) and protocols on trade in e-commence and services is a priority. While these are unavoidably complex, the strain on economic growth due to COVID-19 necessitates the acceleration of the AfCFTA.

The newly launched Pan-African Payment and Settlement System (PAPSS) holds potential: the platform, developed by Afreximbank and the AfCFTA Secretariat, is expected to bolster intra-African trade by facilitating simpler and secure cross-border payments and reducing payment transaction costs by $5 billion annually. The African Trade Gateway, AfCFTA Adjustment Facility and Trade Finance Facility are also expected to take off, making 2022 a promising year for the effective operation and success of regional economic initiatives. However, it will take much longer for the continent to fully recover from the economic shocks of the pandemic.

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With the explosion in digital technologies and data, countries across are grappling with effective ways to address the threats emerging in the digital space as well as provide supportive structure for digital technologies uptake. At present, at least 66 percent of countries in the world has at least a form of data protection laws. By data governance, we mean the processes and laws available in managing the availability, usability, integrity, and security of the data in the digital economy. African continent is not left out in the emerging structure with also proliferation of data governance and policies. However, UNCTAD report in 2020 noted that African region has the lowest adoption rate of the new technology and data protection laws.

CSEA has collected vast dataset to dive deep into the scope and coverage of digital development and evolution of data governance principles in Africa. This is under our project - Strengthening Data Governance in Africa. The Digital Governance Index was designed to evaluate Africa's level of digital development. The Index covers 54 African economies and is derived utilizing 21 dimensions to assess performance across three indicators

We performed detailed analytics (click here) on cross-country performance in these indicators.

The index is expected to be an indicator for assessing African’s digital evolution and uptake. This will help to pinpoint early and late adopters of the digital space as well as their pace. With awareness of the Digital Governance Index, governments and key stakeholders can adapt and integrate policy initiatives to strengthen requisite skills, provide efficient and inclusive digital services to all; bridge digital divides to order to fulfill the principle of leaving nothing behind while fostering economic development. Digital Governance Index will provide policymakers at national and regional level with information to support decision on digitalization policies.

The Covid-19 pandemic occurred at a time when sovereign debt had already increased substantially in Sub-Saharan Africa (SSA). Between 2010-2017, government debt as a share of GDP averaged 34.5% in SSA but increased significantly to 51.5% in 2019 (IMF 2021a, p. 25). Similarly, in SSA, official external debt as a share of GDP averaged about 15% between 2010-2017 but rose substantially to 23.6% in 2019 (IMF 2021a, p. 27). One main reason behind these accumulated debt levels was a shift in the debt structure from concessional towards more non-concessional financing with relatively higher interest rates. Increased debt ser-vice payments diminished fiscal space in most SSA countries. Moreover, non-concessional financing includes private credit, such as Eurobond issuance. Another reason is the growing momentum to close the continent’s infrastructure deficit, which the African Development Bank (AfDB) has estimated will cost about US$130 to US$170 billion annually (AfDB 2019).

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The Nigerian health system has suffered several setbacks. It is vastly under-resourced in terms of personnel and medical infrastructure. While this is a widespread problem, conditions in rural areas are often far worse compared to urban ones. Nigeria’s poor health system has resulted in penurious outcomes, prompting stakeholders to call for immediate government intervention. Yet, the government’s health expenditure is still significantly lower than the World Health Organization’s (WHO) recommendation of 15% of the annual budget.

Over the decades, the migration of medical doctors from Nigeria has increased. The NOI Poll in 2018 revealed that 88% of doctors in Nigeria were seeking employment abroad. Furthermore, between 2015 and 2021, about 4,528 Nigerian-trained doctors have migrated to the United Kingdom (UK). Even with the pandemic and existing health burdens in Nigeria, doctor’s migration has increased. This worrying trend exacerbates an already deteriorating health system. And it is unlikely to stop, as Nigerian doctors continue to seek better working conditions abroad.

Health Personnel Shortage and Migration

A WHO report revealed that Nigeria has a Doctor-Patient ratio of 4 doctors per 10,000 patients and five hospital beds per 10,000 patients.

With over 200 million people, it would take about 25 years to produce enough doctors to cater to the population, asserts the Nigerian Medical Association (NMA). This dire situation can only lead to poor health outcomes. High child and maternal mortality rates are preventable if doctors are readily available. The link between the number of physicians and mortality rates has been documented in the literature, reflecting the negative consequences of doctor shortages in Nigeria.

The primary reason for the large number of medical doctors emigrating each year is the lack of adequate funding in the sector. The 2021 health expenditure accounted for only 7% of the total budget. It is less than the 15% agreed on by African leaders and the WHO in 2001.

According to the NMA, approximately 2000 doctors leave the country each year. The average number of doctors trained in Nigeria and currently practising in the United Kingdom (UK) increased significantly between July 2020 and May 2021 – ranking Nigerian doctors the third highest in the UK.

In 2020 the highest monthly earnings of a Nigerian doctor were about USD 1,365. In Sierra Leone, a doctor earns up to USD 2,000, while doctors in the UK, United States, and Saudi Arabia earn up to ten times what doctors earn in Nigeria. It automatically increases the appeal of emigrating to these countries. Further, the lack of equipment in hospitals in Nigeria and poor working conditions mean that the opportunity cost of emigration is significantly low.

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